基于免疫PSO的新能源配电网无功多目标模糊优化

考虑分布式能源的间歇性和随机性对配电网电压的影响，用模糊数表征分布式电源出力不确定性和负荷功率的波动性，构建配电网多目标模糊无功优化模型，提出分布式电源和无功补偿装置输出无功功率的协同优化方法。以有功网损最小和电压偏差最小为目标函数，并将目标函数和约束条件模糊化，根据其隶属度函数形成模糊适应度函数，再将两目标通过最大满意度法转化为单目标，最后利用免疫粒子群算法进行求解，从而确定在负荷功率模糊波动下具有不同模糊出力水平的分布式电源和具有不同运行方式的无功补偿装置输出无功功率的最优值。以IEEE33配电网系统为算例，验证了所提出的模型和算法的可行性和有效性。

Multi-Objective Fuzzy Optimization for Reactive Power of Distribution Network Based on Immune Particle Swarm Optimization Algorithm

Considering the influence of intermittent and randomness of distributed energy on the voltage of distribution network, the fuzzy power is used to characterize the fluctuation of distributed power output and load power. The multi-objective fuzzy and reactive power optimization model of distribution network is proposed in this paper. Besides, the coordinated optimization method is introduced for the output reactive power of distributed generations and reactive power compensation devices. By taking the minimum loss of power network and the smallest voltage deviation as objective function, the objective function and the constraint conditions are fuzzified, and the fuzzy fitness function is formed according to the membership function. Then, the multi-objective optimization problem is transformed into the single objective optimization by the maximum satisfaction method. Finally, the immune particle swarm optimization algorithm is used to determine the optimal value of the output reactive power of the distributed generations with different fuzzy output levels and the reactive power compensation device with different operating modes under fuzzy fluctuations of the load powers. By taking the IEEE33 distribution system as an example, the feasibility and validity of the proposed model and algorithm are verified.