Impact of Forecasting Uncertainty of PV Generation and Electricity Demand on Local Electricity Supply and Demand System

Abstract

In this study, we analyze how forecasting methods for PV power generation and demand affect cost, CO2 emissions, and battery capacity in local power systems. The choice of forecasting methods affects cost and battery capacity. For example, it reduces total cost by up to 38% and optimal battery capacity by up to 60%. CO2 emissions are reduced by increasing PV size, and the reduction varies with the forecasting methods: 8% for a less accurate forecasting method and 15% for a more accurate method. Insufficient and surplus imbalance rates are reduced by the introduction of batteries and private generator, and the reduction varies from 8% to 11%, depending on the accuracy of the forecasting methods.