Power Flow for Distribution Network with Renewable Energy Sources

Abstract

The power flow techniques are of great importance for the modern distribution network expansion planning due to the increasing uncertainty. In this study, a probabilistic power flow is proposed in order to incorporate long-term uncertainty sources which are load demand, wind speed, and solar irradiance. A convolution-based power flow is constructed by using the matrices of the bus-injection to branch-current and branch-current to bus-voltage. Its results are compared with that of full AC power flow in terms of the accuracy. The results of bus voltages and current flows are obtained for radial 21 bus benchmark system and the obtained results show that the uncertainty related to renewable generation and load are incorporated into power flow problem effectively in terms of accuracy and required simulation time.