大停电后电力系统恢复优化的模型与方法
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摘要
随着社会的发展,人们对电力的依赖程度越来越大,这就要求电网需要有较高的供电可靠性。随着电力系统特别是高压与超高压电网的发展,系统规模不断增大,由于电网结构不合理、运行管理不当、继电保护及安全自动装置误动、拒动,不可抗外力等各种原因,发生电力系统事故甚至大面积停电的可能性不可忽视。尽管各电力系统都在不断采取各种有效措施提高系统的安全运行水平,但国内外近年发生的电力系统大面积停电事故仍不乏其例。鉴于发生大面积或停电的潜在可能性、危害性,深入地、系统地研究电力系统大面积停电后的恢复问题,对确保发生事故后能安全、快速地恢复供电,减少停电损失,具有十分重要的理论和实际意义。目前,国内外开始对在线的自适应恢复优化方法方面作了一些研究,但仍有很多重要问题没有得到很好的解决。
在此背景下,本论文对大停电后电力系统恢复过程的优化方法进行了比较系统深入的研究,结合电力系统恢复的各个阶段主要目标,发展了电力系统恢复三个不同阶段恢复方案的优化方法,取得了一定的成果:
1)在黑启动决策中,现有的决策方法尚不能合理融合定性和定量指标,也没有同时考虑指标之间的关联性以及模糊性。因此,采用了Vague值表示黑启动方案评价指标值,可以对其进行比较和综合;引入了Vague值模糊测度来描述评价指标之间的关联性。在此基础上,提出了基于非可加测度理论的黑启动决策方法。与现有方法相比,所提出的方法能够处理黑启动方案评价指标之间的关联性,且能合理地处理黑启动决策中的模糊信息。
2)电力系统大停电后的网架重构是一个多目标、多变量的组合优化问题。本文发展了计及恢复操作时间不确定性的网架重构方案优化的机会约束规划模型。该模型以恢复的发电节点数和负荷恢复收益作为节点收益,计及了恢复操作时间的不确定性,搜索网架重构过程中收益最大的网架重构方案。之后,针对网架重构问题的特点,提出了一种改进遗传算法求解方法。
3)大停电后电力系统负荷恢复阶段的主要内容是全面、快速地恢复负荷。通常,此阶段系统中有大量的节点负荷需要负荷,但系统的发电能力尚未完成恢复,需要分阶段优化选择所要恢复的目标负荷。针对问题中优化变量较多,采用基于角度调制的DE算法对问题进行求解;提出参考节点虚拟功率偏差的概念,对负荷恢复方案的进行频率约束的验证,减少了动态潮流计算量,提高了问题的求解效率。
With the rapid increase of power demand in recent years, the reliability of power supply has becoming more and more important. Nowadays, the development of the power system especially the high-voltage or extra high-voltage network, the scale of the system has been rapidly increasing. Despite of the implementation of various effective measurements for increasing the power system security, the possibility of the occurrence of power system contingency or even large-area power outage still exist due to many reasons, such as structure imperfection, malfunctions of protective relays and circuit breakers, natural calamities. In recent years, several impressive events of large-area power outage have taken place to the power system in many countries. Therefore, it is of great importance to lucubrate the optimization of power system restoration after blackouts for ensuring the rapid and safe restoration of power supply and reducing the economic losses. Though the adaptive methods of the optimization of power system restoration have been studied in many available references, many progresses still need to be made.
Given this background, the method of the optimization of power system restoration is studied in this thesis. With the various objectives of the three stages during power system restoration process taken into account, some significant research results are obtained as follows:
1) Determining the optimal black-start strategy has significant impacts on the speed of power system restoration after a blackout. In the existing black-start decision-making methods, the qualitative and quantitative indexes cannot be well synthesized, and the relevance among the indexes cannot be taken into account. Given this background, the Vague set is first employed in this work to represent the indexes for facilitating the comparisons among them. Then, the Vague value measure is presented, and a mathematical model for black-start decision-making developed. Comparing with the existing methods, the developed method could deal with the relevance among the indexes and more reasonably represent the fuzzy information.
2) The network reconfiguration during power system restoration after blackouts usually takes a long and complex procedure. To address the uncertainties in the restoration steps and time involved, a CCP (Chance Constrained Programming) based method for network reconfiguration scheme optimization is proposed in this paper. The proposed method can generate the best restoration sequence to maximize the benefit of the reconfiguration scheme by taking in to account the number of restarted generators-nodes and the income from restored restored-nodes accordingly. The Genetic Algorithm (GA) is employed to solve for the optimal solution subject to special requirements of the network reconfiguration operation.
3) The third stage of power system restoration is load restoration stage, in which the main objective is to restore as many loads as possible. Generally speaking, during load restoration stage, a large amount of buses and loads has to be restored, but the power supply is not completely restored yet, so the amount of buses and loads to be restored at a time has to be decided by the dispatchers. To optimizing the election of buses and loads to be restored, the concept of virtual power violation of reference bus is used to examine the constraint of maximum frequency violation. The Differential Evolution algorithm based on signal modulation theory is employed for the optimal solution subject to special requirements of the load restoration.
在此背景下,本论文对大停电后电力系统恢复过程的优化方法进行了比较系统深入的研究,结合电力系统恢复的各个阶段主要目标,发展了电力系统恢复三个不同阶段恢复方案的优化方法,取得了一定的成果:
1)在黑启动决策中,现有的决策方法尚不能合理融合定性和定量指标,也没有同时考虑指标之间的关联性以及模糊性。因此,采用了Vague值表示黑启动方案评价指标值,可以对其进行比较和综合;引入了Vague值模糊测度来描述评价指标之间的关联性。在此基础上,提出了基于非可加测度理论的黑启动决策方法。与现有方法相比,所提出的方法能够处理黑启动方案评价指标之间的关联性,且能合理地处理黑启动决策中的模糊信息。
2)电力系统大停电后的网架重构是一个多目标、多变量的组合优化问题。本文发展了计及恢复操作时间不确定性的网架重构方案优化的机会约束规划模型。该模型以恢复的发电节点数和负荷恢复收益作为节点收益,计及了恢复操作时间的不确定性,搜索网架重构过程中收益最大的网架重构方案。之后,针对网架重构问题的特点,提出了一种改进遗传算法求解方法。
3)大停电后电力系统负荷恢复阶段的主要内容是全面、快速地恢复负荷。通常,此阶段系统中有大量的节点负荷需要负荷,但系统的发电能力尚未完成恢复,需要分阶段优化选择所要恢复的目标负荷。针对问题中优化变量较多,采用基于角度调制的DE算法对问题进行求解;提出参考节点虚拟功率偏差的概念,对负荷恢复方案的进行频率约束的验证,减少了动态潮流计算量,提高了问题的求解效率。
With the rapid increase of power demand in recent years, the reliability of power supply has becoming more and more important. Nowadays, the development of the power system especially the high-voltage or extra high-voltage network, the scale of the system has been rapidly increasing. Despite of the implementation of various effective measurements for increasing the power system security, the possibility of the occurrence of power system contingency or even large-area power outage still exist due to many reasons, such as structure imperfection, malfunctions of protective relays and circuit breakers, natural calamities. In recent years, several impressive events of large-area power outage have taken place to the power system in many countries. Therefore, it is of great importance to lucubrate the optimization of power system restoration after blackouts for ensuring the rapid and safe restoration of power supply and reducing the economic losses. Though the adaptive methods of the optimization of power system restoration have been studied in many available references, many progresses still need to be made.
Given this background, the method of the optimization of power system restoration is studied in this thesis. With the various objectives of the three stages during power system restoration process taken into account, some significant research results are obtained as follows:
1) Determining the optimal black-start strategy has significant impacts on the speed of power system restoration after a blackout. In the existing black-start decision-making methods, the qualitative and quantitative indexes cannot be well synthesized, and the relevance among the indexes cannot be taken into account. Given this background, the Vague set is first employed in this work to represent the indexes for facilitating the comparisons among them. Then, the Vague value measure is presented, and a mathematical model for black-start decision-making developed. Comparing with the existing methods, the developed method could deal with the relevance among the indexes and more reasonably represent the fuzzy information.
2) The network reconfiguration during power system restoration after blackouts usually takes a long and complex procedure. To address the uncertainties in the restoration steps and time involved, a CCP (Chance Constrained Programming) based method for network reconfiguration scheme optimization is proposed in this paper. The proposed method can generate the best restoration sequence to maximize the benefit of the reconfiguration scheme by taking in to account the number of restarted generators-nodes and the income from restored restored-nodes accordingly. The Genetic Algorithm (GA) is employed to solve for the optimal solution subject to special requirements of the network reconfiguration operation.
3) The third stage of power system restoration is load restoration stage, in which the main objective is to restore as many loads as possible. Generally speaking, during load restoration stage, a large amount of buses and loads has to be restored, but the power supply is not completely restored yet, so the amount of buses and loads to be restored at a time has to be decided by the dispatchers. To optimizing the election of buses and loads to be restored, the concept of virtual power violation of reference bus is used to examine the constraint of maximum frequency violation. The Differential Evolution algorithm based on signal modulation theory is employed for the optimal solution subject to special requirements of the load restoration.
引文
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