求解动态无功优化问题的混合免疫遗传算法

无功优化是电力系统运行中提高经济性和电压安全性的重要措施,为防止静态无功优化可能导致无功控制设备的频繁操作,考虑并联电容器投切组数和有载调压变压器变比档位的调节次数约束,建立了电力系统动态无功优化模型。提出免疫遗传算法与非线性内点法相结合的混合算法进行求解,其中免疫遗传算法处理离散变量,非线性内点法处理连续变量,并在免疫遗传算法中设计独特的编码方式,使抗体能够自动满足动态约束。采用IEEE14系统的24时段无功优化问题进行仿真计算,动态无功优化后离散控制设备的调节次数很少,有功损耗比静态优化结果仅有轻微增加,算例结果验证了混合免疫算法的有效性。

Hybrid immune genetic algorithm for dynamic optimal reactive power flow

Reactive power optimization of power system is an important control method to ensure power system operation securely and economically.To avoid excessive adjustments of capacitor banks and transformer tap ratios,the dynamic reactive power optimization problem with time-related constraints consideration is was formulated.A hybrid method combines immune genetic algorithm and nonlinear interior point method is was proposed to solve this problem.The immune genetic algorithm deals with discrete variables and the nonlinear interior point method deals with continuous variables.The encoding of antibodies in immune genetic algorithm is specially designed to satisfy the time-related constraints.Numerical simulation has beenwas applied to IEEE 14 bus system over a 24hrs period.Compared with static reactive power optimization,the adjustments of discrete equipments obtained by dynamic reactive power optimization are few,and the active power loss obtained by dynamic reactive optimization is a little greater.The results verify the validity of the proposed method.