| 引用本文: | 刘庆珍,黄君莹,王少芳.复合电压薄弱性指标及以其为导向的无功优化策略[J].电力自动化设备,2024,44(1):147-152,159. |
| LIU Qingzhen,HUANG Junying,WANG Shaofang.Compounding voltage weakness indicator and reactive power optimization strategy oriented to it[J].Electric Power Automation Equipment,2024,44(1):147-152,159. |
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| 摘要: |
| 提出了一种新的电力系统薄弱环节确定指标，并提出以系统薄弱环节分析为导向的多目标函数无功优化方法。首先，融合薄弱性指标电压和功率两方面的特点和优势，定义了新的薄弱环节复合裕度判定指标，综合描述负荷正常工作点与电压崩溃点的距离；以该指标为判定标准识别出系统的电压薄弱环节点集，由此点集构成无功优化的待补偿节点集。然后，建立多目标无功优化模型，采用改进自适应遗传算法，在算法选择环节采用确定式选择原则替换传统轮盘赌法，进而完成多目标无功优化模型求解。最后，以IEEE 30节点系统和新英格兰IEEE 39节点系统为仿真试验案例，通过优化后多项系统运行指标与传统方法计算结果的对比，验证了以新的薄弱环节判定指标为无功优化策略的有效性和优越性，同时也证明了改进后的自适应遗传算法在多目标无功优化计算中的高效性。 |
| 关键词: 薄弱环节 复合裕度指标 多目标无功优化 自适应遗传算法 确定式选择原则 |
| DOI：10.16081/j.epae.202303004 |
| 分类号:TM761 |
| 基金项目:国家自然科学基金资助项目(51807030) |
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| Compounding voltage weakness indicator and reactive power optimization strategy oriented to it |
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LIU Qingzhen1, HUANG Junying1, WANG Shaofang2
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1.Fujian Key Laboratory of New Energy Generation and Power Conversion, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China;2.China Electric Power Research Institute Co.,Ltd.,Beijing 100192, China
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| Abstract: |
| A new weak link determination indicator of power system is proposed and a multi-objective function reactive power optimization method oriented to system weak link analysis is proposed. The characteristics and advantages of both voltage and power aspects of the weakness indicator are fused. A new weak link compounding margin determination indicator is defined, which comprehensively describes the distance between the load normal operating point and the voltage collapse point. This indicator can be used as the determination criterion to identify the voltage weak link point set of system, which constitutes the set of nodes to be compensated for reactive power optimization. A multi-objective reactive power optimization model is established, and an improved adaptive genetic algorithm is used to replace the traditional roulette wheel method with deterministic selection principle in the algorithm selection process, and then the multi-objective reactive power optimization model is solved. Taking the IEEE 30-bus system and the New England IEEE 39-bus system as simulative testing cases, by comparing several system operation indicators and the calculative results of traditional method, the efficiency and superiority of reactive power optimization strategy according to the new weak link determination indicator is verified, as well as the high efficiency of the improved adaptive genetic algorithm in the multi-objective reactive power optimization calculation is verified. |
| Key words: weak links compounding margin indicator multi-objective reactive power optimization adaptive genetic algorithm deterministic selection principle |
