Analysing the Impact of Rationality on the Italian Electricity Market

International audienceWe analyze the behavior of the Italian electricity market with an agent-based model. In particular, we are interested in testing the assumption that the market participants are fully rational in the economical sense. To this aim, we extend a previous model by considering a wider class of cases. After checking that the new model is a correct generalization of the existing model, we compare three optimization methods to implement the agents rationality and we verify that the model exhibits a very good fit to the real data. This leads us to conclude that our model can be used to predict the behavior of this market

Multi-agent Electricity Markets and Smart Grids Simulation with Connection to Real Physical Resources

The increasing penetration of distributed energy sources, mainly based on renewable generation, calls for an urgent emergence of novel advanced methods to deal with the associated problems. The consensus behind smart grids (SGs) as one of the most promising solutions for the massive integration of renewable energy sources in power systems has led to the development of several prototypes that aim at testing and validating SG methodologies. The urgent need to accommodate such resources require alternative solutions. This chapter presents a multi-agent based SG simulation platform connected to physical resources, so that realistic scenarios can be simulated. The SG simulator is also connected to the Multi-Agent Simulator of Competitive Electricity Markets, which provides a solid framework for the simulation of electricity markets. The cooperation between the two simulation platforms provides huge studying opportunities under different perspectives, resulting in an important contribution to the fields of transactive energy, electricity markets, and SGs. A case study is presented, showing the potentialities for interaction between players of the two ecosystems: a SG operator, which manages the internal resources of a SG, is able to participate in electricity market negotiations to trade the necessary amounts of power to fulfill the needs of SG consumers.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N. 641794 (project DREAM-GO). It has also received FEDER Funds through the COMPETE program and National Funds through FCT under the project UID/EEA/00760/2013. The authors gratefully acknowledge the valuable contribution of Bruno Canizes, Daniel Paiva, Gabriel Santos and Marco Silva to the work presented in the chapter.info:eu-repo/semantics/publishedVersio

Modeling the Risks of Geothermal Development

Geothermal energy has emerged as a promising energy source in recent years and has received serious attention from developers and potential users. Despite the advantages of this resource, such as potential cost competitiveness, reliability, public acceptance, etc., the commercial development and use of geothermal energy has been slow. Impediments to the development of this resource include technical, financial, environmental and regulatory uncertainties. Since geothermal power is unique in that the generation facility is tied to a single fuel at a single site, these uncertainties are of particular concern to utility companies. The areas of uncertainty and potential risks are well known. This paper presents a method for quantifying the relevant uncertainties and a framework for aggregating the risks through the use of submodels. The objective submodels can be combined with subjective probabilities (when sufficient data is not available) to yield a probability distribution over a single criterion (levelized busbar cost) that can be used to compare the desirability of geothermal power development with respect to other alternatives