Trading Strategy For Decentralized Energy Resources In Sequential Electricity Markets: A Swiss Case Study

This paper derives optimal day-ahead trading strategies for an aggregator of a decentralized energy resources' mix, who participates in a multi-market environment, including a day-ahead, an intraday and a balancing market. The optimization problem is solved using multi-stage stochastic programming, which is subject to different levels of uncertainties such as variable generation output, day-ahead and intraday market prices. Risk management is conducted to investigate the effect of risk exposure on the total revenue of the aggregator. A case study based on the data from the Swiss electricity market demonstrates the effectiveness of the proposed model.