基于组合算法的在线无功优化及策略

为解决无功优化问题,构造出一种实用的目标函数,提出一种基于设备优先级的组合算法。该算法结合了非线性原对偶内点法收敛快的特性和改进遗传算法处理离散变量的优点,提高了算法的全局收敛能力和收敛速度。利用短期负荷预报,对未来24h系统负荷进行分段并确定负荷水平,以此来确定无功补偿控制设备动作的优先级。在线无功电压控制系统采用控制设备优先级策略和组合算法的协调策略后,实现了控制设备的合理动作。仿真结果和实际电网的运行情况表明,基于设备优先级的组合算法能够合理控制设备动作,提高电网的电压合格率,降低电网损耗。

Study on reactive power optimization and its strategy based on a combined algorithm

A practical objective function on the problem of reactive optimization was constructed, and a combined algorithm, which associates the fact convergence character of interior point algorithm and the merit of advanced genetic algorithm, was proposed to improve the convergence speed as well as the ability of global convergence. The combined algorithm uses short-term load forecasting and divides the future day's load into several parts to determine the load level, all above will determine the priority of reactive power control devices. On-line Vol/Var control system combines the priority policy of control devices and the coordinate policy of combined algorithm to make sure the control devices acting properly. The results of simulation and the practical operation in power system show that the algorithm can control devices' action properly and improve voltage acceptance rate and reduce the active power loss.