考虑模糊机会约束处理源荷两侧不确定性的配电网无功优化策略

A reactive power optimization strategy for distribution networks considering fuzzy chance constraints to deal with uncertainties on both sides of source-load

随着可再生能源的迅速发展,可再生能源作为分布式能源接入配电网的容量逐渐增大。由于出力的随机性给配电网带来网损增加、电压波动等问题,影响配电网系统的安全经济运行。为此,应充分考虑分布式电源出力和负荷功率的不确定性,构建以网损和电压偏移最小为目标的无功优化模型,利用模糊机会约束处理不确定性问题,最后采用改进粒子群算法对模型进行求解。通过改进的IEEE-33系统进行分析,验证所提策略的有效性,结果表明模糊处理随机性后采用改进粒子群算法求解有利于减小系统的网损,提高系统的稳定性。

With the rapid development of renewable energy sources,the capacity of renewable energy sources as distributed energy sources connected to the distribution network gradually increases,which will affect the safe and economic operation of the distribution network system due to the randomness of its power output to bring problems such as network loss increase and voltage fluctuation.For this reason,the uncertainty of distributed power supply output and load power should be fully considered,a reactive power optimization model with the objective of minimizing network loss and voltage shift should be constructed,the uncertainty problem should be handled by using fuzzy chance constraints,and finally the model should be solved by improved particle swarm algorithm.The analysis is carried out by the improved IEEE-33 system to verify the effectiveness of the proposed strategy.The results show that the solution by the improved particle swarm algorithm after fuzzy treatment of randomness is beneficial to reduce the network loss of the system and improve the stability of the system.