Name
Abstract | ||
|---|---|---|
The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players' strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players' models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21827-9_50 | IEA/AIE (2) |
Keywords | Field | DocType |
strategic bidding methodology,deep study,different technique,adaptive learning,proposed methodology,electricity market negotiation,electricity market,past experience,market simulator,past action,bids formulation,mascem player,multiagent systems,forecasting methods,intelligent agents | Electricity market,Intelligent agent,Electricity,Computer science,Simulation,Operations research,Multi-agent system,Strategic bidding,Adaptive learning,Negotiation,Reinforcement learning | Conference |
Citations | PageRank | References |
5 | 0.69 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiago Pinto | 1 | 68 | 25.43 |
| Zita Vale | 2 | 64 | 27.90 |
| Fátima Rodrigues | 3 | 45 | 7.12 |
| Hugo Morais | 4 | 257 | 31.41 |
| Isabel Praça | 5 | 212 | 40.45 |