Simulation of the operation of hydro plants in an electricity market using Agent Based Models - introducing a Q Learning approach

Abstract

The restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example.