Effective load carrying capability evaluation for high penetration renewable energy integration

Effective Load Carrying Capability Evaluation for High Penetration Renewable Energy Integration
Zhi Chen
Department of Electrical Engineering Arkansas Tech University Russellville, Arkansas USA zchen3@
Abstract— This paper proposes an Approximate Dynamic Programming (ADP) based approach to evaluate the effective load carrying capability (ELCC) of high penetration renewable resources by solving the long-term security-constrained unit commitment (SCUC) problem with various uncertainties related to solar radiation, wind speed, and load level. Compared with traditional approaches, the proposed approach can assist Independent System Operator (ISO) to make the decision on the basis of current day information only, hence it can reduce the computation burden from future states forecasting. The objective of the proposed long-term SCUC formulation is to minimize the operation cost for the base case with forecast values while considering variable cost from uncertainties. Numerical case studies on a 6-bus system illustrate the effectiveness of the proposed ADP based long-term SCUC model for the investigation of ELCC under various uncertainties. Index Terms-- Effective load carrying capability, approximate dynamic programming, renewable resource integration, power system reliability.
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978-1-4673-8040-9/15/$31.00 ©2015 IEEE
power generation, solar power generation, and hourly load demand are simulated via Monte Carlo simulation with various probability distributions. Instead of focusing on various scenarios in terms of the huge scenario tree as discussed in most hourly based SCUC in literature, the proposed ADP solution decomposes long-term SCUC model into sub-problems which are then solved iteratively with reduced computation burden. Uncertainties are simulated via MC and results of subproblems are feedback to the master process for further iterations to satisfy the convergence criterion. The major contribution of the paper is to develop an adaptive long-term SCUC model that could effectively address the ELCC of renewable energy and economic operation of power systems under various uncertainties in low carbon power system planning. The rest of the paper is organized as follows. An ADP approach is introduced in Section II for investigating the effective load carry capability of renewable generations via stochastic long-term SCUC. Numerical study and a set of sensitivity analyses are presented in Sections III. The conclusion drawn from the analysis is provided in Section IV. II. A. MODELING DESC i ,t Pi ,t
Commitment of unit i at time t Power dispatch of unit i at time t
PLS ,b ,t Load shedding at bus b at time t .
Vdn,t
n Pd ,t
Value function approximation Slope of Value function approximation I. INTRODUCTION
The increasing concern on environmental in electricity section brings significant renewable resource implementation. Since wind and solar radiation are plentiful and work environmentally across the world, wind turbines and photovoltaic panels are specifically installed and distributed rapidly as compared to other renewables, e.g., hydro and wave source. In the meanwhile, the integration of renewable energy into power grid is still facing hard circumstances because they introduce multiply uncertainties. Thus, the effective load
Lei Wu Department of Electrical and Computer Engineering
Clarkson University Potsdam, New York USA lwu@ carrying capability (ELCC) of candidate renewable energy is necessary to be measured in long-term generation planning. After that, ISOs can deal with new challenges from intermittent sources to operate the system efficiently while maintaining the system reliability with the information of ELCC for new installed renewable sources. Effective load carrying capability represents the amount of extra load that can be supplied in the system at the same reliability level due to the installation of the new generation unit [1]. It is a long-established value for conventional power plants [1]. Over recent years, similar values have been calculated for wind power [2] and solar power [3]. More specialized analyses considers, for example, system reliability in the optimization of future generation portfolios [4]. Thus, the calculation of ELCC becomes the significant part in renewable resource integration in power system planning. Rather than [5] investigated ELCC via load duration curve with non-sequence solutions, SCUC can assist ISO to obtain the hourly variation of renewable energy resources during the power system operation horizon. [6] proposed a long-term SCUC, while stochastic programming and Lagrangian relaxation were employed in [7] to solve the long-term SCUC. Although renewable generations have negligible emission, they are not dispatchable by ISO. Operations of are studied and analyzed with uncertainties for variable generations [8-11]. In order to handle a range of different forms of uncertainty, from hourly of wind, solar, and demands, to daily and monthly variations in fuel supply for convention units, the stochastic programming framework is usually used to handle the random condition in optimization problems. Uncertain information in stochastic programming is usually expressed as the scenario tree [7]. The challenge here is that the scale of scenario trees grows exponentially with the increase of time durations under consideration [12]. Solving large-scale model directly is computationally intractable for real world problems. In order to address these computational problems, [13] resorted to approximate dynamic programming (ADP). This technique has recently shown useful approximate solutions for largescale multi-period resource optimization problems [14] [15]. This paper proposes a long-term SCUC optimization model and ADP solution to study the impacts of uncertainties from renewable energy on ELCC. Uncertainties of wind