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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.

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

ERC-COG - Consolidator Grant

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2020-COG

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Host institution

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 222 247,19
Address
CALLE SERRANO 117
28006 MADRID
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 222 247,19

Beneficiaries (2)

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