Reactive power optimization control strategy for large-scale new energy access grid based on optimized particle swarm algorithm

Abstract

Large scale new energy sources has high relativity to the distribution network, which will affect grid reactive power operation. Reactive power optimization can effectively improve power quality and system operation's safety, reliability and economy. Firstly, according to the characteristics of the new energy cluster where the isolated grid is connected to the flexible DC grid, a multi-objective imaginary power optimization model is builded that comprehensively includes system power cost and the new energy's reactive power margin cluster. Among them, to maximize the reactive power margin of the new energy cluster can effectively perfect the velocity of network restraint, and realize the pre-regulate of the fixity of transient voltage for the distributed energy cluster. Then, changing multi-objective into a single- objective optimization model by weighting method, and the particle swarm algorithm is used to solve it. Finally, through simulation verification, it is distinct that the proposed imaginary power optimization way can not only effectively reduce the system network loss, but also significantly enhance the imaginary power range of the distributed energy cluster, that can improve the system voltage.