Mitigation of PV Power Fluctuations using Moving Average Control in an OpenDSS-Python Environment

Abstract

Several technical challenges are presented with the integration of photovoltaic systems into electrical grids, being output power variability due to transient clouds one the most significant issues. In this paper is tested a variability smoothing approach for a grid-integrated multi-megawatt installation which comprises a photovoltaic system and a battery energy storage system. The approach consists of two algorithms: moving average control, which uses a fixed window size to estimate a smooth power curve; and state of charge control, which aims to preserve the storage flexibility and the state of charge close to a reference value. Simulations performed in an OpenDSS-Python environment, using the IEEE 123 Node Test Feeder, demonstrate the effectiveness of the approach and its suitability for impact alleviation of photovoltaic power integration into distribution networks.