| 引用本文: | 刘文丽,张 涛,杨晓雷,陶 欢.计及负荷随机性含风电电力系统TCSC多目标优化配置[J].电力系统保护与控制,2023,51(5):58-69.[点击复制] |
| LIU Wenli,ZHANG Tao,YANG Xiaolei,TAO Huan.Multi-objective optimal allocation of TCSC for a power system for windpower and load randomness[J].Power System Protection and Control,2023,51(5):58-69[点击复制] |
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| 摘要: |
| 实现可用输电能力和电压稳定的双重改善，提出一种考虑风电和负荷随机性的灵活交流输电系统(flexible AC transmission system, FACTS)多目标优化配置方法。首先推导基于拉丁超立方、k-means聚类和蒙特卡洛抽样三者相结合的系统场景生成技术。然后以区域间可用输电能力和电压稳定指标L为目标，建立晶闸管控制串联电容器(thyristor-controlled series capacitor, TCSC)多目标优化配置模型。最后通过增加混沌初始化和变惯性权重设置改进多目标粒子群算法以求解所建模型。基于改进的IEEE30节点系统，对比了最可能发生的系统场景配置TCSC前后的非劣解集和模糊最优解，分析了极端系统场景配置TCSC前后的优化结果。仿真结果表明，所提场景处理方法、多目标优化模型和改进算法在解决相关问题上具有有效性。 |
| 关键词: 风电 负荷随机性 场景 TCSC 可用输电能力 电压稳定指标L |
| DOI：10.19783/j.cnki.pspc.220615 |
| 投稿时间：2022-04-28修订日期：2022-07-05 |
| 基金项目:国家自然科学基金项目资助(52007103)；国网浙江省电力有限公司科技项目资助(5211JX1900CX) |
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| Multi-objective optimal allocation of TCSC for a power system for windpower and load randomness |
| LIU Wenli1,ZHANG Tao1,YANG Xiaolei2,TAO Huan2 |
| (1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China;
2. State Grid Jiaxing Power Supply Company, Jiaxing 314033, China) |
| Abstract: |
| To gain improvement in both available transmission capacity (ATC) and voltage stability, a flexible AC transmission system (FACTS) multi-objective optimization allocation method considering wind power and load randomness is proposed. First, based on the combination of Latin hypercube, k-means clustering and Monte Carlo sampling, a method for generating system scenarios is proposed. Then, a thyristor-controlled series capacitor (TCSC) multi-objective optimal allocation model with ATC and voltage stability L indicator as objective functions is established. Finally, the multi-objective particle swarm algorithm (MOPSO) is improved by adding chaos initialization and variable inertia weight setting to analyze the model. Based on a modified IEEE30 node system, the non-inferior solutions and fuzzy optimal solutions before and after TCSC allocation of the system scenario with the greatest occurrence probability are compared. The optimization results before and after TCSC allocation of the extreme system scenario are analyzed. The simulation results show that the proposed scenario processing method, the multi-objective optimization model and the improved algorithm are effective in solving related problems.
This work is supported by the National Natural Science Foundation of China (No. 52007103). |
| Key words: wind power load randomness scenario TCSC ATC voltage stability indicator L |
