A Data-based Platform for Supporting Profit-driven Strategy in the Italian Spot Electricity Markets

This paper proposes a data-based web platform to maximize the profit of a player participating in the Italian spot electricity markets. To ensure the scalability and portability of the platform, the micro-services approach are chosen with four stand-alone services communicating among one another. In the platform, a web crawler module retrieves data from the official and open sources, and a machine learning-based module is created to forecast the bidding strategies of all the market players for the next day across different spot markets. Based on the forecasted strategies, simplified market-clearing mechanisms are adopted to obtain the initial market information. Then by focusing on a single player, his/her strategy is optimized to maximize the daily profit over multiple spot markets with different payment schemes. The client can access the system through a simple, user-friendly web application. The simulation of the platform shows that around 92% of the market players can increase their profits. An example of a randomly selected player shows that the platform suggests a strategy leading to a 127.6% increase in its profit compared with its real bids in the markets.