基于遗传算法的变电站电压无功综合控制

采用常规方法进行变电站电压无功控制时 ,往往使二次侧电压过于接近边界而导致系统承受负荷波动的能力大大下降 ,成为系统安全运行的隐患。该文在负荷预测的基础上把遗传算法应用于变电站电压无功控制 ,使主变中流过的无功功率及主变二次侧电压偏移最小。首先建立无功电压控制的求解模型 ,针对其计算空间过大的特点 ,引入遗传算法在全局范围内求最优解。对实例计算结果表明 ,所提算法较传统方法能更有效地搜索到最优控制策略 ,并使二次侧电压合格裕度有较大增加

Reactive power/voltage control in the substation based on GA

Reactive power/volt control in a substation using general approach usually results in the volt in the secondary side on being too close to the boundary. It will make the ability of enduring the variation of load in a system decrease a lot and become the threat of the system. Based on the short term load forecast, this article firstly uses genetic algorithm to calculate the optimal control schedule in a substation. The purpose is minimizing the reactive power through the transformer and the deviation of the secondary bus voltage. It constructs a model of the reactive power and volt control problem firstly and uses genetic algorithm to calculate the optimal control. An instance indicates that the proposed approach can find the optimal control more effectively than general approach and make the margin of appropriate volt in the second side increase much.