Skip to main content

A Computational Approach To Electricity Markets


The process of restructuring of electricity industry is transforming the traditional vertical integrated monopolies, into deregulated entities, where decentralized decisions are made by independent agents interested to maximize their own reward.

In such a decentralized context, there is a growing interest toward models and tools that allow analyzing oligopolistic electricity markets, and agent's behaviours for both short-term and long-term strategies. The interest is twofold. On one hand, the regulatory authority needs appropriate tools for monitoring the electricity market, and simulate - before the actual implementation - new regulatory provision.

On the other side, the active market participants benefit from tools that help them to make strategic decisions for maximizing their payoffs. We propose to investigate the adoption of a multi-agent framework for the simulation of a general oligopolistic electricity market, and for the study of strategies of market participants both for short and long time horizons. To deal with the inherent uncertainties of the market, a stochastic programming approach will be adopted.

More precisely, we propose to adopt Monte-Carlo simulation techniques combined with machine learning to create detailed market agents' behavioural models. The validation of the general multi-agent platform will make use of real market data collected possibly from RTE or PJM market operator. Finally, the possibility of analysing real market data using data-mining techniques will be explored.

The proposed project is clearly multidisciplinary, and allows to combine the fellow's background that involves power engineering and economics, with the expertise of the host institutions that is known to be very prestigious in power engineering and computer science fields.

The new competencies acquired by the fellow during her stay with the host institution will be extremely useful for the development of future research projects in her original team.

Field of science

  • /natural sciences/computer and information sciences
  • /engineering and technology/electrical engineering, electronic engineering, information engineering/electrical engineering/power engineering
  • /social sciences/economics and business/business and management/commerce

Call for proposal

See other projects for this call

Funding Scheme

EIF - Marie Curie actions-Intra-European Fellowships