首页> 外文会议>Intelligent System Applications to Power Systems, 2009. ISAP '09 >Reactive Power Planning Using a Two-Level Optimizer Based on Multi-Objective Algorithms
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Reactive Power Planning Using a Two-Level Optimizer Based on Multi-Objective Algorithms

机译:基于多目标算法的两级优化器无功规划

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Reactive Power Planning (RPP) is proposed here as a three-objective optimization: reactive compensation investment, system loss, and the active power stability margin after critical contingencies. A two-level optimizer with Improved Non-dominated Sorting Genetic Algorithm (NSGAII) and Interior Point Algorithm is proposed to obtain the Pareto front of RPP. NSGAII performs optimization in the planning stage to find the optimal compensation scheme (locations and sizes of VAR devices). According to the compensation scheme, operation-oriented stage adjusts the output of the VAR devices to optimize the economic aspect (system loss) and security (post-contingency stability margin). A simulation was conducted on New England 39-bus system and a three dimensional Pareto front was obtained, showing the decrease of system loss and the increase of stability margin with gradual addition of VAR support. Solutions under different compensation level are given, among which suitable solutions can be selected for RPP.
机译:在此提出无功功率规划(RPP)作为三目标优化:无功补偿投资,系统损耗和关键突发事件后的有功功率稳定裕度。提出了一种采用改进的非支配排序遗传算法(NSGAII)和内点算法的二级优化器,以获取RPP的Pareto前沿。 NSGAII在计划阶段进行优化,以找到最佳补偿方案(VAR设备的位置和大小)。根据补偿方案,面向操作的阶段会调整VAR设备的输出,以优化经济方面(系统损失)和安全性(应急后稳定余量)。在新英格兰39总线系统上进行了仿真,并获得了三维帕累托前沿,表明随着逐渐增加VAR支持,系统损失减少了,稳定裕度增加了。给出了不同补偿水平下的解,其中可以为RPP选择合适的解。

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