基于无迹变换含“风光”系统无功优化研究

Research on reactive power optimization based on "wind-photovoltaic" system with unscented Transformation

由于分布式电源并网的随机性,给电网无功优化引入新的问题。本文通过无迹变换近似风电场风速、光伏电站的光照强度和负荷的有功功率的概率分布,然后,搭建考虑有功损耗、电压偏移量和优化成本的多目标无功优化模型,随后,在求解模型中将迁移算子、Hooke-Jeeves模式搜索、启发式交叉策略引入到粒子群算法中,改进了粒子群算法早熟、陷于局部最优的问题。最后,本文用IEEE-33节点的配电系统验证了本文所提算法结果损失较小误差的情况下收敛时间缩短近十倍的优势以及相比传统TPSO算法优化本模型综合结果均更优的特点。

Due to the randomness of the distributed power grid,a new problem is introduced to the reactive power optimization of the power grid. In this paper,the probability distribution of the active power of the wind speed,the light intensity and the load of the photovoltaic power station is approximated by the unscented transform,then,a multi-objective reactive power optimization model considering the active loss,the voltage offset and the optimization cost is built,subsequently,in the solution model, migration operator,Hooke- Jeeves mode and heuristic crossover strategy are introduced into particle swarm optimization,which improves the problem of premature and partial optimization. Finally,IEEE- 33 nodes system is used to verify that the convergence time of the proposed algorithm is nearly ten times shorter than traditional algorithm and better results of TPSO algorithm.