MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH FOR DISTRIBUTION NETWORK CONSIDERING PV GENERATION UNCERTAINTY

In recent years, as the installed capacity of distributed generation (DG) and the penetration level continue to increase, the uncertainties of the DGs like photovoltaic (PV) generation bring new problems and challenges to the reactive power and voltage control in distribution systems. In this paper, a multi-objective optimal reactive power (VAR) dispatch model for distribution network considering PV generation uncertainty is established, aiming at minimizing the active power loss and minimizing the voltage deviation. Regarding the uncertainty of PV power output, a truncated double Gaussian mixture model is applied to construct the probability density function of solar irradiance, and the copula theory is utilized to describe the PV power spatial dependence between multiple PV stations. In addition, a scenario analysis method with an improved K-means scenario reduction technique is applied to obtain the typical scenarios considering PV power spatial dependence. To solve the complicated optimization model, a multi-objective particle swarm optimization (PSO) algorithm is applied to obtain the Pareto front, and the fuzzy set theory is employed to determine the compromise solutions. Finally, the corresponding simulations are performed on the IEEE 33-bus test system to demonstrate the validity and effectiveness of the proposed optimization model.