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Understanding the Energy Transition with a Machine Learning Toolbox

Project description

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.

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.

Keywords

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

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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
Total cost
€ 1 679 125,00

Beneficiaries (1)