Single electricity market forecasting and energy arbitrage maximization framework

Abstract

The rapid deployment of renewable-based generation to meet the net-zero carbon targets has affected the wholesale energy paradigm. In the island of Ireland, the Single Electricity Market (SEM) aims to deliver high levels of supply security, reliability, and transparency through multiple markets with different trading time frames and clearing procedures. This paper proposes a powerful methodology to maximize the revenues from the participation in the SEM. A forecasting model of four successive stages based on neural networks is proposed to predict the demand and system marginal prices of the SEM ex-ante markets. An energy arbitrage optimization framework is proposed for battery energy storage systems (BESS) to maximize the arbitrage profits. The methodology efficacy is validated by achieving 91.1% selling accuracy, 97.9% buying accuracy, and 85.1% energy arbitrage net accuracy of the ideal case where the SEM data is perfectly-known for three consecutive months. Furthermore, the BESS degradation is evaluated and a cost-benefit analysis is introduced to evaluate the economic feasibility of BESS participating in the SEM ex-ante markets. The results reveal that the participation of BESS in the SEM solely is not profitable, however, under stacked revenues arrangement, the proposed methodology can be applied to boost the BESS revenues.