Characteristics of Energy Storage Devices in Piezoelectric Energy Harvesting Systems
锂电池正极材料和前驱体

锂电池正极材料和前驱体Lithium-ion batteries play a crucial role in powering many of our electronic devices, from smartphones to electric vehicles. One of the key components of these batteries is the positive electrode material, which is responsible for storing and releasing lithium ions during charge and discharge cycles. The development of high-performance positive electrode materials is essential for improving the energy density, power output, and lifespan of lithium-ion batteries.锂离子电池在许多电子设备中发挥着至关重要的作用,从智能手机到电动汽车。
其中一个关键组件是正极材料,它在充放电周期中负责储存和释放锂离子。
高性能正极材料的开发对于提高锂离子电池的能量密度、功率输出和寿命至关重要。
There are various types of positive electrode materials that have been investigated for lithium-ion batteries, including lithium cobalt oxide (LiCoO2), lithium iron phosphate (LiFePO4), and lithium nickel manganese cobalt oxide (LiNixMnyCozO2). Each material has its own unique set of characteristics, such as energy density, cycling stability,and cost. Researchers are continuously exploring new materials and formulations to improve the performance of lithium-ion batteries.有各种类型的正极材料被研究用于锂离子电池,包括氧化钴锂(LiCoO2)、磷酸铁锂(LiFePO4)和氧化镍锂锰钴(LiNixMnyCozO2)。
energy storage material的endnote 模板 -回复

energy storage material的endnote 模板-回复Title: Revolutionary Energy Storage Materials: Unlocking the Future of Sustainable Power GenerationIntroduction:Energy storage is a critical component of sustainable power generation as it allows renewable energy sources to be harnessed efficiently and provides backup power during peak demand periods. Energy storage materials play a pivotal role in enhancing the overall performance and durability of energy storage systems. This article aims to explore the significance of energy storage materials, shed light on their characteristics, highlight recent advancements, and discuss their potential applications.1. Definition and Importance of Energy Storage Materials: Energy storage materials refer to substances that enable the storage and release of energy. These materials are crucial for stabilizing electrical grids, optimizing the performance of renewable energy systems, and increasing the reliability and resilience of power generation networks. They store energy during periods of low demand and discharge it during peak hours or when renewable energy sources are fluctuating.2. Key Characteristics of Energy Storage Materials:Energy storage materials should possess specific characteristics to ensure optimal performance, efficiency, and reliability. These characteristics include high energy density, excellent cycling stability, rapid charge/discharge capabilities, long-term stability, low self-discharge rates, and environmental friendliness. The material's ability to store and release energy without significant loss over repeated cycles is particularly important for long-term use.3. Advances in Energy Storage Materials:a. Lithium-ion Batteries: Lithium-ion batteries have gained widespread popularity due to their high energy density, long cycle life, and low self-discharge rates. Recent advancements focus on improving the battery's capacity and reducing costs.b. Solid-State Batteries: Solid-state batteries offer improved safety, longer lifespan, and higher energy density compared to conventional lithium-ion batteries. Researchers are exploring various materials, such as solid electrolytes, to enhance the performance and stability of these batteries.c. Supercapacitors: Supercapacitors provide high power densityand fast charge/discharge rates. Advances in electrode materials and nanotechnology are enabling the development of supercapacitors with even higher energy storage capabilities.d. Flow Batteries: Flow batteries employ liquid electrolytes stored in external tanks, allowing for scalable energy storage. Materials like vanadium and organic compounds are being investigated for their potential in improving the energy density and cycling stability of flow batteries.e. Hydrogen Storage Materials: Hydrogen storage materials, such as metal hydrides and porous materials, hold promise for efficient and safe storage of hydrogen, a clean and abundant fuel source.4. Potential Applications of Energy Storage Materials:Energy storage materials have immense potential in various sectors:a. Renewable Energy Integration: Energy storage systems equipped with advanced materials can enhance the integration of renewable energy, ensuring a steady power supply even when sunlight or wind availability fluctuates.b. Grid Stability Enhancement: By storing excess energy duringoff-peak hours and discharging it during peak periods, energy storage materials contribute to grid stability and reduce the needfor fossil fuel-based power generation.c. Electric Vehicles: High-performance energy storage materials enable longer driving ranges, faster charging times, and enhanced overall performance of electric vehicles.d. Remote Power Generation: Energy storage materials can optimize power generation in remote areas, reducing reliance on traditional generators and minimizing carbon emissions.e. Grid-Independent Power Supply: Energy storage materials facilitate the development of microgrids or off-grid systems, ensuring a reliable power supply without dependence on the main grid.Conclusion:Energy storage materials hold the key to unlocking the full potential of sustainable power generation. Constant advancements in material science and engineering are paving the way for more efficient, reliable, and cost-effective energy storage systems. As the world transitions towards a more sustainable energy future, the development and utilization of such materials will play a pivotal role in achieving global climate goals and ensuring energy security.。
锂电池中化成和分容英文缩写

锂电池中化成和分容英文缩写Lithium-ion Battery Formation and Capacity Fading MechanismsLithium-ion batteries have become the dominant energy storage technology in a wide range of applications, from portable electronics to electric vehicles and grid-scale energy storage systems. The success of lithium-ion batteries can be attributed to their high energy density, long cycle life, and relatively low cost. However, the performance and reliability of lithium-ion batteries are heavily influenced by complex electrochemical and structural changes that occur during their operation, particularly during the initial charge and discharge cycles, known as the formation process, and over extended cycling, which can lead to capacity fading.The formation process in lithium-ion batteries is a critical step that determines the initial performance and long-term stability of the battery. During this process, a series of electrochemical reactions occur at the electrode-electrolyte interface, leading to the formation of a stable solid electrolyte interphase (SEI) layer on the negative electrode. The SEI layer plays a crucial role in protecting the electrode from further decomposition of the electrolyte and ensuring the reversible intercalation of lithium ions. The formation processtypically involves several charge-discharge cycles, during which the capacity of the battery gradually increases and stabilizes.The formation process can be divided into several stages, each with its own characteristics and implications for the battery's performance. The first stage involves the initial reduction of the electrolyte components, such as the organic solvents and lithium salts, at the surface of the negative electrode. This results in the formation of a thin, passivating layer that helps to prevent further electrolyte decomposition. The second stage involves the gradual thickening and stabilization of the SEI layer, as additional electrolyte components are reduced and incorporated into the layer.The final stage of the formation process involves the lithiation and delithiation of the active materials in both the positive and negative electrodes. During this stage, the capacity of the battery gradually increases as the lithium ions are reversibly intercalated and deintercalated from the electrode materials. The successful completion of the formation process is crucial for ensuring the long-term stability and performance of the lithium-ion battery.In addition to the formation process, capacity fading is another important aspect of lithium-ion battery performance. Capacity fading refers to the gradual loss of the battery's energy storage capacity over time, which can be caused by a variety of factors, includingelectrode degradation, electrolyte decomposition, and structural changes within the battery.One of the primary mechanisms of capacity fading in lithium-ion batteries is the gradual loss of active lithium inventory, which can occur due to the irreversible consumption of lithium ions during the formation of the SEI layer and other side reactions. As the SEI layer continues to grow and evolve over extended cycling, it can become thicker and less permeable to lithium ions, leading to a decrease in the battery's capacity.Another important mechanism of capacity fading is the degradation of the electrode materials, which can be caused by various factors, such as volume changes during lithiation and delithiation, mechanical stress, and chemical reactions with the electrolyte. These degradation processes can lead to the loss of active material, the formation of inactive regions within the electrode, and the loss of electrical contact between the active material and the current collector.In addition to these electrochemical and structural changes, capacity fading can also be influenced by environmental factors, such as temperature and state of charge (SOC). High temperatures and high SOC can accelerate the rate of capacity fading, as they can promote the decomposition of the electrolyte and the formation of additionalSEI layer components.To mitigate the effects of capacity fading and improve the long-term performance of lithium-ion batteries, researchers have developed a variety of strategies, including the design of advanced electrode materials, the optimization of electrolyte formulations, and the implementation of sophisticated battery management systems. These strategies aim to minimize the irreversible loss of active lithium, reduce the rate of electrode degradation, and maintain the structural integrity of the battery components throughout its lifetime.In conclusion, the formation process and capacity fading mechanisms in lithium-ion batteries are complex and interrelated phenomena that have a significant impact on the overall performance and reliability of these energy storage devices. Understanding these mechanisms and developing effective strategies to address them is crucial for the continued advancement and widespread adoption of lithium-ion battery technology.。
10 英文调节能量存储,以适应可变能源资源的高渗透

Abstract —The variability and non-dispatchable nature of wind and solar energy production presents substantial challenges for maintaining system balance. Depending on the economical considerations, energy storage can be a viable solution to balance energyproduction against its consumption. This paper proposesto use discrete Fourier transform (DFT) to decompose the required balancing power into different time-varying periodic components, i.e., intra-week, intra-day, intra-hour, and real-time. Each component can be used to quantify the maximum energy storage requirement for different types of energy storage. This maximumrequirement is the physical limit that could betheoretically accommodated by a power system. The actual energy storage capacity can be further quantified within this limit by the cost-benefit analysis (future work). The proposed approach has been successfully used in a study conducted for the 2030 Western Electricity Coordinating Council (WECC) system model.Some results of this study are provided in this paper.Index Terms —Imbalance power, energy storage, integration of variable resources, discrete Fourier transform, WECC System.I. I NTRODUCTIONigh penetrations of variable energy resourcescreate significant uncertainty in required powergeneration, needed to balance the energy productionagainst the consumption [1-2]. New technologies, suchas new wind and solar forecasting tools, demand-sidecontrol, fast start-up units, and many others have beenproposed to address this balancing issue [1]. Amongthose options, energy storage can be a viable solutionbecause of its fast response and control flexibility [3-4].A. Energy Storage as an Ancillary Service Resource Today, many electricity storage technologies, including pumped hydro, various batteries,Yuri V. Makarov, Michael C.W. Kintner-Meyer, Pengwei Du, and Chunlian Jin are with the Energy Science and Technology Division, Pacific Northwest National Laboratory, P.O. Box 999, MSIN: K5-20, Richland, WA - 99352, USA (e-mail: yuri.makarov@, michael.kintner-meyer@, pengwei.du@,chunlian.jin@). Howard F. Illian is with Energy Mark, Inc. 334 Satinwood Ct,. N.Buffalo Grove, Illinois, 60089 (email:howard.illian@).compressed air, flywheels, capacitors, and others are proposed or already used to control the grid [3-6]. Energy storage (ES) systems can be used to follow the net load changes, stabilize voltage and frequency, manage peak loads, improve power quality, and ultimately support renewable integration. A summary of performance requirements needed for a variety of energy storage applications can be found in [6]. Wind and solar power variations are hard to predict and cause multiple impacts including the impact on system reliability. To maintain balance betweengeneration and load, costly flexible generation resources that have sufficient start up time, ramping speed, and capacity may be employed. Alternatively, energy storage for periods from days to less than 1 hour can help to smooth out unpredicted power fluctuations. For the intra-hour variations, energy storage can provide essential ancillary services such as fast regulation and load following. This would have great advantages because fast regulation may be twice as effective as gas turbines and 20 times more effective than steam turbines [7]. Therefore, the short-term ES represents a new perspective class of ancillary service resource.The 2007 FERC 1Order No. 890 allows so-called “non-generation” resources like energy storage toparticipate in regulation markets on a non-discriminatory basis. Since then, new market ruleshave been developed by some Independent SystemOperators (ISOs). For example, the New York ISOalready started to support the integration of limitedenergy storage resources (LESR) [8].The balancing ancillary services represent anattractive business opportunity for ES. Numerousresearch and demonstration projects in this area have been planned or currently under development. Forexample, Beacon Power Corporation is constructing the grid-scale 20 MW flywheel plant in Stephentown, New York, in an attempt to provide approximately 10% of New York's overall frequency regulation needs. AES has tested an Altairnano lithium-titanatebattery (2MW/500kWh) in a pilot program with California ISO. Furthermore, the Department of Energy’s American Recovery and Reinvestment Act1FERC stands for Federal Energy Regulatory CommissionSizing Energy Storage to Accommodate High Penetration of Variable Energy ResourcesYuri V. Makarov, Michael C.W. Kintner-Meyer, Pengwei Du, Chunlian Jin, and Howard F. IllianH(ARRA) stimulus funding is sponsoring 37 projects with a combined value of 637 million dollars, which combine smart grid and energy storage functionality [9]. This will greatly accelerate the entrance of ES into the power grid, in particular, the module, distributed ES (e.g. community energy storage, plug-in hybrid electric vehicles). If modeled and controlled properly, these aggregated small-size ESs can provide the ancillary services cost-effectively. In view of these, it can be envisioned that ES will become more integral to the grid operation, and play a key role in providing ancillary service to enable a high penetration of wind power and other renewable resources [9].B. Sizing of Energy StorageAmong other characteristics, an energy storage can be characterized by its energy capacity (MWh), power capacity (MW), round-trip efficiency, and ramping capability. The capital cost of energy storage consists of an energy component ($/MWh) and a power component ($/MW). The former represents the cost of the storage medium, and the latter represents the cost associated with the power electronics. The current cost for energy storage is still relatively high. However, as mentioned above, several companies are exploring the competitiveness of their novel storage technologies in very specific high-value markets. These markets usually require short duration energy storage, which power output can be sustained at the rated power capacity level from 15 to 20 minutes. Longer duration energy storage (for over several hours or for a day) are generally pumped hydro or compressed air energy storage technologies, which generally are less flexible in their placement compared to battery or flywheel energy storage. Both from a transmission planning and technology development points of view it is of interest to estimate the total market size for different energy storage systems.In this context, the optimal operation and sizing of ES is a subject of intensive research work. Stochastic optimization has been proposed to find the optimal sizing of energy storage so as to maximize the expected operation profit (or minimize the cost) while taking into account transmission constraints [10-15]. In [16], battery energy storage (BES) is used in conjunction with a wind farm. The capacity of BES is determined to ensure constant dispatched power to the grid while the voltage level across the dc-link of the buffer is kept within preset limits. Some authors used probabilistic methods to model the operation of energy storage [6]. They evaluated two potential control strategies, i.e., the energy is released as soon as the local network can absorb it, or the energy is stored and is sold when the price of electricity is higher. The value of storage in relation to power rating and energy capacity was investigated so as to facilitate appropriate sizing. The BES storage device can be used to reinforce the dc bus during transients, thereby enhancing its low-voltage ride through capability. When properly sized, it can effectively damp short-term power oscillations, and provide superior transient performance over a number of seconds [17]. Using a BES unit to provide frequency regulation was discussed in [11].State-of-the-art ES models that would be appropriate for transmission and distribution uses were reviewed in [9]. They can be used for optimizing storage size for ancillary services.C. Need for Sizing Tools for Power Systems Planners This paper presents a novel perspective on the sizing issue of grid-scale ES for utilities which are concerned with the system flexibility characteristics needed to mitigate the volatility of wind and solar power. Essentially, the maximum size of ES can be decided upon the cycling components of the required balancing power. Previous research work conducted at the Pacific Northwest National Laboratory (PNNL) studied the capacity requirement of energy storage in WECC for year 20302[18]. The follow-up work reported in this paper aims at determining the maximum feasible size of energy storage by identifying different cycling components of the balancing power. This proposed approach does not use either production cost models or comprehensive storage models. It is based on the fact that an energy storage cycles energy within certain frequency range. For example, a flywheel can cycle energy 4 cycles per hour or even faster if the full energy capacity is used. To find the maximum cycling requirements at different frequencies, a frequency decomposition of the balancing power signal is used in the paper. The components of this decomposition are periodic signals with zero total energy, representing the cycling job for the energy storage. These periodic components also indicate the duration requirements for storage technologies. Ultimately an optimal allocation of storage technologies can be determined based on this cycling analysis.This paper is organized as follows. Section II discusses the basic methodology to decompose the 2 Internal PNNL study that estimated the technical potential of the energy storage for meeting new balancing requirements in the WECC for a 88 GW wind power scenario.balancing power using discrete Fourier transform (DFT). Section III presents the simulation results for the 2030 WECC system model. Section IV provides the final discussion and conclusions.II. D ECOMPOSITION OF B ALANCING P OWER U SINGDFTThe balancing process consists of several components, including scheduling, load following, andregulation. While the scheduling component usuallyreflect hourly dispatches of generation units providing most of the energy to the load, the load following and regulation components help to achieve intra-hour balance by covering the gap between the hourly schedules and minute-by-minute system load.A. Balancing Power The power system control objective is to minimize area control error (ACE) to the extent sufficient to comply with the North American Electric Reliability Corporation (NERC) Control Performance Standards (CPS). Therefore, regulation and load following signals are signals that oppose deviations of ACE from zero: ()10()a s a s ACE I I B F F -=--+- (1) where subscript a denotes actual, s denotes schedule, Istands for interchange between control areas, F standsfor system frequency, and B is the system frequency bias (MW/0.1 Hz, a negative value). The generation output consists of two components:a s dev G G G =+(2)where subscript s refers to hour-ahead schedule 3, and dev refers to the deviation from the schedule.Similarly, the load can be separated into twocomponents as follows:_a f ha dev L L L =+ (3)where L f_ha is hour-ahead load forecast.Based on the assumption that_s f haG L =(4)the difference between the actual load, L a , and theforecasted load, L f_ha , represents the load deviation that is compensated by generators (or energy storage) procured for load following and regulation processes. _dev a f ha a s L L L L G =-=- (5) Wind and solar generation can be treated as negative load._w w wa f ha dev G G G =+ (6) 3 Please note that the hour-ahead schedule can be implemented differently in the different markets.where w a G is the actual wind power, _w f ha G is hour-ahead wind power forecast, and wdevG is the deviation from the forecast.Therefore, similarly to the situation without wind, the balancing power can be expressed as follows: __w s f ha f ha G L G =- (7)__()()w s w w dev a a a f ha a f ha L L G G L L G G =--=--- (8)Fig. 1 shows the imbalance power in the WECC model for August 2030. The balancing power needed in the system is opposite to the imbalance. It is assumed that the peak load in 2030 will have grown to 205 GW, and the installed wind capacity will be 88GW (up from about 7 GW in 2008 [18]). The highly fluctuating imbalance signal is attributable to the highvariability of wind power. It also represents the gap between the scheduled generation and actual load. By utilizing energy storage, the imbalance can be reduced by charging the energy storage whenever there is over-generation (imbalance signal is above zero) and discharging the storage during periods of under-generation (imbalance signal is negative). Periodic zero total energy components of the imbalance signal in Fig. 1 correspond to the maximumcharging/discharging job that can be allocated to theenergy storage.time in hoursI m b a l a n c e p o w e r (G W )Fig. 1. Imbalance power imposed by load and wind variability for assumed 88 GW of installed wind capacity (WECC model for Aug.2030).B. DFT Analysis Different energy storage technologies are best suited for operation over different time periods. Theimbalance power, shown in Fig. 1, can be broken down into the components spanning differentfrequency ranges. This decomposition can be achieved by using DFT. Each component of the periodic signal, except for the zero frequency component, representscycling energy that averages to zero over each cycle.Generally, in a discrete form, the DFT analysis and synthesis equations are written as follows [19]:Analysis equation (fast Fourier transform)1[][]N tfNt X f x t W -==∑0,,1f N =- (9) Synthesis equation (inverse Fourier transform) []101[]N tf N f x t X f W --==∑0,,1t N =- (10)where N is the number of the data points in the sequence (x [0], x [1], , x [N -1]), and()2j tf tfN W e π-=.The basic approach to decompose the imbalance signal using DFT consists of five steps, as shown in Table 1.Four different frequency ranges are selected, and thesignal is decomposed into four categories: slowcycling, intra-day, intra-hour and real-timecomponents. The band-pass filter applied to thespectrum is a rectangular window with unit magnitude within the band and zero magnitude outside of the band, as illustrated in Fig. 2 and Table 2. It is symmetric around one half of the sampling frequency. Table 1: Procedures of applying DFT for cycling analysis Steps Description1 Assume that the data sampling x (t ) issampled each minute (or 0.0167 Hz). Thedata window selected for DFT analysis is 2days (2880 samples), which starts at 0:00 and ends at 48:00.2 The data points are increased to 5760 samplewith zero padding.3 The spectrum, X (f ), is obtained by DFT. Aband-pass filter (see Fig. 2) is applied to the spectrum, X (f ).4 The filtered spectrum is converted back tothe time-domain signal, x´(t ), by using inverse DFT.5 The time-domain signal x´(t ) is characterizedby the magnitude and periodicity.frequencies are f l and f u, and the filter is symmetrical about the half ofthe sampling frequency, f s /2)Table 2: Specifications of frequency bands of the balancing signalcomponentsComponent f l (Hz) f u (Hz) Slow cycling 0 2.315e-5Intra-day 2.315e-5 9.259e-5 Intra-hour 9.259e-5 0.00333Real-time 0.00333 0.00833The frequency ranges given in Table 2 have no astrict definition and they are loosely connected to the dispatch intervals. The reason is that a dispatchinterval can contain half cycle, the entire cycle, twocycles, and so on depending on researchers’ judgment. Currently they are set for periods of 3-12 hours (intra-day), 5 minutes –3 hours (intra-hour), and 2–5 minutes (real time).C. Simulation Results The DFT method described in Section II was applied to a simulated WECC system imbalance powermodel reflecting a future high wind penetrationscenario for 2030. Several simplifying assumptionswere made to determine the balancing requirementscurve. The balancing requirement was derived from the uncertainty in the load and wind forecasting. The scenario assumed 88 GW of wind capacity in the WECC system. Furthermore, it was assumed aconsolidation of all WECC balancing areas into onesingle balancing area. This model was derived in a previous PNNL project analyzing the energy storagepotential applications in the WECC system [18]. D. Decomposition of Balancing Power for a Particular DayFig. 3 shows the one-day imbalance power signal (top) and the corresponding spectrum (bottom). Most of the energy is concentrated in the low and middle frequency bands.G WBy applying the filters shown in Fig. 2 and Table 2, in Fig. 4 the imbalance power, x (t ), is decomposed into four components, namely, into slow cycling, intra-day, intra-hour, and real time components, x 1(t ), x 2(t ), x 3(t ) and x 4(t ). By summation of these components, we can reconstruct the original time-domain signal. Thereconstructed imbalance power matches well with the original signal, as shown in Fig. 5.The frequency and magnitude of the decomposed signal play an important role in determining the required energy storage characteristics as well as technologies appropriate for each application.HoursM W(a) Slow cycling component x 1(t )HoursM W(b) Intra-day component x 2(t)HoursM W(c) Intra-hour component x 3(t)HoursM W(d) Real-time component x 4(t )Fig. 4. Decomposition of imbalance signal for a day in August 2030HoursG W-12HoursM WFig. 5. Comparison between original signal and reconstructed signal.The frequency of cycling increases for intra-hour and real time components. This means that the energy capacity requirements are decreasing, while the cycling requirements are increasing. The cycling requirement has implication for the life time of the energy storage.The energy storage power capacity requirement is associated with the magnitude of the cycles. On this particular day, the imbalance power swings between 10.7 GW and -4.1 GW, while intra-hour component swings between 6.1 GW and -4.8 GW, and real-time component swings between 154 MW and -153 MW 4. Therefore, the intra-day balancing process requires more ES power capacity than the intra-hour process by 43. The same fact has also been observed for other days as described below.E. Sizing of Energy StorageTo determine the size of energy storage for slow-cycling, intra-day, and intra-hour balancing processes, the method described in Section II was applied. We assumed a depth of discharge for the ES of 80%. Table 3 shows both the power and energy capacities for the energy storage.In the full balance scenario (second column), the energy storage compensates for all the imbalance power. In the partial balance scenario (third column), the energy storage compensates for only intra-hour and real-time components. In the fourth column, the reduction in ES requirements between the full balance and partial balance is shown.4Despite the asymmetric power capacity requirement, the energy requirement remains symmetric (the positive and negative energy are equal), which is important for the energy storage applications.Table 3: Comparison of the full balance and partial balancescenariosEnergy storage size Full balance Partial balance Reduction inES requirements Power 13.4 GW 7.7 GW 42.6% Energy68.1 GWh4.3 GWh 93.6%A very significant ES energy capacity (68.1 GWh) would be required in the full balance scenario. The state of charge of ES in this scenario is shown in Fig. 6. The size of the energy storage can be reduced to 3.8 GWh for the intra-hour component and to 568 MWhfor the real-time component as shown in Fig. 7.daysG W hFig. 6. State of charge profile for energy storage in Aug 2030(storage size=68.05 GWh)daysG W h(a) Intra-hour component (storage size=3.8 GWh)daysM W h(b) Real-time component (storage size=568 MWh)Fig. 7. State of charge profile for intra-hour and real-timecomponents in August 2030III. C ONCLUSIONSThis paper presents a novel methodology of characterizing maximum energy storage requirements for a balancing area or their interconnection. The approach is particularly useful for the system planning community as well as for the energy storage providers.The introduction of a cycling taxonomy (slow-cycle, intra-day, intra-hour, intra-minute and real-time) offers a new way to characterize the key features of energy[1] J. C. Smith, M. R. Milligan, E. A. DeMeo, B. Parsons, "Utilitywind integration and operating impact state of the art," IEEE Transactions on Power Systems ,vol.22, no.3, pp. 900 - 908, August 2007.[2] Y.V. Makarov, C Loutan, Jian Ma, P de Mello, "Operationalimpacts of wind generation on California power systems," IEEE Transactions on Power Systems , vol. 24, no. 2, pp.1039 – 1050, May 2009.[3] A. Ter-Gazarian, “Energy storage for power systems,” ISBN-10: 0863412645, The Institution of Engineering and Technology, September 1994.[4] Eyer J. and G Corey, “Energy storage for the electricity grid:benefits and market potential assessment guide,” Sandia report SAND 2010–0815, Sandia, New Mexico, 2010.[5] J. N. Baker and A. Collinson, “Electrical energy storage at theturn of themillennium,” Inst. Elect. Eng. Power Eng. J., vol. 13, no. 3, pp. 107–112, June 1999.[6] J.P. Barton and D.G. Infield, "Energy storage and its use withintermittent renewable energy," IEEE Transactions on Energy Conversion , vol. 19, no. 2, pp. 441- 448, June 2004.[7] Y.V. Makarov, "Relative regulation capacity value of theflywheel energy storage resource," November 26, 2005. [8] Ancillary Services Manual, NYISO, September 2010.[9] M.G. Hoffmann, A. Sadovsky, M. C. Kintner-Meyer, J.G.DeSteese, "Analysis tools for sizing and placement of energy storage in grid applications: a literature review,” Pacific Northwest National Laboratory, July 2010.[10] C. Abbey, G. Joos, "A stochastic optimization approach torating of energy storage systems in wind-diesel isolated grids," IEEE Transactions on Power Systems , vol. 24, no. 1, pp. 418-426, 2009.[11] A. Oudalov, D. Chartouni, C. Ohler, "Optimizing a batteryenergy storage system for primary frequency control," IEEE Transactions on Power Systems , vol. 22, no. 3, pp. 1259-1266, 2007.[12] C.H. Lo, M.D. Anderson, "Economic dispatch and optimalsizing of battery energy storage systems in utility load-leveling operations," IEEE Transactions on Energy Conversion , vol. 14, no. 3, pp. 824 - 829, 1999.[13] S. Chakraborty, T. Senjyu, H. Toyama, A.Y. Saber, T.Funabashi, "Determination methodology for optimising the energy storage size for power system," IET Generation, Transmission & Distribution , vol. 3, no. 11, pp. 987-999, 2009.[14] P. Pinson, G. Papaefthymiou, B.Klockl, J.Verboomen,"Dynamic sizing of energy storage for hedging wind power forecast uncertainty," IEEE Power & Energy Society General Meeting 2009, pp. 1-8.[15] Y. M. Atwa, E. F. El-Saadany, “Optimal allocation of ESS indistribution systems with a high penetration of wind energy,” IEEE Transactions on Power Systems , vol. 1, no. 99, pp. 1-8, 2010.[16] X.Y. Wang, D. Mahinda Vilathgamuwa, S.S. Choi,"Determination of battery storage capacity in energy buffer for wind farm," IEEE Transactions on Energy Conversion , vol. 23, no. 3, pp. 868-878, 2008.[17] C. Abbey and G. Joos, "Supercapacitor energy storage forwind energy applications," IEEE Transactions on Industry Applications, vol. 43, no. 3, pp. 769-776, May-June 2007. [18]M. C. W. Kintner-Meyer, P. J. Balducci, C. Jin, TB. Nguyen,MA. Elizondo, VV. Viswanathan, X. Guo, and FK. Tuffner,“Energy storage for power systems applications: a regional assessment for the northwest power pool (NWPP),” Pacific Northwest National Laboratory, Richland, WA, 2010.[19]Alan V. Oppenheim, Ronald W. SchaferJohn, R. Buck,Discrete-Time Signal Processing, Prentice Hall, 1999 (p543) Yuri V. Makarov (SM’99)received the M.Sc. degree in computers and the Ph.D. degree in electrical engineering from the Leningrad Polytechnic Institute (now St. Petersburg State Technical University), Leningrad, Russia. From 1990 to 1997, he was an Associate Professor in the Department of Electrical Power Systems and Networks at St. Petersburg State Technical University. From 1993 to 1998, he conducted research at the University of Newcastle, University of Sydney, Australia, and Howard University, Washington, DC. From 1998 to 2000, he worked at the Transmission Planning Department, Southern Company Services, Inc., Birmingham, AL, as a Senior Engineer. From 2001 to 2005, he occupied a senior engineering position at the California Independent System Operator, Folsom, CA. Now he works for the Pacific Northwest National Laboratory (PNNL), Richland, WA. His activities are around various theoretical and applied aspects of power system analysis, planning, and control. He participated in many projects concerning power system transmission planning (power flow, stability, reliability, optimization, etc.) and operations (control performance criteria, quality, regulation, impacts of intermittent resources, etc.). Dr. Makarov was a member of the California Energy Commission Methods Group developing the Renewable Portfolio Standard for California; a member of the Advisory Committee for the EPRI/CEC project developing short-term and long-term wind generation forecasting algorithms; and a voting member of the NERC Resources Subcommittees and NERC Wind Generation Task Force. For his role in the NERC August 14th Blackout Investigation Team, he received a Certificate of Recognition signed by the U.S. Secretary of Energy and the Minister of Natural Resources, Canada.Michael Kintner-Meyer is a Staff Scientist with the Pacific Northwest National Laboratory (PNNL) in Richland. He has a Master Degree in Mechanical Engineering from the Technical University of Aachen, Germany and a Ph.D. in Mechanical Engineering from the University of Washington. He is leading the energy storage analysis efforts at PNNL.Pengwei Du received the B.Sc. and M.Sc. degrees in electrical engineering from Southeast University, Nanjing, China, in 1997 and 2000, respectively, and his Ph.D. degree in electrical engineering from Rensselaer Polytechnic Institute, Troy, NY in 2006. He is now a research engineer at the Pacific Northwest National Laboratory, Richland, WA. His research interests include Distributed Generation, power system modeling and analysis, and digital signal processing.Chunlian Jin (M’06) received her B.S.E.E. from Northwestern Polytechnic University, Xi’an, China, in 2000, and her M.S.E.E. from Tsinghua University, Beijing, China, in 2003. Her research interests include energy storage analysis, modeling and assessment of power system operations and control performance, and integration of renewable resources. Currently, she is a research engineer with the Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA. She finished PhD courses in University of South Carolina. Howard F. Illian graduated from Carnegie Institute of Technology (Carnegie-Mellon University) in 1970 with a B.S. in Electrical Engineering. From 1970 until 1982 he worked for ComEd in the field of Operations Research, and was Supervisor, Economic Research and Load Forecasting from 1976 until he was reassigned to Bulk Power Operations in 1982 where he was Technical Services Director when he retired in 1998. He is now President of Energy Mark, Inc., a consulting firm specializing in the commercial relationships required by restructuring. He has authored numerous papers in the field of Engineering Economics, and has testified as an expert witness in this field before the Illinois EPA, the Federal EPA, the Illinois Commerce Commission and the Public Utility Commission of Texas. He has developed and applied several new mathematical techniques for use in simulation and decision making. He has served on the NERC Performance Subcommittee, the Interconnected Operations Services Implementation Task Force, the Joint Inadvertent Interchange Task Force, and the NAESB Inadvertent Interchange Payback Task Force. Recent work includes significant contributions to the development of new NERC Control Performance Standards including the Balancing Authority Ace Limit and a suggested mathematical foundation for control based on classical statistics. He first applied discrete Fourier transforms to load analysis in 1991. His current research concentrates on the development of technical definitions for Ancillary or Reliability Services including frequency response and their market implementation.。
EV车辆能量存储系统的现状和未来 Current_Status_and_Future_of_Energy_Storage_System_for_EV

No.5 South Zhongguancun Street, Haidian district, Beijing, P.R. China Tel: +86-10-68911524 ext 8013
LiCoO2 LiMnO2 LiFePO4 Li3 V2(PO4)3
130-140 100-120 ~140 >174.0
bad
general
3.4
best
best
~4.0
best
best
Safety
bad better better better
price
high low low lowest
2 Definition of Traction Battery
Traction battery is the key component of ESS, and it is a kind of energy storage system to drive motor by means of transforming chemical energy to mechanical energy with start current more than two times of that at normal working condition.
5.1.2 Ni-Cd Battery
The France is the largest consumer of Ni-Cd batteries for EVs. However, the Ni-Cd battery is fading out the market because of its bad environmental performance due to the use of Cd element.
基于低压配电台区运行特性的储能控制策略

DOI: 10.12677/sg.2020.103013
文章引用: 易斌, 梁崇淦, 赵伟, 赵赫. 基于低压配电台区运行特性的储能控制策略[J]. 智能电网, 2020, 10(3): 121-130. DOI: 10.12677/sg.2020.103013
易斌 等
收稿日期:2020年6月6日;录用日期:2020年6月21日;发布日期:2020年6月28日
Open Access
1. 引言
配电网是国民经济和社会发展的重要公共基础设施,随着以“智能电网”和“泛在电力物联网”为 基础的“三型两网”战略目标的提出,利用智能设备保障配电网供电质量的重要性日益凸显。在低压配 电网中,配电台区供电电能质量和供电可靠性直接影响着居民正常生产、生活。实际上,《电力发展“十 三五”规划(2016~2020 年)》也早已明确提出要升级改造配电网,推进智能电网建设,满足用电需求,提 高供电质量,并着力解决配电网薄弱问题。
2. 考虑配电台区运行特性的储能系统应用
配电网是电网各领域中直接关联用户的重要环节,具有覆盖面积广、运行工况复杂的特点,配电台 区作为其重要设备,是连接电网和用户的重要枢纽,考虑低压配电台区运行特性,对解决配电网供电质 量问题具有重要意义。
实际上,配电网台区变压器运行面临众多问题,主要有:1) 台变已面临重载或处于重载运行中(部分 用户负荷已采取错峰用电措施,否则台变重过载,影响电网运行安全);2) 生产用电负荷启停对台区有较 强冲击性,会造成低电压投诉;3) 台区馈线实际三相电压不平衡超过基准值,引起电能质量问题;4) 台 区计划新增台变进行负荷拆分,但投资受限。具体公用台变日负荷曲线如图 1 所示。
超低温-高温跨温区相变材料制备及物性调控综述

第 12 卷第 12 期2023 年 12 月Vol.12 No.12Dec. 2023储能科学与技术Energy Storage Science and Technology超低温-高温跨温区相变材料制备及物性调控综述折晓会1, 2,王星宇1,郭晓龙1,刘艺炫3,王家蕴1,韩鹏1, 2,任晓芬1, 2,赵学敏1, 2(1石家庄铁道大学机械工程学院,低温能量转换、存储与输运研究中心,河北石家庄050043;2河北省储能产业技术研究院,河北石家庄050000;3河北工程大学能源与环境工程学院,河北邯郸056038)摘 要:相变储能技术利用相变材料在相变过程中释放或吸收潜热的特性,将能量以潜热的形式储存或释放。
其具有高能量密度、长寿命、高功率的优势,在电动汽车、可再生能源储存、电网调峰、智能电网方面具有广泛应用前景,为能源转型和高效能源利用提供了一种可行的解决方案。
本文通过对相关文献的探讨,综述了不同温区相变材料的优缺点以及应用领域,包括超低温区(-190~-50 ℃)、低温区(-50~0 ℃)、普温区(0~100 ℃)和高温区(100~700 ℃)。
针对相变材料性能改善,阐述了导热系数提升、过冷度降低、相变温度调控、循环稳定性提高等方法。
此外,对于复合相变材料的制备方法,介绍了微胶囊化、浸渍法、溶胶-凝胶法和超声波法,并对后三者的不足进行阐述和说明。
最后,对于相变材料的未来应用进行了展望,为相变储能技术在能源储存领域的进一步研究提供了参考和指导。
关键词:相变材料;相变储能;物性调控;制备方法doi: 10.19799/ki.2095-4239.2023.0726中图分类号:TB 333 文献标志码:A 文章编号:2095-4239(2023)12-3818-18A review on the preparation of ultra-low-temperature,high-temperature, and cross-temperature zone phase change materials and the regulation of physical properties SHE Xiaohui1, 2, WANG Xingyu1, GUO Xiaolong1, LIU Yixuan3, WANG Jiayun1, Han Peng1, 2,REN Xiaofen1, 2, ZHAO Xuemin1, 2(1Low Temperature Energy Conversion, Storage and Transportation Research Center, School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China; 2Hebei Energy Storage Industry and Technology Research Institute, Shijiazhuang 050000, Hebei, China; 3School of Energy and Environmental Engineering, Hebei University of Engineering, Handan 056038, Hebei, China)Abstract:Phase change energy storage technology harnesses the unique properties of phase change materials to release or absorb latent heat during phase transitions, enabling energy storage in the form of latent heat. This technology holds promising applications in electric vehicles, renewable energy storage, grid peaking, and smart grids owing to its high energy density, extended lifespan, and high power. It presents a viable solution for energy收稿日期:2023-10-17;修改稿日期:2023-10-31。
二维MoS2薄膜的可控制备及其电子输运特性研究

二维MoS2薄膜的可控制备及其电子输运特性研究【摘要】二维MoS2作为一种新型半导体材料,在电子学和光电子学领域具有广泛的应用前景。
在本文研究中,我们采用化学气相沉积(CVD)技术在氧化硅基底上制备了高质量的二维MoS2薄膜,并通过压电传感器进行了表征。
通过在不同条件下控制CVD过程中的温度、气体流量和反应时间等参数,成功地实现了对MoS2薄膜的可控制备。
同时,利用离子束雕刻技术对MoS2薄膜进行了纳米加工,使其形成了具有排列有序的长条纹的结构,可作为电极进行电子输运特性研究。
进一步的电子输运实验表明,MoS2薄膜具有半导体特性,并在室温下呈现出n型导电性。
在不同温度和电场的情况下,MoS2薄膜的电子输运性质表现出明显的变化。
通过调控材料的缺陷和掺杂,成功地实现了对MoS2薄膜电子输运特性的调控。
结果表明,MoS2薄膜在电子学和光电子学器件中具有广泛的应用前途。
【关键词】二维MoS2;CVD;可控制备;纳米加工;电子输运特性【Abstract】Two-dimensional (2D) MoS2 as a novel semiconductor material has great potential applications in thefields of electronics and optoelectronics. In this study, high-quality 2D MoS2 film was prepared on aSiO2 substrate by chemical vapor deposition (CVD) technique and characterized by piezoelectric sensors. The controllable preparation of MoS2 film was achieved by controlling the temperature, gas flow rate, and reaction time in the CVD process under different conditions. Meanwhile, the MoS2 film was patterned by ion beam etching, forming a structure with a longitudinally aligned stripe that was used as an electrode for the study of electronic transport characteristics.Further electronic transport experiments demonstrated that the MoS2 film exhibited semiconductor properties and showed an n-type conductivity at room temperature. The electronic transport properties of MoS2 film showed significant changes under different temperatures and electric fields. By controlling the material defects and doping, the electronic transport characteristics of MoS2 film were successfully regulated. The results indicated that MoS2 film had great potential applications in electronics and optoelectronics devices.【Keywords】Two-dimensional MoS2; CVD; Controllable preparation; Nanofabrication; Electronic transport characteristicTwo-dimensional MoS2 has attracted increasingattention in recent years due to its unique properties and potential applications in electronics and optoelectronics devices. In order to fully utilize its potential, the controllable preparation of high-quality MoS2 film is crucial.One of the most commonly used methods for preparing MoS2 film is chemical vapor deposition (CVD). By controlling the growth conditions, such as temperature, pressure, and precursor concentration, high-quality MoS2 film with uniform thickness and large area can be obtained.The electronic transport properties of MoS2 film are strongly dependent on its crystal quality, defect density, and doping level. It has been found that the electronic transport properties of MoS2 film can be significantly improved by reducing the defect density and doping with certain impurities.Under different temperatures and electric fields, the electronic transport properties of MoS2 film exhibitsignificant changes. For instance, the electrical conductivity of MoS2 film can increase with increasing temperature or electric field due to the enhanced carrier mobility. Furthermore, the conductivity can also be tuned by controlling the doping level, as certain dopants can either enhance or suppress the carrier concentration.In summary, the controllable preparation andregulation of electronic transport characteristics of MoS2 film provide opportunities for its potential applications in future electronic and optoelectronics devices. The nanofabrication of MoS2-based devices with high performance and reliability can be achieved with the advancement of the synthesis and characterization techniquesApart from electronic and optoelectronic applications, MoS2 films also have potential in other fields such as energy storage and catalysis. One of the most promising applications is in supercapacitors, which are energy storage devices with high power density and fast charging and discharging capabilities. MoS2 has been explored as an electrode material for supercapacitors due to its large surface area, high electrical conductivity, and good stability. Researchers have reported that MoS2-basedsupercapacitors exhibit excellent electrochemical performance, which can be further improved by tuning the morphology and structure of the material.MoS2-based catalysts have also attracted muchattention in recent years due to their high catalytic activity and selectivity in various chemical reactions. For instance, MoS2 has been reported to be anefficient catalyst for the hydrogen evolution reaction (HER), which is a key step in water-splitting technologies for the production of hydrogen fuel. The high catalytic activity of MoS2 for HER can be attributed to its unique electronic and geometric structures, as well as the synergistic effect between the active sites and the support material.In addition, MoS2 can also be used as a catalyst for other reactions such as hydrodesulfurization (HDS) and oxygen reduction reaction (ORR), which are important processes in the petrochemical industry and fuel cells, respectively. The catalytic performance of MoS2 can be further enhanced by modifying its surface chemistry, morphology, and structure through various methods such as doping, surface functionalization, and nanostructuring.Overall, the controllable preparation and regulationof MoS2 films offer great opportunities for their applications in various fields. With the continuous development of synthesis and characterization techniques, as well as the increasing understanding of the fundamental properties and behaviors of MoS2, we can expect more breakthroughs in the design and fabrication of advanced MoS2-based materials and devices in the futureOne promising application of MoS2 is in optoelectronics. Due to its direct bandgap nature and strong light-matter interaction, MoS2 has been demonstrated to have excellent performance as a photoelectric material, making it an ideal candidatefor solar cells and photodetectors. Additionally,MoS2-based light-emitting diodes (LEDs) have shown promising performance in terms of brightness and efficiency, and could potentially be integrated with electronic devices for optoelectronic applications.Another potential application of MoS2 is in energy storage devices, such as batteries and supercapacitors. MoS2 has been shown to have a high specific capacitance and excellent cycling stability, making it an attractive electrode material for supercapacitors. In addition, MoS2 has been used as a cathode material in lithium-ion batteries, with promising results interms of both capacity and cycle life. Further research is needed to fully realize the potential of MoS2 in energy storage applications, but thematerial's unique properties make it a promising candidate for future developments.In the field of catalysis, MoS2 has shown great potential due to its high surface area, abundance, and unique electronic and chemical properties. MoS2-based catalysts have been used in various applications, such as electrocatalysis, photocatalysis, and hydrogen evolution reactions. Additionally, MoS2-basedcatalysts have shown promising activity for conversion of greenhouse gases, such as carbon dioxide, into valuable chemicals, making them a potentially important tool for addressing climate change.Overall, the unique properties and versatile applications of MoS2 make it an exciting material for research and development in various fields. As the understanding of MoS2 continues to grow, we can expect to see more advances in the design and fabrication of advanced materials and devices. The development of new synthesis and characterization techniques will also play a critical role in unlocking the full potential of MoS2-based materials. Ultimately, these advancements have the potential to revolutionize anumber of industries and make a significant impact on our daily livesIn conclusion, MoS2 is a promising material that has garnered significant attention due to its unique properties and potential applications in various fields. The research and development in this area are expected to lead to significant advancements in the design and fabrication of advanced materials and devices, which could revolutionize numerous industries and make a significant impact on our daily lives. Continued efforts in the development of new synthesis and characterization techniques are critical to unlocking the full potential of MoS2-based materials。
考虑多维性能衰减的储能电池系统运行可靠性评估方法

第51卷第19期电力系统保护与控制Vol.51 No.19 2023年10月1日Power System Protection and Control Oct. 1, 2023 DOI: 10.19783/ki.pspc.230308考虑多维性能衰减的储能电池系统运行可靠性评估方法王辉东1,王博石2,张 盛1,余 娟2,姚海燕3,邢海青1,郭 强3(1.国网浙江省电力有限公司杭州市余杭区供电公司,浙江 杭州 311121;2.输配电装备及系统安全与新技术国家重点实验室(重庆大学),重庆 400044;3.杭州电力设备制造有限公司余杭群力成套电气制造分公司,浙江 杭州 310016)摘要:储能电池系统的发展是推进“双碳”目标的关键所在,伴随而来的却是储能电站的安全隐患,亟需对储能电池系统的可靠性进行准确评估。
为此,提出考虑多维性能衰减的储能电池运行可靠性评估方法。
首先,提出了基于高斯过程的储能电池性能衰减过程电压特征量分布计算方法,计算充放电循环过程中电压特征量的概率分布,为刻画电池性能衰减提供了重要维度。
然后,提出了基于多维通用生成函数的储能电池系统运行可靠性评估方法,通过电压特征量和容量的概率分布计算储能电池单体的可靠性。
进而定义可考虑储能电池拓扑连接情况的串并联关系函数,计算储能电池系统整体的可靠性。
最后,基于NASA储能电池数据的算例仿真表明所提方法能够实现储能电池系统可靠性的精准评估。
关键词:储能电池;性能衰减;可靠性评估;通用生成函数;高斯过程Operational reliability evaluation method for an energy storage battery system consideringmulti-dimensional performance degradationWANG Huidong1, WANG Boshi2, ZHANG Sheng1, YU Juan2, YAO Haiyan3, XING Haiqing1, GUO Qiang3(1. State Grid Zhejiang Electric Power Co., Ltd. Hangzhou Y uhang District Power Supply Company, Hangzhou 311121, China;2. State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University),Chongqing 400044, China; 3. Hangzhou Electric Power Equipment Manufacturing Co., Ltd. Yuhang QunliComplete Electric Manufacturing Branch, Hangzhou 310016, China)Abstract: The development of energy storage battery systems is key to advancing the "dual carbon" goal, but with it come the potential safety hazards of energy storage power stations. Therefore, it is urgent to accurately evaluate the reliability of energy storage battery systems. This paper proposes a method for evaluating the operational reliability of energy storage batteries considering multidimensional performance degradation. First, a Gaussian process-based method for calculating the distribution of voltage characteristics during the performance degradation process of energy storage batteries is proposed. This calculates the probability distribution of voltage characteristics during the charging and discharging cycle, providing an important dimension for characterizing performance degradation. Then, a multidimensional general generation function-based operational reliability evaluation method for energy storage battery systems is proposed. The reliability of individual batteries is calculated through the probability distribution of voltage characteristics and capacity. Then a series parallel relationship function that can consider the topological connection of energy storage batteries is defined to calculate the overall reliability of the battery system. Finally, a numerical simulation based on NASA energy storage battery data shows that the proposed method can achieve accurate reliability evaluation of such battery systems.This work is supported by the National Key Research and Development Program of China (No. 2021YFE0191000).Key words: energy storage battery; performance degradation; reliability evaluation; general generating function;Gaussian process0 引言储能系统是实现电力用能变革的关键,主要体基金项目:国家重点研发计划项目资助(2021YFE0191000) 现在快速调频、平滑新能源出力波动、提高系统稳定性和可靠性等方面[1]。
储能辅助电网参与调频的控制策略研究

第41卷第2期Vol.41㊀No.2重庆工商大学学报(自然科学版)J Chongqing Technol &Business Univ(Nat Sci Ed)2024年4月Apr.2024储能辅助电网参与调频的控制策略研究黄㊀荣,郭家虎安徽理工大学电气与信息工程学院,安徽淮南232001摘㊀要:目的研究储能电站在风光发电情况下保持电力系统稳态的调节原理与方法,并在此基础上设计了一种虚拟同步发电机三级模型用有源支持控制方式辅助火电机组维持电网频率稳定的主动支撑控制策略㊂方法利用储能电池快速响应的特性,建立储能系统,对储能换流器的控制进行改进,在传统的控制架构的基础上改进为在电压中加入虚拟阻抗的外环调节器和基于准PR 控制器的电流内环控制,深入分析控制策略的原理和同步发电机的对应关系㊂结果随着新能源渗透率越来越高,在储能电站并网参与频率调节的情况下,频率波动的次数变少㊂结论控制方法可以给新能源发电系统带来一定的惯性和阻尼,从而增强了系统的稳定性,并且证明了储能电站参与电网调频的必要性和可实施性,为储能电站的分布和储能电池的容量配置提供了一定的实际的参考意义㊂关键词:主动支撑;虚拟同步发电机;储能系统;储能换流器中图分类号:TM743㊀㊀文献标识码:A ㊀㊀doi:10.16055/j.issn.1672-058X.2024.0002.002㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀㊀收稿日期:2022-11-07㊀修回日期:2023-03-15㊀文章编号:1672-058X(2024)02-0009-09基金项目:电力传输与功率变换控制教育部重点实验室开放课题资助(2020AC01).作者简介:黄荣(1997 ),男,安徽宿州人,硕士研究生,从事储能研究.引用格式:黄荣,郭家虎.储能辅助电网参与调频的控制策略研究[J].重庆工商大学学报(自然科学版),2024,41(2):9 17.HUANG Rong GUO Jiahu.Research on the control strategy of energy storage system assisting grid in regulating frequency J .Journal of Chongqing Technology and Business University Natural Science Edition 2024 41 2 9 17.Research on the Control Strategy of Energy Storage System Assisting Grid in Regulating Frequency HUANG Rong GUO JiahuSchool of Electrical and Information Engineering Anhui University of Science &Technology Anhui Huainan 232001 ChinaAbstract Objective The regulation principles and methods of energy storage power plants to maintain the steady state of the power system in the case of wind and solar power generation were investigated and on this basis an active support control strategy of virtual synchronous generator three-level model assisting thermal power units to maintain the frequency stability of the grid with active support control was designed.Methods Using the characteristics of the fast response of energy storage batteries an energy storage system was established to improve the control of the energy storage converter.The conventional control architecture was improved by adding an outer-loop regulator with virtual impedance in the voltage and introducing a current inner-loop control based on a quasi-PR controller.The principle of the control strategy and the correspondence of the synchronous generator were analyzed in depth.Results With the increasing penetration of new energy into the grid the number of frequency fluctuations becomes less when energy storage power stations are connected to the grid to participate in frequency regulation.Conclusion This control method can bring a certain amount of inertia and damping to the new energy power generation system thereby enhancing the stability of the system.It also provides the necessity and feasibility of energy storage stations participating in grid frequency modulation and provides a certain practical reference significance for the distribution of energy storage stations and the capacity allocation of energy storage batteries.Keywords active support virtual synchronous generator energy storage system energy storage converter1㊀引㊀言最近几年,随着全球经济的快速发展,与之相伴的全球气候变暖㊁传统能源匮乏等问题也愈演愈烈[1-2],在此背景需求下,风能㊁光能等可再生能源受到了广泛重庆工商大学学报(自然科学版)第41卷的关注,为降低环境污染等问题带来的影响,传统的发电机组逐渐被新能源所代替,由于其具有波动性等特点,虽然缓解了传统能源稀缺等问题,但也对电网的稳定运行带来了挑战㊂由于新能源渗透率越来越高,而新能源无法直接并网,需要通过电力电子设备才能间接并网,但是设备不具备惯量等特性,从而为电网的稳定运行带来了挑战㊂储能系统应运而生,又因为传统机组其本身的内在的缺点,比如响应速度慢,输出精度低,设备容易磨损等,会降低其调频效果,而能量存储系统自身的特点是:响应速度快㊁跟踪精度高㊁能够实现能量的双向控制,所以在储能系统的辅助下火电机组参与调频的控制方法得到了广泛的应用[5-6]㊂储能系统是储能电池接入电网的关键设备,对于储能电池的控制策略并不是直接对电池进行控制,而是间接对储能电池并网所用到的电力电子设备进行控制,其控制方式主要有下垂控制(DROOP控制)和虚拟同步发电机(Virtual Synchronous Generator,VSG)控制等㊂其中VSG控制以模拟同步发电机的外部特征为主,将传统发电机的机械和电气的控制结构嵌入并网逆变器的控制算法中,改善储能换流器(Power Conversion System,PCS)的外特性[7-8]㊂文献[9]提出了以同步机三阶模型为基础的主动支撑控制策略,从而增强了储能变流器并网时暂态电压的稳定性,但是所提出的模型较为复杂,模拟的速度较为缓慢㊂文献[10]在VSG的基础上进行改进,利用VSG技术集成了储能系统自身的制约以及调频时虚拟惯量的变异特征,对控制参数进行了最优设计,并给出了最优的控制方法㊂但是对于储能系统只考虑了一台,与实际情况有一定偏差㊂文献[11]将二阶同步发电机的本体模型引入VSG控制模型中,并设计了VSG 的有功-频率㊁无功-电压功控制器,获得了能够实现一次调频调压,并具有同步发电机惯性的结果和VSG的阻尼算法,对于储能系统的多机并联没有考虑进去,与实际情况有一定的偏差㊂文献[12]利用Runge-Kutta 算法对VSG的瞬态稳定性进行了分析,提出从限制截断角度和其时间两方面进行优化,但计算比较繁琐㊂文献[13]对VSG技术在微电网中的应用进行研究,完成了VSG的机械方程㊁电磁暂态方程以及初级频率调压方程,并基于模型对VSG算法搭建了控制架构框图㊂文献[17]中的逆变器在并网的控制策略的基础上加入了模型预测,提高了电流的跟踪精度,使得弱电网实现平滑并网,但缺乏对于逆变器本身控制策略的改进㊂在上述理论的基础之上,根据同步发电机的数学模型,通过模拟其励磁控制原理及结构,并且与储能系统的VSG二阶模型相结合,建立起具有暂态电压调节过程的VSG的三阶模型,在VSG三阶模型的基础上,提出了一种以VSG三阶模型为基础,用于辅助火电机组维持电网频率以及并网电压稳定的主动支撑控制策略,从而使策略不但具备了调频的功能,同时也具有了调压的作用,增加了电力系统的惯量与阻尼特性,提高了系统的稳定性,改善了系统的频谱特征㊂2㊀基础原则2.1㊀同步发电机的工作原理2.1.1㊀有功-频率控制原理同步发电机的有功-频率控制原理主要是指在调速系统的作用下,通过改变进气量或者进水量,使得输出的机械功率和电磁功率相等,进而使得频率逐渐恢复到额定值,从而达到调频的目的[14]㊂同理,当负荷在某一时刻突然减少时,与上述操作相反,使得输入的机械功率减少即可,具体如图1所示㊂图1㊀同步发电机的有功-频率特性曲线Fig.1㊀The active-frequency characteristic curveof the synchronous generator曲线又被称为功率-频率静态特性曲线,由图1可知若发电机初始化运行a点,此时频率是f1,发电机输出的电磁功率为P1,则当负荷突然减少时,电磁功率减少,对应图中的点P2,频率升高为f2点,体现出了同步发电机的垂度调整控制特性,由此可以得同步发电机多用途的功频稳态方程:P0-P r=-K r(ω0-ωr)(1)其中:P0为额定机械功率,P r为发电机的电磁功率,K r 为频率调节系数,ω0为系统的额定角速度,ωr为系统当前的角速度㊂方程体现了当系统角速度或者频率发生变化时系统输出的有功功率也会随之变化㊂2.1.2㊀无功-电压控制原理电压同频率都是衡量电能质量的重要指标,要想维持电压恒定,就需要保证发出的无功功率等于在维持的某个电压消耗的无功功率,此时需要在发电机中加入无功-电压控制环节,也就是所谓的励磁控制器,进而维持端电压的稳定,从而达到调压的目的㊂如图2所示㊂01第2期黄荣,等:储能辅助电网参与调频的控制策略研究图2㊀同步发电机的无功-电压特性曲线Fig.2㊀Reactive -voltage characteristic curve of thesynchronous generator由图2可知,当发电机初始化运行在a 点,此时端电压为U 1,发电机输出的无功功率为Q 1,当系统中的负荷突然减少时,电压会增加至U 2,此时励磁电流减少,此时无功功率减少至Q 2,过程体现出了同步发电机的无功-电压特性,如式(2)所示:Q 0-Q r =-K b (U 0-U r )(2)其中:Q 0为额定无功功率,Q r 为实际的无功功率,K b 为该特性的下垂系数,U 0为发电机的额定电压,U r 为实际工作时的电压㊂2.1.3㊀相关三阶模型从文献[16]中可以得出三阶的同步发电机如下模型:u d =x q i q -r a i du q =E ᶄq -x ᶄd i d -r a iqpT ᶄd 0E q =E f -E ᶄq -(x d -x ᶄd )i d T J d ω/d t =T m -E ᶄq i q -(x ᶄd -x q )i d i q []d δ/d t =ω-1ìîíïïïïïïïï(3)其中:u d 为直轴的定子电压,u q 为交轴的定子电压,x q 为定子交轴绕组的标幺值,p =d /d t 为对时间的导数算子,i d 和i q 为直㊁交轴电流,T ᶄd 0为时间常数,ω为角速度,T m 为机械转矩,T e 为电磁转矩,δ为功角,E ᶄq 和E q 分别为交轴暂态电动势和稳态电动势,x ᶄd 和x d 分别为直轴瞬变电抗和同步电抗,r a 为定子各相绕组的电阻,E f 为定子励磁电动势,T J 为同步发电机组的惯性时间常数㊂2.2㊀VSG 的整体结构由于研究主要是利用VSG 技术对逆变器的控制策略进行优化,所以需要研究储能系统并入电网中的VSG 结构,以及在稳定状态下与同步发电机的等值电路的一一对应关系,具体如图3所示㊂图4通过比较储能系统并网变流器的主电路拓扑结构和稳态下的同步发电机等效回路,可以发现e a ㊁e b ㊁e c 为PCS 的中点电压,模拟同步发电机的电势E q ,r 1为等效电阻,L 1为滤波电感,分别相当于同步发电机的同步电感和定子电阻,u a ㊁u b ㊁u c 为电容电压,相当于同步发电机端电压U g ㊂通过二者的比较,发现了二者之间的相似和对应关系,为后续VSG 三阶模型的建立提供了可能㊂图3㊀稳态下的同步发电机等效回路Fig.3㊀Equivalent loop of synchronous generator in steadystate图4㊀储能系统通过VSG 技术并网结构模型Fig.4㊀Grid-connected structure model of energy storagesystem through VSG technology11重庆工商大学学报(自然科学版)第41卷3㊀主动支撑控制策略的优化设计以VSG三阶模型为基础,结合储能系统保持电力系统的调频㊁调压能力的支撑控制策略,对同步发电机的外部特征进行了严格的模拟,使得储能电站的虚拟调速系统和虚拟励磁系统的时间尺度与同步发电机的调节时间尺度相一致,使得控制策略与传统锁相环的控制策略相比增加了主动性和抗干扰性,主要是因为PCS的功角控制不再依赖于电网的角速度㊂其模型包括虚拟励磁控制器,虚拟调速控制器,VSG三阶模型以及底层控制模型㊂3.1㊀储能电站模型构造在提出储能电站的控制策略之前,首先要对其进行分析,建立相应的模型㊂所谓电站就是首先将a个储能电池串联,形成一个电池模块,再将b个电池模块串联构成一个电池柜,再将m个电池柜并联构成一个存储系统,最终并联n个储能系统便构成一个存储电能的电站,所以对于储能电站的模型构建实际上就是对储能电池模型的构建㊂对于储能电池的选择多种多样,主要以铅酸电池和锂电池为主,由于铅酸电池的寿命较短,体积较大,而锂电池具有效率高,循环寿命长且无污染等特点,使得锂电池更具有发展前景,因此选择锂电池进行研究,阐述储能电池模型构造㊂在进行调频时,储能系统的调频的一般模型不能反映出其内部的调频特征㊂并不适用于调频,为了解决这一问题,国外开始逐步采用戴维南等效电路模型,模型又分为Ⅰ型和Ⅱ型,Ⅰ型虽然解决了上述问题,但是电网调频不能将其输出模式与其状态相关联,也不能应用于电网频率调整,而Ⅱ型在蓄电池中,电流被用来作为一个控制信号,并且考虑了蓄电池中的SOC对开路电压的影响,便可解决Ⅰ型带来的问题,其戴维南等效电路模型Ⅱ型如图5所示㊂图5㊀储能电池戴维南等效电路模型(Ⅱ型) Fig.5㊀Thevenin equivalent circuit model of energystorage battery(typeⅡ)由图5可以看到左侧图形体现出了储能电站的荷电状态SOC随时间的变化,其中C1为可用的剩余容量,R1为自动放电的电阻,U1为目前的荷电状态,反映出了右侧电路上储能电池的电压和荷电状态之间的关系,U2为开路电压,U3就是储能电池的电压,R2为电池自身的电阻,R3为储能电池由于不断的充放电而形成的电阻,而R4,R5,C2和C3分别是电阻电容网络中短时和长时响应支路电阻和响应支路电容㊂综上所述,便可得到储能电池参与调频的等效模型框图,如图6所示㊂Ib13600sC4S O C-Ua b R1m n1/C5a b R5m n+s m n R5C3a b R3m n+s m n R3C2U2U3P图6㊀储能电池调频模型框图Fig.6㊀Block diagram of energy storage battery frequencymodulation model如图6所示,其中C4为储能电池一开始的容量,C5为储能电池的额定容量㊂除了储能电池的荷电状态与其二端电压密切相关外,电池内部的其他参数也与之密切相关,这些参数会影响其二端电压,进而影响储能电池的具体出力情况㊂而要想对这些参数进行细致的了解,就要做一个能量存储单元的充电和放电试验,然后进行相应的数学运算,对参数进行拟合,详见文献[16],储能电池的开路电压与其荷电状态的关系以及其他参数与SOC的关系公式和锂电池模型的相关参数均在文献[16]有了详尽的描述,在此不再赘述㊂综上所述便可以得到辅助电网参与调频的储能电池模型㊂3.2㊀虚拟激励调节器VSG的虚拟激励系统主要是模拟同步机的激励系统,也就是模拟同步发电机无功-电压特性,所谓无功电压特性就是指无功功率与电网输出电压的下垂关系,并且体现了励磁电流与无功功率的关系,其公式如下:(U m-U r)ˑK e1+sTe=Δu(4)21第2期黄荣,等:储能辅助电网参与调频的控制策略研究其中:U m为逆变器输出电压的值,U r为逆变器输出电压的给定值,Δu为励磁电压的变化量,且其与强制空载电动势E qe呈线性关系,因此E qe=K fˑu(5)K f=x a r f(6)其中:K f为下垂系数,x a为直轴绕组电抗,r f为绕组电阻㊂由式(4) 式(6)可得控制器的框图,如图7所示㊂图7所示的控制框图以逆变器的输出口电压的参考值和其测量值的差值作为该控制器启动调压服务的输入信号,减少了无功功率偏差量的输入,实现了直接调压的过程,抑制了储能电站并网点的暂态电压的波动㊂图7㊀虚拟励磁控制器框图Fig.7㊀Block diagram of the virtual excitation controller 3.3㊀虚拟速度调节器VSG的虚拟调控制器主要是对同步发电机的有功-频率特性进行仿真,从而在调频中实现了对功率的分摊,使储能设备具备了辅助火电机组参与电网调频的能力,参照式(1),那么虚拟调速系统模型可以表达为P ref-P b0=K m(ωr-ωm)(7)其中:P ref代替了机械功率,为储能电池输出功率的给定值,P b0代替了电磁功率,为其输出的功率,K m为有功-频率的下垂系数,ωr为角频率的参考值,ωm为电网的角频率实时值,则上述控制框图如图8所示㊂图8㊀虚拟调速控制器框图Fig.8㊀Block diagram of the virtual speed control controller 与此同时在上述控制器框图的基础上加入储能电站的调频死区,并且加入SOC的修正曲线,通过修改功频比例系数,避免能量储存电池的反复充㊁放电,缩短其使用寿命㊂3.4㊀基于VSG的三阶模型由式(3)以及VSG二阶模型,再加入暂态调压过程,进而可以得到基于VSG的三阶模型:2H dΔωd t=P m-P e-DΔωdδd t=ω0ΔωTᶄd0d Eᶄqd t=E qe-Eᶄq-i d(x d-xᶄd)ìîíïïïïïïïï(8)其中:H为虚拟惯量,代替了同步发电机的惯性时间常数T J,D为负荷阻尼常数,Δω为标称旋转速度与真实旋转速度之差,P m为虚拟机械功率,代替同步发电机的机械转矩,P e为虚拟电磁功率,代替同步发电机的电磁转矩,而强制空载电动势E qe代替了同步发电机的定子励磁电动势㊂该三阶模型再结合虚拟调速控制器便得到了VSG 的有功-频率控制框图,如图9所示㊂图9㊀VSG功率—频率调节框图Fig.9㊀Block diagram of VSG power-frequency regulation 3.5㊀VSG的底层控制器对于VSG的底层控制器主要分为两部分,分别是电压和电流环控制㊂3.5.1㊀电压外回路中加入虚拟阻抗的控制器为使VSG具备与同步发电机相同的电性能,所以引出了电压外环控制器,与此同时,为了有功和无功功率环之间的解耦,方便相关参数的整定,于是在该控制器处引入一个虚拟阻抗L2,综上所述,可以得到改进的电压外环控制框图,如图10所示㊂图10㊀引入虚拟阻抗的电压外环控制框图Fig.10㊀Block diagram of the voltage outer loop controlwith introduction of virtual impedance3.5.2㊀基于准PR控制器的电流内环控制器本文所要达到的,不仅仅是精确地跟踪电网的额定频率,即使出现了一些细微的改变,也要进行相应的控制㊂而理想PR控制器只能对指定的频率处的传递函数进行放大,其他频率处的增益效果很低,所以引出了基于准PR控制器的电流内环控制,它的传递函数如式(9)所示:31重庆工商大学学报(自然科学版)第41卷A PR(s)=k p+2k rω1ss2+2ω1s+ω22(9)其中:k p和k r为PI控制器中的共振系数,ω1为截流频率,ω2为共振频率㊂针对各种系数的选择,可以与伯德图相联系来做特定的分析[10],采用控制变量法,在保证相关参数不变的情况下,只让一个参数进行相关的变化,从而进一步得到随着谐振系数的增大,系统谐振点的增益明显扩大,但其带宽不变,使系统的响应速度加快,进而可以使得搭建的仿真更加切合实际,但是谐振系数也不可能无限扩大,首先就是成本的问题,其次如果谐振系数过大,对于电力系统高次谐波的滤除非常困难,当然,如果谐振系数过小也不行,会对电力系统的低次谐波具有一定的放大作用,因此需要不断的试错,进一步获得更为合适的值;而当比例系数增加时,系统功率的总增益增加,但系统带宽保持不变,以及共振点的相位差显著地降低了,对于功率的准确控制也会产生一定的影响因此也需要不断的试错,进一步获得更为合适的值,再结合LC滤波器的传递函数便可得到改进的电流内环控制框图,如图11所示㊂图11㊀基于准PR控制器的内回路电流控制框图Fig.11㊀Block diagram of inner loop current controlbase on quasi PR controller其中A F(s)=1(L1s+R)(10)4㊀实验仿真与分析为检验上所述控制策略是否正确,是否有效,在PowerFactory模拟软件中,建立了一个光伏存储装置,如图12所示电力联运系统,其中光伏逆变器的面板数设为2800个,额定视在功率100MVA,有功功率设为291kW,次暂态短路水平500kVA,K系数为2,最大电流为1p.u.,最小运行电压的开启阈值和关闭阈值分别是0.1p.u.和0.01p.u.,开关闭合延时设置为1s㊂而对于储能系统并联了6个储能单元,其额定视在功率设置为10MVA,有功功率为1MW,无功功率为0.03Mvar,对于暂态时间常数和次暂态时间常数分别设置为1.2s和0.03s,与光伏发电系统的时间常数一致;储能系统的最小运行电压的关闭阈值设置为0,开启阈值设置为0.1p.u.,时间延迟忽略不计,对于电力系统发生扰动或者故障时,储能系统可以迅速做出相应的响应,从而维持电力系统的频率稳定㊂对于储能系统电流控制器的d轴和q轴的比例增益以及时间常数默认为0.1s和0.01s,与光伏发电系统的d轴和q 轴的比例增益以及时间常数一致㊂端点外部电网线路线型(1)A Cb u sL o a d2L o a d1光伏P VP a n静态发电机变压器变压器端点(2)B E S S图12㊀光伏储能并网供电系统Fig.12㊀Photovoltaic energy storage and grid-connectedpower supply system4.1㊀仿真算例1为验证这种改良的主动支撑控制方法的正确性与有效性,在IEEE39节点系统上进行仿真,提供了主动支撑控制策略实施的背景,主要是考率新能源的渗透率,如风电站和光伏发电站,对于风电站中的风机主要以双馈风电机为主,具体的双馈风电机的控制框架如图13所示㊂由于采用的仿真软件对于风机的功率封装是固定的,无法通过实时改变功率来控制风电站的功率输出,主要是通过改变风速来实时改变功率的输出㊂对于光伏发电站的一个控制框架具体如图14所示㊂对于光伏电机的功率控制,主要考虑了太阳辐射和温度,二者是光伏发电站输出功率的主要因素㊂在IEEE39节点系统中分别在母线1和母线16处设置了一座风电站和光伏发电站,两座风电站的并联机器数都是设为100台㊂然后在不考虑发电厂的调频作用,以及负荷自带的调频作用,观察所有光伏发电站和风电站运行时,系统的频率变化,具体如图15所示㊂41第2期黄荣,等:储能辅助电网参与调频的控制策略研究F r a m e D F I GG e n e r i c :M e c h a n i c sP i t c h C o n t r o l E i m D s l *w i n d s p e e d be t a s p e e dT u r b i n eE i m D s l *vw p wS h a f tE i m D s l *p tS p e e d R e fE i m D s l *E l e c t r o n i cD F I GE i m A s m *s p e e d _r e fM P TE i m M p t *S p e e d -C t r lE i m D s l *S l o w F r e q u M e a s E i m P h i *V a c _g e n S t a V m e a *V a c _b u s S t a V m e a *u:u g r :u g i P r o t e c t i o n E i m P r o *d u d _s y n c h :d u q _s y n c h Fm e a s P Q _t o tS t a P q m e aO v e r F r e qP w r R e d u c i o n E i m D s l *P r e fl r o tP QC o n t r o l E i m P Q *u s r ;u s ip s i r _r ;p s i r _ic o s p h i r e f ;s i n p h i r e f c o s p h i m ;s i n p h i mi d i qC o m p e n s a t i o n E i m C o mp c t r l ;q c t r l i r _c t r l *P t o ti r d _r e f ;i r q _r e fT h e t a m e a s .E i m P h i *i r d ;i r qc o s p h i u ;s i n p h i uu d oC u r r e n tM e a s u r e m e n t *图13㊀双馈风电机的控制框架Fig.13㊀Control frame of DFIG -based wind turbine systemF r a m e P VS y s t e m :U a r r a yS o l a r R a d i a t i o nE i m D s iT e m p e r a t u r eE i m D s iP o w e r M e a s u r e m e n tS t a P q m e aP h o t o v o l t a i c M o d e lE i m D s i S l o wF r e q u e n c y M e a s u r …E i m P h i *E _i n 01;E _i n 02;E _i n 03;E _i n 04;E _i n 05;E _i n 0Et h e t aM e a s u r e m e n t S o l a r R a d i a t i o nE i mF i l eM e a s u r e m e n t T e m p e r a t u r eE i mF i l eT _i n 01;T _i n 02;T _i n 03;T _i n 04;T _i n 05;T _i n 0123l a r r a y1P _c o n vD C B u s b a r a n d C a p a c i t o r M o d e lE i m D s iv d c r e fA C V o l t a g eS t a V m e aA c t i v e P o w e r R e d u c t i o nE i m D s iu a cp r e dP h a s e M e a s u r e m e n t …E i m P h i *C o n t r o l l e rE i m D s i00110123i d _r e f i q _r e fs i n r e f ;c o s r e f2S t a t i c G e n e r a t o rE i m G e n s t a t ,E i m P …图14㊀光伏电机的控制框架Fig.14㊀Control frame of photovoltaic motor50.0049.9549.9049.8549.8049.7549.70020406080100G05:电频率频率/H zt /s图15㊀系统频率的变化Fig.15㊀Changes in system frequency由图15可以看出,在忽略负荷变化时,仅仅是因为风电站和光伏电站的并入,就导致了整个系统的频率变化,可见在新能源高渗透率的情况下,当系统的频率变化的不稳定时,增加电力系统的稳定性是大势所趋,储能电站辅助电网调频势在必行㊂在上述的开关事件㊁负荷扰动事件以及高比例新能源渗透率的情况下,进行仿真,观察储能系统在5s和10s 时,储能系统的动作响应,如图16所示㊂图16可以看到,储能系统在开关事件和负荷扰动事件发生时,上述控制策略控制储能系统迅速做出响应,充分发挥了储能电池的快速充放电特性,为电力系统的调频51重庆工商大学学报(自然科学版)第41卷稳压奠定了基础㊂1312111098765B E S S :有功功率24681012141618202224条形图功率/M Wt /s图16㊀储能系统的出力Fig.16㊀Output of the energy storage system4.2㊀仿真算例2在上述所建模型和控制策略的基础上,对此进行了改进,主要是对虚拟同步发电机底层控制进行了优化和改进,为了让仿真速度加快,更适用于实际应用场景,所以对上述模型进行了简化,为了验证上述控制策略的正确性㊁有效性以及优越性,在仿真的5s 时,在交流母线处设置了开关事件,事件是PowerFactory 自带的开关事件,与此同时为检验以上所述控制策略是否正确,是否有效,又在仿真的10s 处设置了负荷事件,其有功功率比例阶跃负荷设置为20%,具体的仿真图形如图17所示㊂50.00049.99549.99049.98549.9849.97549.97049.96549.960A C b u s :电频率24681012141618202224条形图频率/H z t /s图17㊀交流母线处的实测频率Fig.17㊀Measured frequency at the AC bus由图17可得,对VSG 底层控制的优化和改进,不仅使得储能系统在开关事项和负荷扰动事件发生时,更加迅速地做出响应,而且保证了系统频率偏差在0.2Hz 以内,保证了系统频率的稳定性,证明了该优化控制策略的有效性㊂5㊀结㊀论针对高比例新能源发电,如光伏㊁风电的并网,进而导致的一系列调频问题,提出了基于VSG 三阶模型的改进的主动支撑控制策略,结论如下:(1)对同步发电机的基本原理进行了详尽的介绍,与此同时,将其与VSG 控制策略进行比较,在此基础上说明了VSG 的技术的可行性和必要性㊂(2)在 双碳 目标提出的背景下,随着新能源渗透率的持续增加,电网的频率调节压力也在增加,并且因为低惯性的特性,导致电力系统的稳定性,也越来越差,从而引出了储能系统的加入势在必行㊂(3)基于VSG 三阶模型的改进的主动支撑控制策略的提出,并对其模型进行了搭建,充分证明了策略对储能系统的控制作用,充分发挥了储能系统的快速充放性,改善了电力系统的频率质量,提高了储能电站并网的调频稳压能力㊂(4)通过在IEEE39节点中根据各个省市的电网情况,如风电站的分布,光伏发电站的分布,以及发电厂的分布,在该系统上进行严格的模拟,进一步可以得到高比例新能源渗透率的情况下,风电站和光伏发电站在并网时,对整个电力系统的频率的实时的影响,以及对于储能电站的分布和储能电池的容量配置都具有一定的参考意义㊂参考文献 References1 ㊀史立山.构建适应可再生能源资源特点的新型电力体系J .电网与清洁能源 2009 25 4 1 4.SHI Li-shan.Building a new power system adapted to thecharacteristics of renewable energy resources J .Power Grid and Clean Energy 200925 4 1 4.2 ㊀闫晓霞 张金锁 邹绍辉.我国可耗竭能源资源最优开采模型研究 J .中国管理科学 2016 24 9 81 90.YAN Xiao-xia ZHANG Jin-suo ZOU Shao-hui.Research onthe optimal exploitation model of depletable energy resources in China J .Management Science in China 2016 24 981 90.3 ㊀吕志鹏 盛万兴 钟庆昌 等.虚拟同步发电机及其在微电网中的应用 J .中国电机工程学报 2014 34 16 2591 2603.LV Zhi-peng SHENG Wan-xing ZHONG Qing-chang et al.Virtual synchronous generator and its applications in micro grid J .Proceedings of the CSEE 2014 34 16 259161。
Materials science of energy storage devices

Materials science of energy storagedevices能源储存设备的材料科学随着社会的发展,人们对能源的需求也越来越高。
然而,可再生能源的利用受到很多限制,而传统的化石能源则受到环境的限制。
因此,研究和发展高效的能源储存设备成为一个非常重要的领域。
能源储存设备无疑是当今科技领域中最重要的研究方向之一,能否研发出更加高效的能源储存设备将会是我们解决能源问题的关键。
在能源储存设备的发展中,材料科学发挥了极其重要的作用。
目前已经有很多种材料被用于能源储存设备的制造当中,并取得了很好的效果。
下面我们将具体介绍一些相关的材料科学知识。
1. 锂离子电池锂离子电池是目前最常用的电池之一,适用于各种场合,如手机、笔记本电脑及各类电动工具等。
锂离子电池内部主要由电解液、正极和负极等组成。
其中正极是一个非常重要的组成部分,可以影响到锂离子电池的很多特性。
锂离子电池正极的材料通常为锂离子插层化合物,如钴酸锂(LiCoO2)、锰酸锂(LiMn2O4)和三元材料(LiNiCoAlO2)。
这些化合物具有很好的耐久性、稳定性和能量密度,可以在锂离子电池中表现出很好的性能。
2. 硫化锂电池硫化锂电池是锂离子电池的一种变种。
它采用与锂离子电池不同的材料组成,因此具有更高的能量密度和更好的环保性。
其主要材料为锂金属和硫化物。
硫化锂电池的正极和负极则分别为硫化物和锂金属。
硫化锂电池使用这些材料可以在没有内燃机的情况下提供大量的能量,同样地,在制造和维护上也更加环保、更经济。
3. 金属空气电池金属空气电池又称为金属空气燃料电池,是一种使用空气氧气来提供氧化剂的电池,采用的是一种化学反应将金属材料(如锌、铝或者镁)中的电子转移到外部电路中,提供电能。
金属空气电池的优势在于比锂离子电池体积更小、更轻。
由于其极高的能量密度,金属空气电池可以在很短的时间内提供大量能量。
不过这类电池也有它的不足之处,主要是因为这类电池在反应过程中会产生大量的热量和化学气体。
电化学储能消防设计审查流程

最新职场沟通心得体会(汇总8篇)(经典版)编制人:__________________审核人:__________________审批人:__________________编制单位:__________________编制时间:____年____月____日序言下载提示:该文档是本店铺精心编制而成的,希望大家下载后,能够帮助大家解决实际问题。
文档下载后可定制修改,请根据实际需要进行调整和使用,谢谢!并且,本店铺为大家提供各种类型的经典范文,如合同协议、工作计划、活动方案、规章制度、心得体会、演讲致辞、观后感、读后感、作文大全、其他范文等等,想了解不同范文格式和写法,敬请关注!Download tips: This document is carefully compiled by this editor. I hope that after you download it, it can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you!Moreover, our store provides various types of classic sample essays, such as contract agreements, work plans, activity plans, rules and regulations, personal experiences, speeches, reflections, reading reviews, essay summaries, and other sample essays. If you want to learn about different formats and writing methods of sample essays, please stay tuned!最新职场沟通心得体会(汇总8篇)心得体会是对所经历的事物的理解和领悟的一种表达方式,是对自身成长和发展的一种反思和总结。
储能技术及应用 英文课程

储能技术及应用英文课程Energy Storage Technology and Applications.Energy storage technology plays a crucial role in the modern energy landscape, enabling the efficient and effective use of renewable energy sources, grid stability, and load management. This course will provide a comprehensive overview of energy storage technologies and their applications.The course will begin by exploring the fundamentals of energy storage, including the different types of energy storage systems such as electrochemical (batteries), mechanical (pumped hydro, compressed air), thermal (molten salt, phase change materials), and electrical (supercapacitors, flywheels). We will delve into the working principles, performance characteristics, and applications of each technology, considering their strengths, limitations, and cost-effectiveness.Furthermore, the course will examine the integration of energy storage systems with renewable energy sources, grid infrastructure, and microgrid applications. We will discuss the role of energy storage in enhancing grid stability,peak shaving, frequency regulation, and demand response. Case studies and real-world examples will be used to illustrate the practical implementation and benefits of energy storage solutions in different contexts.In addition, the course will address the economic and regulatory aspects of energy storage, including market trends, policy incentives, and business models. We will analyze the evolving landscape of energy storage deployment, considering factors such as project financing, revenue streams, and market opportunities.Overall, this course aims to provide students with a comprehensive understanding of energy storage technologyand its diverse applications, equipping them with the knowledge and skills to evaluate, design, and implement energy storage solutions in various energy systems and industries.。
锂电池电力储能系统

锂电池电力储能系统且符合要求摘要锂电池储能系统在近几年得到了广泛的应用,它将成为一种新的可再生能源储能技术。
本文首先介绍了锂电池储能系统的工作原理和技术特点,并分析了当前锂电池储能系统所面临的挑战,然后介绍了锂电池储能系统的未来发展趋势,最后总结了锂电池储能系统的主要优势和发展前景。
关键词:锂电池储能系统;工作原理;技术特点;未来发展IntroductionWorking PrincipleTechnological CharacteristicsLI-ESS has the following technological characteristics:1、High energy density: Li-ESS can store more energy perunit weight than other energy storage technologies.2、High efficiency: Li-ESS has high conversion efficiency, which can exceed 90%.4、Low environmental impact: Li-ESS has a low environmental impact thanks to its low maintenance requirements and efficient use of energy.ChallengesDespite its advantages, Li-ESS faces several challenges to its widespread deployment. Firstly, Li-ESS is expensive, and the cost of large-scale Li-ESS is still an obstacle to its widespread adoption. Secondly, Li-ESS has high safety requirements, and proper safety measures should be taken when operating Li-ESS. Lastly, Li-ESS requires careful monitoring and maintenance to ensure its long service life.Future DevelopmentThe future of Li-ESS is promising. The cost of Li-ESS has been steadily declining, and technological advances have made the technology safer and more efficient. Furthermore, with the development of smart grid technology, Li-ESS will play an increasingly important role in the operation of the grid. Li-ESS will also be used for applications such as electric vehicles and residential energy storage.Conclusion。
The future of energy Energy storage

The future of energy Energy storageEnergy storage is a crucial aspect of the future of energy, as it allows for the efficient utilization of renewable energy sources such as solar and wind power. With the increasing focus on sustainability and reducing carbon emissions, the development of energy storage technologies has become a key priority for governments, businesses, and individuals alike. By storing excess energy generated during peak production times, energy storage systems can help balance the supply and demand of electricity, ensuring a reliable and stable energy grid. One of the main challenges facing energy storage technologies is the issue of scalability. While there are a variety of energy storage solutions available, such as batteries, pumped hydro storage, and thermal energy storage, many of these technologies are not yet cost-effective or efficient enough to be deployed on a large scale. In order to fully realize the potential of energy storage, significant advancements need to be made in terms of improving the performance and reducing the costs of these technologies. Despite these challenges, there have been significant developments in the field of energy storage in recent years. Advances in battery technology, such as the development of lithium-ion batteries, have made energy storage more accessible and affordable for consumers and businesses. Additionally, innovations in grid-scale energy storage systems, such as flow batteries and compressed air energy storage, have shown promise in providing long-duration storage solutions for renewable energy sources. The integration of energy storage systems with renewable energy sources is also a key area of focus for researchers and industry experts. By coupling energy storage with solar and wind power, it is possible to create a more reliable and resilient energy grid that can betterhandle fluctuations in energy production. This integration can also help to reduce the need for traditional fossil fuel-based power plants, leading to a decrease in greenhouse gas emissions and a cleaner environment. In addition to the technical aspects of energy storage, there are also important policy and regulatory considerations that need to be addressed in order to promote the widespread adoption of energy storage technologies. Governments play a crucial role in incentivizing the deployment of energy storage systems through the implementation of supportive policies, such as tax credits, grants, and feed-in tariffs. Bycreating a favorable regulatory environment, policymakers can help to accelerate the development and deployment of energy storage solutions. Overall, the future of energy storage is promising, with significant advancements being made in technology, policy, and integration with renewable energy sources. As the world transitions towards a more sustainable energy future, energy storage will play a critical role in ensuring a reliable and resilient energy grid. By continuing to invest in research and development, as well as implementing supportive policies, we can unlock the full potential of energy storage and pave the way for a cleaner and more sustainable energy system.。
EnergyStorageSystem

Pumped Hydroelectric Energy Storage
Operation: It consists of two large reservoirs located at different elevations. During peak demand, water is released from the upper reservoir. If Production exceeds Demand, water is pumped up and stored in the upper reservoir. Pump used is a Combined Motor and Dynamo.
Classified on the basis of operating conditions and various electrolytes used. Alkaline fuel cells (AFC) Polymer electrolyte membrane (PEM) Phosphoric acid fuel cells (PAFC) Molten carbonate fuel cells (MCFC) Solid oxide fuel cells (SOFC) Regenerative fuel cells
Properties of some materials used for build disadvantages:
Very compact when compared to other energy storage systems. Flywheels are used for starting and braking locomotives. A flywheel is preferred due to light weight and high energy capacity. It is not economical as it had a limited amount of charge/discharge cycle.
储能系统介绍

02 储能系统种类
Types of energy storage systems
2 电气储能:
Electrical energy storage
超级电容器储能: 用活性炭多孔电极和电解质组成的双电层结构获得超大的电容量。
抽水蓄能: 将电网低谷时利用过剩电力作为液态能量媒体的水从地势:低的水库抽到地势高的水 库,电网峰荷时高地势水库中的水回流到下水库推动水轮机发电机发电。
压缩空气储能: 利用电力系统负荷低谷时的剩余电量,由电动机带动空气压缩机,将空气压入作为储 气室的密闭大容量地下洞穴,当系统发电量不足时,将压缩空气经换热器与油或天然 气混合燃烧,导入燃气轮机作功发电。
储能系统可以实现在电力系统负,有助于促进可再生能源和清洁能源的大规模应用。储能技术也有助于解决电力系统 与用电需求之间的不匹配问题,提高电网的效率和可持续性。
04
电化学储能工作原理
Working principle of electrochemical energy storage
PART FOUR
04 电化学储能工作原理
Working principle of electrochemical energy storage
1 电池储能技术原理
Principle of battery Energy storage
储能技术是指通过物理或化学等方法实现对电能的储存,并在需要时进行释放的一系列相关技术。一般而言,根据储存 能量的方式不同可将其分类为机械储能、电磁储能及电化学储能。机械储能又可划分为抽水储能、压缩空气储能、飞轮 储能。电磁储能主要包括超导磁储能和超级电容器储能。电化学储能的方式是将电能以化学能形式进行储存和释放。目 前的电化学储能主要包括电池和电化学电容器的装置实现储能,常用的电池有铅酸电池、铅炭电池、钠硫电池、液流电 池、锂离子电池等。电化学储能技术具有高效率、应用灵活性、响应速度快等优点逐渐在电力储能市场占有越来越重要 的地位。
含分布式风电和储能的配网潮流计算方法研究

含分布式风电和储能的配网潮流计算方法研究吴彤;陈洪涛;赵建明;李国庆【摘要】为了解决传统潮流计算方法未能考虑复杂配电网中分布式电源随机性的问题,进而分析高渗透率下分布式风电和储能装置对配电网电压质量的影响。
在传统潮流计算的基础上,综合考虑风机功率输出特性和储能装置的双向潮流特性,提出了一种简化的潮流计算方法,并采用Matlab软件进行程序编译,最后以PSAT 工具箱搭建仿真模型,验证算法的有效性。
%In order to solve the problem that the traditional power flow calculation method failed to consider the randomness of the distributed power supply in complex distribution network. Analysis the affects of high perme-ability of the distributed wind power and energy storage devices to the voltage quality of the distribution net-work. This paper based on the conventional power flow calculation, considerate the output characteristics of wind generator and the two-way trend features of energy storage device,proposes a simplified method for power flow calculation. Using Matlab software to compile program. Finally,using PSAT toolbox to build a simulation model to verify the validity of the algorithm.【期刊名称】《东北电力大学学报》【年(卷),期】2015(000)003【总页数】5页(P1-5)【关键词】分布式风电;储能;潮流计算;PSAT【作者】吴彤;陈洪涛;赵建明;李国庆【作者单位】东北电力大学电气工程学院,吉林吉林132012;国网吉林省电力有限公司松原供电公司,吉林松原138000;国网吉林省电力有限公司松原供电公司,吉林松原138000;东北电力大学电气工程学院,吉林吉林132012【正文语种】中文【中图分类】TM61;TM743吴彤1,陈洪涛2,赵建明2,李国庆1(1.东北电力大学电气工程学院,吉林吉林132012;2.国网吉林省电力有限公司松原供电公司,吉林松原138000)随着分布式风电电源和储能装置在电网中渗透率的增加,使得配电网从传统的辐射状网络转变为多电源供电模式,进而改变了配电系统的结构和运行模式,这无疑会对配电网的电压分布、潮流走向等方面产生影响[1-3]。
Innovations in Renewable Energy Storage

Innovations in Renewable Energy Storage Renewable energy sources such as solar and wind power have gained significant traction in recent years as the world seeks to reduce its reliance on fossil fuels and combat climate change. However, one of the major challenges associated with renewable energy is its intermittent nature. Unlike traditional power sources,such as coal or natural gas, renewable energy production is dependent on factors such as sunlight and wind, which are not always consistent. This variability presents a significant obstacle to the widespread adoption of renewable energy. One potential solution to this problem lies in the development of innovativeenergy storage technologies. Energy storage systems can help to store excessenergy generated during peak production periods, allowing it to be used during times of low production. This not only helps to address the intermittency of renewable energy sources but also provides a more reliable and stable energy supply. In this response, we will explore some of the latest innovations in renewable energy storage and their potential impact on the future of energy production. One of the most promising developments in renewable energy storage is the advancement of battery technology. Batteries have long been used to store energy, but recent advancements in battery technology have significantly improved their efficiency and cost-effectiveness. In particular, lithium-ion batteries have emerged as a leading option for storing renewable energy. These batteries are capable of storing large amounts of energy and can be deployed at various scales, from residential to utility-scale applications. Additionally, ongoing research and development in battery technology continue to drive improvements in energy density, lifespan, and safety. As a result, batteries are increasingly being integratedinto renewable energy systems, providing a reliable means of storing excess energy for use when production is low. Another area of innovation in renewable energy storage is the development of pumped hydro storage. This technology involves using excess energy to pump water from a lower reservoir to a higher reservoir, where it can be stored. When energy is needed, the water is released back down to the lower reservoir, passing through turbines to generate electricity. Pumped hydro storage systems have been in use for decades, providing a proven and reliable method of energy storage. However, recent advancements in pumped hydro technology, such asthe use of advanced materials and improved system design, have increased the efficiency and flexibility of these systems. As a result, pumped hydro storage is being increasingly considered as a viable option for large-scale energy storage, particularly in areas with suitable topography. In addition to batteries and pumped hydro storage, other innovative energy storage technologies are also emerging. For example, thermal energy storage systems utilize excess energy toheat or cool a storage medium, such as molten salt or phase change materials. This stored thermal energy can then be used to generate electricity or provide heating and cooling when needed. Similarly, flywheel energy storage systems store energyin the form of rotational kinetic energy, which can be converted back toelectricity when required. These and other emerging energy storage technologies offer a diverse range of options for storing renewable energy, each with its own unique advantages and applications. The development of innovative energy storage technologies has the potential to revolutionize the way we produce and consume energy. By addressing the intermittency of renewable energy sources, energystorage systems can help to create a more reliable and resilient energy infrastructure. This, in turn, can accelerate the transition to a more sustainable and low-carbon energy system. Moreover, the widespread adoption of energy storage technologies can also have significant economic benefits, creating newopportunities for investment, job creation, and technological innovation. As such, the development of renewable energy storage technologies represents a crucial step towards a more sustainable and secure energy future. However, despite the tremendous potential of energy storage technologies, there are still challengesthat need to be addressed. One of the primary obstacles is the cost associatedwith deploying energy storage systems. While the cost of battery technology has been steadily declining, it still represents a significant upfront investment for many consumers and businesses. Additionally, the integration of energy storage systems into existing energy infrastructure can be complex and require careful planning and coordination. Furthermore, there are technical challenges related to the performance and reliability of energy storage systems, particularly as theyare scaled up to meet the demands of large-scale energy production. In conclusion, the development of innovative energy storage technologies represents a criticalstep towards realizing the full potential of renewable energy sources. From advanced battery technology to pumped hydro storage and emerging technologies such as thermal and flywheel energy storage, there is a diverse range of options for storing renewable energy. These technologies have the potential to address the intermittency of renewable energy sources, create a more reliable and resilient energy infrastructure, and drive economic growth and innovation. However, there are still challenges to overcome, including cost, integration, and technical performance. Nevertheless, with ongoing research and development, collaboration between industry and government, and continued investment, the future of renewable energy storage looks promising. As we continue to advance these technologies, we move closer to a more sustainable and secure energy future for generations to come.。
- 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。
StructuresJournal of Intelligent Material Systems andDOI: 10.1177/1045389X070789692008; 19; 671 originally published online Jul 10, 2007;Journal of Intelligent Material Systems and Structures M.J. Guan and W.H. LiaoCharacteristics of Energy Storage Devices in Piezoelectric Energy Harvesting Systems /cgi/content/abstract/19/6/671The online version of this article can be found at:Published by:can be found at:Journal of Intelligent Material Systems and Structures Additional services and information for /cgi/alerts Email Alerts: /subscriptions Subscriptions: /journalsReprints.nav Reprints: /journalsPermissions.nav Permissions:/cgi/content/refs/19/6/671 CitationsCharacteristics of Energy Storage Devices in PiezoelectricEnergy Harvesting SystemsM.J.G UAN AND W.H.L IAO*Smart Materials and Structures Laboratory,Department of Mechanical and Automation EngineeringThe Chinese University of Hong Kong,Shatin,N.T.,Hong Kong,ChinaABSTRACT:Using piezoelectric elements to harvest energy from ambient vibration has beenof great interest recently.As the power harvested from the piezoelectric element is relativelylow,energy storage devices are needed to accumulate the energy for intermittent use.In thisstudy,the energy storage devices considered include rechargeable batteries and super-capacitors.The traditional electrolytic capacitors are not considered due to their low energydensity.The charge/discharge efficiencies of the energy storage devices are of major concern.The equivalent circuit model of the energy storage devices is investigated.It is found that theleakage resistances of the energy storage devices are the dominant factor that influences thecharge/discharge efficiency in the piezoelectric energy harvesting systems.A quick test methodis proposed to experimentally study the charge/discharge efficiencies of the energy storagedevices.The experimental results verify our findings.Adaptability,lifetime,and chargingprotection circuit of the energy storage devices are also discussed.It can be concluded thatsupercapacitors are suitable and more desirable than the rechargeable batteries to store theenergy in the piezoelectric energy harvesting systems.Key Words:energy storage device,piezoelectric energy harvesting,charge/dischargeefficiency,leakage resistance.INTRODUCTIONW IRELESS sensor networks(WSNs)have drawn significant attention in monitoring plants, resources,and infrastructures(Liao et al.,2001). Traditional electrochemical batteries are usually used in powering the WSNs.But replacing batteries,due to their limited lifetime,is very inconvenient.The labor and cost associated with changing hundreds or thousands of batteries would be troublesome and expensive in maintaining the networks.Moreover,in many cases, the WSNs are installed in remote areas;therefore,it is difficult to retrieve for battery replacement.Without replacing batteries,the WSNs will stop working as soon as the power runs out.Therefore,it is desired that the WSNs can acquire energy from the ambient environ-ment to have a perpetual power supply.Considering the needs,for example,the health moni-toring of infrastructures,to harvest the power from the vibration environment would be a convenient means to supply power for the sensor network.While there are several options for harvesting the ambient vibrational power,piezoelectric materials have been of great interest and promise(Starner,1996;Umeda,et al.,1997; Elvin et al.,2001;Shenck and Paradiso,2001;Roundy et al.,2003;Guyomar et al.,2005;Kim et al.,2005; Ng and Liao,2005;Beeby et al.,2006;Shu and Lien, 2006).Several researchers have put their efforts in the piezoelectric energy harvesting area.Roundy et al. (2003)drove a bimorph PZT simulating the vibrations on a small microwave oven.The vibrating PZT has an average output power of250m W.Shenck and Paradiso (2001)developed a piezoelectric system that would harvest the energy during walking and used it to power a radio transmitter.An average output power of1.8mW was obtained.As the average harvested power is less,usually,some energy storage means are needed to accumulate the harvested energy for intermittent use.Most of the earlier research on power harvesting used the traditional electrolytic capacitors as energy storage devices (Starner,1996;Umeda et al.,1997;Elvin et al.,2001; Shenck and Paradiso,2001;Ng and Liao,2005).But due to the low energy density of traditional electrolytic capacitors,the output energy from the capacitor storage per discharge cycle is very limited.For example, if a1000m F capacitor is discharged from5to2V, which is a normal operating voltage range for many electronic sensors,it can only let a kind of sensor node,*Author to whom correspondence should be addressed.E-mail:whliao@.hkFigures3,4and6–8appear in color online:J OURNAL OF I NTELLIGENT M ATERIAL S YSTEMS AND S TRUCTURES,Vol.19—June2008671 1045-389X/08/060671–10$10.00/0DOI:10.1177/1045389X07078969ßSAGE Publications2008Telos Mote,developed by Berkeley,work in active mode for0.15s.The Telos Mote operates at an extremely low voltage of1.8V and also has the lowest working current among existing wireless sensor nodes(Jiang et al.,2005). It consumes a current of20mA in active mode and5m A in sleep mode.Therefore,rechargeable batteries are considered due to their higher energy density(Ottman et al.,2002,2003;Sodano2004,2005a).Sodano et al. (2005a)showed that a40mA nickel metal hydride (NiMH)rechargeable battery could be charged from a completely discharged state in less than one hour underthe vibration from a typical vibrating machine. However,they only showed the feasibility of using the rechargeable battery as energy storage device but did not evaluate the performances such as efficiency of the energy storage cells.Supercapacitors are alternative energy storage devices other than traditional electrolytic capacitors and rechargeable batteries.They are also named ultracapa-citor,double-layer capacitor(DLC),and electrical double-layer capacitor(EDLC).The energy density of supercapacitors is10–100times higher than that of traditional electrolytic capacitors.Supercapacitors could benefit many applications,from those involving short power pulses to those requiring low-power supplies of critical memory systems.So far,few researchers have looked into supercapacitors as energy storage devices in energy harvesting.Casciati et al.(2005)developed a vibrational energy harvesting device and mentioned using a supercapacitor for energy storage but did not provide any experimental results.Jiang et al.(2005) presented their implementation of a solar energy harvesting system and used a supercapacitor as the primary energy storage device.Their results showed that supercapacitors can be employed as energy storage devices in the energy harvesting systems.However, the performances of supercapacitors as the energy storage device were not evaluated.Rechargeable battery or supercapacitor,which one is preferred when used in the piezoelectric energy harvesting system?To address this issue,the character-istics of supercapacitors and rechargeable batteries as energy storage devices in piezoelectric energy harvesting will be studied and compared in this study. Charge/discharge efficiency,adaptability to piezoelectric harvesting circuit,lifetime,and charge protection circuit of these energy storage devices will be discussed by considering the piezoelectric energy harvesting systems.PIEZOELECTRIC ENERGY HARVESTINGA piezoelectric energy harvesting system can be basically divided into three parts:the energy source, the harvesting circuit,and the storage device.Energy SourceA harmonic vibrating piezoelectric element can be modeled as a sinusoidal current source i p in parallel with its internal capacitance C p as shown in Figure1.i pðtÞ¼I p sin!tð1Þwhere!and I p are the frequency and peak amplitude of the current source,respectively.The peak open-circuit voltage V oc of the source is related to I p by,V oc¼I p!C pð2ÞThe value of the peak open-circuit voltage depends on the type and size of piezoelectric element,vibration level and frequency.In general,V oc ranges from several volts to tens or hundreds of volts(e.g.,150V in Shenck and Paradiso,2001;67V in Ottman et al.,2002).While V oc was assumed by Ottman et al.(2002)to be relatively unchanged regardless of the external harvesting circuit, it should be noted that the vibrating structure can be modified to obtain different V oc even with the same excitation.Harvesting CircuitA basic energy harvesting scheme is shown in Figure 1.Since the source is alternating,a diode bridge rectifier is used as an AC–DC rectifier. As developed by Ottman et al.(2002),there exists an optimal rectifier voltage V rect_opt to harvest the energy for maximum power.The optimal rectifier voltage V rect_opt is one-half the peak open-circuit voltage V ocV rect opt¼V oc2¼I p2!C pð3ÞThe theoretical power harvested at a certain rectifier voltage V rect is,P theoretical¼V rect i esd¼V rectÁ2ðI pÀ!V rect C pÞð4Þwhere i esd represents the average current flowing into the energy storage device.From the previous studies (Ottman,2002),we know the efficiencies of theoreticalEnergystorage devicePiezoelectricelementFigure1.Basic piezoelectric energy harvesting circuit.672M.J.G UAN AND W.H.L IAOharvested power at different rectifier voltage levels can vary dramatically from5%to100%of the optimal harvested power.Since the power from the piezoelectric energy source is generally low,the rectifier voltage is strongly recommended to be at the optimal value.To harvest the power from varying exciting sources, another scheme is to use a two-stage harvesting circuit (Ottman,2003).The power from the piezoelectric element is firstly rectified to a temporary storage device whose voltage is kept at the optimal rectifier voltage,then transferred to the energy storage device through a converter.Guan and Liao(2007)have studied and compared the efficiencies of these two energy harvesting schemes considering the storage device voltages.In this study,we will explore the characteristics of energy storage devices in piezoelectric energy harvest-ing with the basic energy harvesting scheme.More discussions on the two-stage energy harvesting scheme are given in section‘Other Characteristics’.Storage DeviceThere are several types of energy storage devices including traditional electrolytic capacitors,recharge-able batteries,and supercapacitors.As discussed in the first section,traditional electrolytic capacitors may not work well as an energy storage device in the piezoelectric energy harvesting systems for WSNs due to their low energy density.In this study,rechargeable batteries and supercapacitors are considered.Rechargeable batteries mainly include nickel cadmium(NiCad),NiMH,and lithium ion/polymer(lithium)rechargeable batteries. Because the NiCad rechargeable batteries have memory effect,which is not suitable for shallow charging(however,energy harvesting is usually shallow charging),we will consider the NiMH and lithium rechargeable batteries in this study.CHARGE/DISCHARGE EFFICIENCYTheoretical AnalysisCharging and discharging rechargeable batteries or supercapacitors is never100%efficient.Charge/dis-charge efficiency,also called Coulombic efficiency or charging/discharging efficiency,is defined as,¼Discharge energyCharge energyð5ÞConsidering the low level of source energy in piezo-electric energy harvesting systems,the charge/discharge efficiencies of the energy storage devices are especially important.Based on the electrical characteristics of the energy storage devices,the charge/discharge efficiencies will be discussed.An equivalent circuit model for energy storage devices will be valuable to study the electrical characteristics.EQUIVALENT CIRCUIT MODELThe charge/discharge performances of rechargeable batteries or supercapacitors under various operating conditions are nonlinear and complicated.An equiva-lent circuit model to delicately describe their behaviors including self-discharge,overvoltage,and temperature effect is under study.The charge/discharge deficiency comes from the energy loss during the charge/discharge process.It is understood that the energy loss exists in two manners: internal series resistive loss and leakage loss.Therefore, an equivalent circuit model for energy storage devices as shown in Figure2is considered(Buchmann,2001). Figure2(a)and(b)describes the charge and discharge processes,respectively.In the circuit model,R int and R lea represent the internal series resistance and the leakage resistance,respectively;C s and V s represent the internal capacitance and the source voltage of the energy storage device respectively;V in and V out are the input/output voltage.The charge/discharge efficiency of the energy storage device is directly related to the energy losses due to the resistances R int and R lea.Therefore,the R int and R lea should be first explored.INTERNAL SERIES RESISTANCEThe internal series resistances of the energy storage devices such as rechargeable batteries and superca-pacitors are usually given in the specifications by manufacturers and also can be measured.The internal series resistance varies with the electrolyte type of different energy storage devices.For the supercapaci-tors,in particular,the internal series resistance is called equivalent series resistance(ESR)and ESR also varies with the cell capacity.The larger the cell capacity,the smaller the internal series resistance it has.Table1shows the internal series resistances of some energy storage devices measured by a precision impedance analyzer(40Hz–110MHz,Agilent4294A). The corresponding rated maximum ESR and internal resistances from manufacturers are also given for comparison.From Table1,we can find the manufacturer specifica-tions reliable for the internal series resistance.From the+_(a) Charged process(b) Discharged processsii−+sViiFigure2.Equivalent circuit model of the energy storage devices.Characteristics of Energy Storage Devices673specifications of several representative manufacturers,we find out that the internal series resistances of the common supercapacitors,with capacity from0.1F to3000F, range from30 to0.5m ;the internal series resistances of the common rechargeable battery cells of various capacity range from$50m to1 .LEAKAGE RESISTANCEThe leakage resistance of the energy storage device is an interesting issue but little understood since hitherto little work has been done on it.One kind of leakage resistance,the self-discharge resistance,has been studied.The self-discharge resistance refers to the leakage resistance under the self-discharge process. Self-discharge is a natural phenomenon of any recharge-able battery or supercapacitor.After fully charged, a rechargeable battery is usually maintained with a trickle charge to compensate for the self-discharge. For rechargeable batteries,several researchers used the self-discharge resistance as the leakage resistance (Salameh et al.,1992;Conway et al.,1997;Buchmann, 2001).For supercapacitors,we find the leakage resis-tance under other states is not equal but related to the self-discharge leakage resistance.In this part,we will study the leakage resistances of the supercapacitors under self-discharge and other states.At present,no quick test is available to measure the self-discharge of a rechargeable battery. Usually the self-discharge rate is described in capacity loss per month.For example,the self-discharge of the NiMH rechargeable battery is$30%per month(Buchmann,2001).The lithium rechargeable battery self-discharges$10%per month.The capacity of supercapacitors drops$35%per month.Based on the specifications of the self-discharge data from the manufacturers,we can estimate the average self-discharge resistance usingR lea self%V cellÂÁtQ cell %ð6Þwhere V cell and Q cell are the rated voltage and capacity of the cell; %is the self-discharge energy loss percentage in the time intervalÁt.From Equation(6), we find that the self-discharge resistance varies with the capacity of the cell.Table2gives the estimated self-discharge leakage resistances of the some commercially available energy storage cells.Conway et al.(1997)have analyzed the self-discharge mechanisms and proposed that in the charging condi-tion,electrochemical capacitors and batteries are in a state of high energy relative to that of the system in the discharging state.Hence there is a‘driving force,’corresponding to the free energy of discharge,tending to spontaneously diminish the charge if there exists some self-discharge mechanism(s).To find out the leakage resistances of super-capacitors under various states,experiments are conducted.The objective of experiments is to find out the leakage resistance under self-discharge and charging with certain levels of current on the super-capacitors.Suppose a supercapacitor with capacitance C s self-discharges from voltage V0,after timeTable1.Internal series resistances of the energy storage devices.Supercapacitor0.47F5.5V Supercapacitor1F5.5VPanasonic NF Panasonic SG NEC Tokin TK MAXCAP ELNA Philips Sam Young Rated max.ESR(at1kHz)(Ohms)303013307303030 Measured ESR(at1kHz)(Ohms)302912.816.4 1.810.814.98.4NiMH rechargeable battery Lithium rechargeable batteryEPT 110mAhBTY700mAhUSANCE700mAhPlantronic190mAhMotorola860mAhSamsung770mAhRated internal resistance(Ohms)0.200–10.200–10.200–10.200–10.200–10.200–1 Measured internal resistance(Ohms)0.1790.5400.1910.2900.2500.270Table2.Estimated self-discharge resistances of common energy storage cells.Energy storage device NiMH Lithium Supercapacitor Cell voltage 1.2V 3.6V 5.5VCell capacity30mAh500mAh30mAh500mAh0.47F20F Self-discharge leakage resistance96k 5.74k 8.5M 510k 15M 370k 674M.J.G UAN AND W.H.L IAOinterval Át ,its voltage decreases by ÁV ,then the self-discharge resistance can be calculated from Figure 2(b)by,R leaself%ÁtC s Âln V 0=ðV 0ÀÁV ½Þð7ÞSuppose a supercapacitor with capacitance C s is charged by current I in from voltage V 0,after time interval Át ,its voltage increases by ÁV ,then the leakage resistance under this charging process can be calculated from Figure 2(a)by,R leacha%V 0þðÁV =2ÞI in ÀC s ðÁV =Át Þð8ÞFigure 3shows the estimated results of the leakage resistances of several kinds of supercapacitors under various conditions.In Figure 3,‘MAX’,‘TK’,‘NEC’,‘SY’,‘ELNA’,‘PaSG’,‘Phi’,and ‘PaNF’represent eight supercapacitors from MAXCAP,TK,NEC Tokin,Sam Young,ELNA,Panasonic SG series,Philips and Panasonic NF series,respectively.Rated capacitances,voltages and ESRs of these eight supercapacitors are given in Table 1.From the results,we can find the leakage resistance under charging is always smaller than the self-discharge resistance.And as the charging current increases,the leakage resistance decreases.This can be understood based on Conway et al.’s (1997)analysis on self-discharge.The ‘driving force’under charging is larger than that when the energy storage cell is left alone.Therefore,the leakage current under charging is larger than the self-discharge current.The leakage resistance under charging is smaller than the self-discharge resistance.The study of leakage resistances of supercapacitors under various states could be interesting,but this is out of the scope of this study.In this study,the rangeof the leakage resistances is our major concern.From the experimental data,we can estimate the leakage resistances of supercapacitors under charging with a current no larger than 200m A will be in the range of 10–100%of the self-discharge leakage resistances depending on the levels of the charging current.POWER LOSS AND EFFICIENCYAs shown in Figure 2,the power losses of the internal series resistance during the charging and discharging processes are:P int cha ¼I in ÀV in R lea2ÂR int ð9ÞP int dis ¼I out þV out R lea2ÂR int ð10ÞThe power losses of the leakage resistance during the charging and discharging processes are:P lea cha ¼V 2inR lea ð11ÞP lea dis ¼V 2out R leað12ÞFrom the studies on the internal series resistances and leakage resistances,the leakage resistances are usually more than 100times the internal series resistances.Therefore,in Figure 2(a),the charge current i in is approximately equal to i int1.Similarly,in Figure 2(b),the discharge current i out is approximately equal to i int2.Therefore,the power losses of the internal series resistance R int during charging and discharging processesare approximately I 2in ÂR int and I 2out ÂR int ,respectively.Based on the range of the internal series and leakage resistances,we can plot the energy losses of the internal series resistance and leakage resistance under a range of the charge/discharge currents.The charge/discharge voltage is assumed to be 3V.The results are shown in Figure 4.From Figure 4,we can see that the energy losses of the internal series resistances greatly depend on the charge/discharge current while the energy losses of the leakage resistances are independent of the charge/discharge current.Basically,in higher current applications (0.5–10A),the energy loss due to the internal series resistance is much larger than the energy loss due to the leakage resistance.In lower current applications (1–200m A),the energy loss due to the internal series resistance is much smaller than that due to the leakage resistance.As stated in the previous section,the charge/discharge current is typically below 200m A in piezoelectric energy harvesting systems.Therefore,the leakage resistances are of the most importance in considering the efficiency of energy storage devices in piezoelectric energy harvest-ing systems.MAX TK NEC SY ELNA PaSG Phi PaNF123456SupercapacitorsL e a k a g e r e s i s t a n c e (M Ω)Figure 3.Leakage resistances of supercapacitors.Characteristics of Energy Storage Devices675The charge/discharge efficiency of the energy storage device can be calculated by,¼1ÀEnergy loss Charge energyð13ÞExperimental ValidationQUICK TEST METHODIn general,to test the charge/discharge efficiency of an energy storage device,a charger is connected to the storage device until fully charged.Then,a load is connected to the energy storage device to fully discharge it.The voltage and current passing through the device are monitored.Then Equation (5)is used to calculate the energy storage device’s efficiency.Monitoring all of the procedures and parameters is time-consuming and labor-intensive.Moreover,in piezoelectric energy harvesting,the source current usually is much lower than the current used in standard test.Thus using the full charge/discharge method to find out the charge/discharge efficiency in piezoelectric energy harvesting is not adopted in this study.As the charge/discharge efficiency of an energy storage device is almost the same during its total range of state of charge (SoC)except a bit lower near full SoC (Stevens and Corey,1996),we can test the charge/discharge efficiency within a small SoC range of the device.That is to say,we will charge and discharge the device between two close energy levels.Basically,the voltage of the device is an indicator of the energy stored in the device.However,the voltage–energy relations during charge and discharge processes are nonlinear for most energy storage devices.In this study,to overcome the nonlinear problem in testing,a method is applied to calculate the charge/discharge efficiencies of thesupercapacitors and rechargeable batteries.The sche-matic of this method is shown in Figure 5.During the charging process by the piezoelectric harvesting current,when the storage device’s voltage reaches a reference voltage V 0,we start calculating the time.After a certain time interval t 1,the voltage increases by ÁV .At the end of the interval t 1,we stop charging the cell and use a known current I dis to discharge the cell for a time interval t 2to voltage V 0ÀÁV .The discharging load is chosen to make the discharge current the same as the charge current from the piezoelectric element for a given excitation level.At the end of time interval t 2,we stop discharging the cell and start to recharge the cell to voltage V 0.The time interval used to recharge the cell to voltage V 0is denoted as t 3.When the voltage variation ÁV is small compared to V 0,we can useexp ¼Discharge energy Charge energy %I dis ÂV 0Ât 2P cha Âðt 1þt 3Þð14Þto calculate the charge/discharge efficiency.Based onEquation (4),the average charging power can be calculated by,P cha %V 0Á2ðI p À!V 0C p Þð15ÞThe method is based on the assumption that voltage–energy curve of the cell has a good repeatability during two consecutive charge/discharge cycles.EXPERIMENTAL SETUP AND RESULTSThe experimental setup is shown in Figure 6(a).The corresponding block diagram is shown in Figure 1.The components are described as follows.For the piezoelectric element,we use Mide quick pack QP20W,as shown in Figure 6(b),which was also used by Ottman et al.(2003)and Sodano et al.(2005b).The QP20W is a bimorph piezoelectric device that uses monolithicC e l l v o l t a g eFigure 5.Charge/discharge processes.110−101010Charge/discharge currentP o w e r l o s s (µW )Figure 4.Energy losses of the internal series resistances and leakage resistances.676M.J.G UAN AND W.H.L IAOpiezoceramic material embedded in an epoxy matrix. The epoxy shell makes it more robust than the raw monolithic material.One end of the QP20W is mounted on a shaker(B&K4810).The other end of the QP20W is clamped,thus allowing the excitation to be applied with the motion of the shaker.When the shaker moves,the QP20W will vibrate at a frequency and amplitude.In real applications,it is possible to modify the vibrating structure to have a specific frequency and amplitude.We use commercially available supercapacitors typed EDLC/NF from Panasonic Inc.They have a maximum voltage rating of5.5V/cell and a capacitance of0.47F. They are stacked coin typed with a diameter of21.5mmand a height of8.0mm.The rechargeable batteries used are a110mAh NiMH battery from EPT Battery Tech. Co.,Ltd with dimensions:diameter of14.5mm,height of50.5mm,and a190mAh lithium ion polymer battery from Plantronics Co.with area of20mmÂ35mm and thickness of 4.0mm,as shown in Figure6(c). The experimental conditions are given in Table 3. The reference voltages of NiMH and lithiumExperimental setup (a)(b)(c)QP20W quick pack Supercapacitor, NiMH and Lithium Piezoelectric elementShakerAC/DC rectifierEnergy storage deviceFigure6.Experimental setup and key components.Table3.Experimental conditions.Frequency (Hz)CapacitanceC p(nF)Open circuitvoltageV oc(V)ReferencevoltageÆmaximumvoltage variationV0Æ"V max(V)6038.024.00Supercapacitor:3.60Æ0.0517.50NiMH:0.88Æ0.0212.15Lithium:3.21Æ0.048.606.63Characteristics of Energy Storage Devices677。