Effect of PV power forecast error on the frequency of a standalone microgrid system

Abstract

The need for solar photovoltaic (PV) power forecasting arises due to rapid fluctuations in solar PV output. This variation can cause an imbalance between the demand and generation in a microgrid. This paper attempts to analyze the impact of inaccuracy in predicting PV power generation on the frequency of a standalone microgrid system. For this purpose, two different forecasting models have been studied for two different types of weather conditions, characterized by varying degrees of cloud cover. Moreover, when addressing frequency fluctuations, restoring them to the nominal value becomes imperative, and this is where secondary controllers play a crucial role. This paper further evaluates and compares the performance of three proportional-integrative derivative (PID) controllers for smoothing frequency control. For the considered combinations of two forecasting models and three secondary controllers, the standard deviation (SD) of frequency is the lowest for the long short-term memory (LSTM) forecaster and Particle Swarm Optimization (PSO) – PID (PSO-PID) controller. The corresponding reduction of SD, after replacing persistence: PSO-PID with LSTM: PSO-PID, in combination with |clear: cloudy| day is |28.43%: 32.12%| for overshoot and |11.87%: 18.36%| for undershoot frequency deviation.