电力系统时变无功优化算法

Algorithm for Time-varying Reactive Power Optimization

根据电力系统实际运行中负荷不断变化的情况,提出了一种新的电力系统时变无功优化算法。从负荷曲线的特点出发,结合设备的动作次数的约束,提出利用遗传算法进行智能化负荷分段的方法;利用免疫系统的免疫信息处理机制和自动调整动量系数的自适应因子的粒子群算法,从整体上获得系统的最优控制方式。IEEE-30算例分析表明,该方法有效减少了补偿设备和变压器分接头的动作次数,明显降低了系统在一天内的网损。

A new algorithm is proposed in the paper for time-varying reactive power optimization according to the load variation. Considering the characteristics of load curve and the act times of devices, an intellectualized method using genetic algorithm for dividing load curve is presented. The proposed method can acquire the optimal control mode of the whole power system by using the particle swarm optimization method which has a mechanism of immune information management and an adaptive factor with an ability, of adjusting momentum coefficient automatically. Results from IEEE-30 system indicate that the proposed method can effectively reduce the act times of compensatory devices and transformer taps as well as the power loss of the system.