Project description
New framework to improve power grid price forecasting
As electricity cannot be stored easily and heavily depends on weather patterns and grid capacity, power prices present highly volatile changes. Green energy transition further amplifies these extreme price jumps, complicating risk assessment for economic agents and logistics engineers. Supported by the Marie Skłodowska-Curie Actions programme, the MAR-EPF project aims to develop a new econometric framework that combines physical real-world constraints with statistical formulas. The proposed framework will factor in weather variables such as wind, solar irradiance and transmission network bottlenecks. Specifically, it will use mixed causal-non-causal models, which allow calculations to account for future-dependent dynamics. MAR-EPF’s approach will help bridge the gap between rigid traditional models and complex neural networks, delivering highly accurate, interpretable energy market forecasts.
Objective
The project focuses on the development of a novel econometric methodology for electricity price forecasting (EPF), with the goal of improving existing methods. Forecasting electricity prices is crucial for energy market trading and stablity. However, the modeling and forecasting of these prices are complex due to the non-storability, the dependence on the transmission grid, and weather patterns. These features, joint with the green transition and expanding power supply from renewable energy sources, give rise to extreme events, heavy tails and complex dynamics in general. In this sense, better forecasting of electricity prices would lead to an improved risk assessment and monitoring for economic agents and engineering involved in the logistics of the electricity market.
To achieve this goal, the project relies on two main contributions: the use of mixed causal–non-causal (MAR) models and the explicit incorporation of physical constraints, such as distribution grid limitations and weather-driven effects, into the econometric framework. MAR models are a class of heavy-tailed autoregressive models that allows a process to depend also on its future. The forward looking specification of MAR models allows the framework to model non-linear and explosive dynamics while maintaining the linear and parsimonious specification typical of autoregressive models. This approach is novel in the literature for electricity price modeling, offering a bridge between the non-linear methods as Artificial Neural Networks (ANN) and traditional linear autoregressive models (ARMA) that are currently in use.
Moreover, by explicitly modeling physical constraints, including transmission network bottlenecks, generation capacity limits, and the influence of weather variables such as temperature, wind, and solar irradiance, the proposed framework will capture the underlying mechanisms that drive price formation in electricity markets, enhancing interpretability and improving forecasting accuracy.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project has not yet been classified with EuroSciVoc.
Be the first one to suggest relevant scientific fields and help us improve our classification service
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
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.
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.
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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
See all projects funded under this callCoordinator
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.
8000 Aarhus C
Denmark
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.