Probabilistic Optimal Power Flow Calculation of AC/DC Hybrid Distribution Network with Photovoltaic Power and Electric Vehicles

Abstract

The AC-DC hybrid distribution network provides DC interfaces for electric vehicle charging stations, photovoltaic power stations, battery storage, and reduces redundant power conversion links and energy loss. The incorporating of the active DC distribution network into AC grid has added complexity into the optimal power flow problem, yet the intermittence of PV output and the randomness of electric vehicles loads lead to a significant increase in the uncertainty and complexity of AC-DC hybrid power system. At present, the study of optimal power flow (OPF) for AC/DC systems containing DC distribution network is still in its infancy and none of them have taken the uncertainties of PV power generation and EV loads into account. This paper firstly establishes the DC grid connected power function for photovoltaic power and electric vehicles by Monte Carlo simulation; secondly the power functions are used to build a probabilistic optimal power flow (POPF) model for an AC/DC hybrid distribution network case consisting of voltage source converters (VSC), DC distribution network and traditional AC network. At last the three-point estimation method (3PEM) using the center distance information of random variables is applied based on existing deterministic optimal power flow algorithm in order to realize the POPF calculation. The results show that the mathematical model and 3PEM used in this paper can take the uncertainties of photovoltaic power generation and electric vehicle load into consideration effectively on the basis of traditional static power flow optimization and the results obtained are of high accuracy and low computational burden. The obtained POPF results reflect more actual operation status of the power grid than static optimal power flow results so it could be used as the planning and operation theoretical basis of AC/DC hybrid distribution network and it could be a useful reference for the further development of electric vehicles.