Economic Operation Algorithm for Energy Storage System with Customer Baseline Load (CBL)-based Load Forecasting

초록

An operation of energy storage system (ESS) in buildings and factories is gaining popularity owing to its decreasing price and increasing efficiency. However, there is a financial risk in conducting ESS without evaluating its profit in advance. Therefore, this paper analyzes economic benefits of ESS before installation. A mathematical model of ESS and an ESS power scheduling algorithm are presented, which consider both a peak load and an energy cost to maximize user뭩 benefit. The algorithm employs customer baseline load (CBL)-based load forecasting which will facilitate its engagement in Korean electricity market since it is used in order to evaluate load reduction in Korea. In addition, symmetric additive adjustment (SAA) is applied to improve low load forecasting accuracy of the CBL-based load prediction. That is, day ahead optimization is performed by the CBL-based load prediction and it is re scheduled hourly with corrected load by SAA during ESS operation. In case study, ESS scheduling results for an actual load, CBL-based load forecasting, and SAA applied load forecasting are compared for a normal load day and a peak load day.