Abstract (EN):
In the last decades power systems witnessed the implementation of an organizational and operational restructuring that lead to the introduction of competitive mechanisms in some activities of the value chain. This is the case of generation and retailing with the development of wholesale and retail markets. These developments together with a renewed emphasis on the adoption of more sustainable solutions while maintaining adequate security of supply levels contributed to increase the interest of generation companies for models enabling the optimization of the use of generation assets or for models and tools to help them to prepare and test bidding strategies to the day-ahead markets. Having in mind the increased complexity of the operation of power systems, Agent-Based Models, ABM, are been used to complement the traditional optimization and equilibrium models, taking advantage of the interaction between agents acting in a simulation environment. In this scope, this paper describes an ABM model that uses Q-learning to provide knowledge for the agents to behave in an optimal way. This model is designed to mimic the main features of the common electricity market between Portugal and Spain, the MIBEL. Apart from describing the developed model, this paper also includes preliminary results from its application to the MIBEL case.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
6