Reactive power optimization of distribution network including photovoltaic power and SVG considering harmonic factors

In the operation of grid-connected photovoltaic power stations, a large amount of harmonic current is injected into distribution network, which reduces the power quality of distribution network. In the paper, the Static Var Generator (SVG) is added to the outlet of the photovoltaic power station, by using the feedforward control strategy for the voltage, SVG can effectively suppress the harmonic current generated by photovoltaic power plants. When the active power output of the PV power station and reactive power of SVG output change, the harmonic current of the grid with SVG and photovoltaic power will change accordingly. The harmonic current model with SVG and photovoltaic power is established based on BP neural network, which can calculate the harmonic current of both SVG and PV. In allusion to the impacts on the distribution network resulting from the grid harmonic current of SVG and PV and the uncertainty of the reactive power optimization, the harmonic index (Total Harmonic Distortion of Voltage, THD U ) is added to the traditional reactive power optimization model based on the established harmonic current model including SVG and photovoltaic power. The chance constrained of the fundamental harmonic voltage and the total harmonic distortion of voltage is analyzed, and the reactive power optimization model of distribution network including the photovoltaic power station and SVG considering harmonic factors is established. In the paper, Particle Swarm Optimization (PSO) is applied to solve the reactive power optimization model and results of IEEE-33 test system case verifies the rationality and feasibility of the model established in the paper. The model can comprehensively reduce the active power loss and the harmonic pollution so as to improve the economy and security of the operation of distribution network.