Development of 24-hour optimal scheduling algorithm for energy storage system using load forecasting and renewable energy forecasting

Abstract

This paper presents the 24-hour optimal scheduling algorithm for Energy Storage System (ESS) using load forecasting and renewable energy forecasting in South Korea electricity tariff structure. For load forecasting and renewable energy forecasting, 24-hour multivariate forecasting model combining very-short-term and short-term forecasting models is developed. Then, load and renewable forecasts are input to the optimal ESS scheduling algorithm. The objective of this algorithm is to maximize the customer's profit by energy arbitrage, minimize the peak load to reduce the contract power, and minimize the charging/discharging cycles to lengthen the expected life of ESS. The effectiveness of this algorithm is validated in case study.