基于粒计算地风电并网电力系统备用容量优化
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首先研究了国内外风电的发展现状以及风电并网对系统可靠性和备用 容量的影响，在此基础上研究基于时间序列分析方法的风速预测模型和威 布尔分布模型，对风电场的风速进行模拟，为风电并入电网对电力系统可 靠性影响的研究奠定基础。
其次，重点研究了风电场并网对电力系统可靠性的影响，采用非序贯 蒙特卡洛模拟法对包含风电场的电力系统进行可靠性评估。
最后，本文提出结合粒计算思想方法和理论的多种群遗传算法，该方 法通过将解空间进行粒度划分，把优化的属性体现出来，并淘汰劣势的粒 空间，使求解问题的搜索空间大大减少，实现快速优化。随后对风电接入 的电力系统备用容量进行优化，通过对可靠性系统的仿真分析，验证了本 文所提结合粒计算的多种群遗传算法的有效性。 关键词：风电并网；可靠性评估；多种群遗传算法；粒计算；备用容量优
Firstly, this paper studied the current development of wind power at home and abroad, as well as influence on system reliability and reserve capacity. Based on studies of time series method, a wind forecasting model was used to simulate wind farms and lay the foundation to research on the impact on the
化
源自文库II
RESERVE CAPACITY OPTIMIZATION BASED ON GRANULAR COMPUTING UNDER WIND POWER
INTEGRATED
ABSTRACT
With large-scale wind power integrated, it makes difficult to control the uncontrollable power grid operation, such as power quality deterioration, uneven distribution of power flow, overload power lines and difficulties in adjusting to power scheduling and so on. These issues seriously affect the stability of power system. In addition, changes of the distribution of reserve capacity influence reliability of the system. Therefore, reserve capacity optimization is an important means to improve the system to accept more wind power and mitigate the adverse effects, and can improve reliability and make full use of resources and energy supply. It’s a multi-objective problem. Therefore, the conventional algorithm for solving such problem would not applicable. Starting from wind power integrated will influence to power system reliability, this paper studies granular computing combined with multiple population genetic algorithm, to optimizate reserve capacity contained wind farms under a given reliability level.
III
power system reliability. Secondly, the paper focused on the impact of wind farms and reliability of
the power system, using sequential sequential Monte Carlo method to evaluate reliability of power system containing wind farms.
基于粒计算的风电并网电力系统备用容量优化
摘要
随着大规模风电并网，风电不可控性使得电网运行的控制难度加大， 如电能质量变差、潮流分布不均匀、线路过载且调节困难、给电力调度带 来麻烦等，这些问题严重影响电力系统的稳定运行。此外，系统备用容量 分布的变化关系到系统的可靠性水平。因此，备用容量优化是提高系统对 风电接纳能力和缓解风电并网对电力系统的不利影响的重要手段，并且能 改善系统可靠性水平，达到备用资源的充分利用和电能供给可靠性的统一。 而备用容量的优化和系统可靠性的统一，是一个多目标协调的问题，因此， 采用常规的优化算法将会使得求解过程严重迟缓。本文主要从风电并网对 电力系统可靠性的影响出发，着重研究结合粒计算思想方法和理论的多种 群遗传算法，对风电并网后使得系统达到给定可靠性水平条件下的备用容 量进行优化。
再次，提出了一种基于交互式协调优化的多种群遗传算法，对电力系 统的经济调度问题做了探索。引入精英策略和移民策略的多种群遗传算法，
I
能够实现对多个种群同时进行优化搜索，移民策略通过移民算子实现种群 之间进化过程中的信息交换，而精英策略通过人工选择算子保证进化过程 的最优解。随后通过仿真验算和分析，验证了多种群遗传算法解决电力系 统多目标优化问题的有效性。
其次，重点研究了风电场并网对电力系统可靠性的影响，采用非序贯 蒙特卡洛模拟法对包含风电场的电力系统进行可靠性评估。
最后，本文提出结合粒计算思想方法和理论的多种群遗传算法，该方 法通过将解空间进行粒度划分，把优化的属性体现出来，并淘汰劣势的粒 空间，使求解问题的搜索空间大大减少，实现快速优化。随后对风电接入 的电力系统备用容量进行优化，通过对可靠性系统的仿真分析，验证了本 文所提结合粒计算的多种群遗传算法的有效性。 关键词：风电并网；可靠性评估；多种群遗传算法；粒计算；备用容量优
Firstly, this paper studied the current development of wind power at home and abroad, as well as influence on system reliability and reserve capacity. Based on studies of time series method, a wind forecasting model was used to simulate wind farms and lay the foundation to research on the impact on the
化
源自文库II
RESERVE CAPACITY OPTIMIZATION BASED ON GRANULAR COMPUTING UNDER WIND POWER
INTEGRATED
ABSTRACT
With large-scale wind power integrated, it makes difficult to control the uncontrollable power grid operation, such as power quality deterioration, uneven distribution of power flow, overload power lines and difficulties in adjusting to power scheduling and so on. These issues seriously affect the stability of power system. In addition, changes of the distribution of reserve capacity influence reliability of the system. Therefore, reserve capacity optimization is an important means to improve the system to accept more wind power and mitigate the adverse effects, and can improve reliability and make full use of resources and energy supply. It’s a multi-objective problem. Therefore, the conventional algorithm for solving such problem would not applicable. Starting from wind power integrated will influence to power system reliability, this paper studies granular computing combined with multiple population genetic algorithm, to optimizate reserve capacity contained wind farms under a given reliability level.
III
power system reliability. Secondly, the paper focused on the impact of wind farms and reliability of
the power system, using sequential sequential Monte Carlo method to evaluate reliability of power system containing wind farms.
基于粒计算的风电并网电力系统备用容量优化
摘要
随着大规模风电并网，风电不可控性使得电网运行的控制难度加大， 如电能质量变差、潮流分布不均匀、线路过载且调节困难、给电力调度带 来麻烦等，这些问题严重影响电力系统的稳定运行。此外，系统备用容量 分布的变化关系到系统的可靠性水平。因此，备用容量优化是提高系统对 风电接纳能力和缓解风电并网对电力系统的不利影响的重要手段，并且能 改善系统可靠性水平，达到备用资源的充分利用和电能供给可靠性的统一。 而备用容量的优化和系统可靠性的统一，是一个多目标协调的问题，因此， 采用常规的优化算法将会使得求解过程严重迟缓。本文主要从风电并网对 电力系统可靠性的影响出发，着重研究结合粒计算思想方法和理论的多种 群遗传算法，对风电并网后使得系统达到给定可靠性水平条件下的备用容 量进行优化。
再次，提出了一种基于交互式协调优化的多种群遗传算法，对电力系 统的经济调度问题做了探索。引入精英策略和移民策略的多种群遗传算法，
I
能够实现对多个种群同时进行优化搜索，移民策略通过移民算子实现种群 之间进化过程中的信息交换，而精英策略通过人工选择算子保证进化过程 的最优解。随后通过仿真验算和分析，验证了多种群遗传算法解决电力系 统多目标优化问题的有效性。