Project description DEENESFRITPL Smart tools to boost understanding of new electricity market With climate change impacting people worldwide, the push for cleaner energy solutions, new resources and optimisation has brought deep changes to the electricity market. To go forward smoothly, the transformation requires new tools for suppliers and consumers. The EU-funded ENECML project will design and utilise an innovative set of statistical tools and structural models combined with machine learning to present several projects and methodologies and assist in better understanding the transition in the electricity market. Moreover, it will support strategic behaviour and market design in the case of energy suppliers and highlight the distribution implications for low socioeconomic status households and consumers. Show the project objective Hide the project objective Objective The goal of this proposal is to build tools to better understand the economic impacts of the rapid transformation of electricity markets, and to help better design electricity markets going forward. I propose to develop and implement novel statistical tools and structural models that contribute to our understanding of this rapid transformation. The proposed research focuses both on firm strategic responses and investment (supply-side), as well as consumer behavior and welfare and distributional impacts (demand-side). The proposal presents several projects and methodologies that examine these issues in detail with unique high-frequency micro-data on firms and households. The tools and models developed in this proposal can help understand the impacts of the energy transition, both on the supply and the demand side. Among the expected methodological contributions, I plan to combine machine learning tools with more standard structural modeling. On the supply side, the proposal emphasizes the need to understand how strategic behavior interacts with market design in the presence of intermittent resources. On the demand side, the proposal highlights the importance of understanding the distributional implications of such changes with special attention to the residential sector and the most vulnerable socio-economic households. Fields of science social scienceseconomics and businesseconomicsmicroeconomicsnatural sciencescomputer and information sciencesartificial intelligencemachine learning Keywords ENECML Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2020-COG - ERC CONSOLIDATOR GRANTS Call for proposal ERC-2020-COG See other projects for this call Funding Scheme ERC-COG - Consolidator Grant Host institution FUNDACIO PRIVADA BARCELONA GRADUATE SCHOOL OF ECONOMICS Net EU contribution € 1 679 125,00 Address CALLE RAMON TRIAS FARGAS 25 27 08005 Barcelona Spain See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Este Cataluña Barcelona Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 679 125,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all FUNDACIO PRIVADA BARCELONA GRADUATE SCHOOL OF ECONOMICS Spain Net EU contribution € 1 679 125,00 Address CALLE RAMON TRIAS FARGAS 25 27 08005 Barcelona See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Este Cataluña Barcelona Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 679 125,00
