Descripción del proyecto
Más información sobre los retos de la integración de las energías renovables
Mientras la Unión Europea se apresura a cumplir sus ambiciosos objetivos climáticos y energéticos, el reto de integrar las fuentes de energía renovables se cierne sobre ella. Los objetivos climáticos y energéticos de Europa exigen una elevada integración de las fuentes de energía renovables, lo que hace que la flexibilidad operativa sea más importante que nunca para gestionar la variabilidad y la incertidumbre de la generación renovable. Teniendo esto en cuenta, en el proyecto THINKPV, financiado por las acciones Marie Skłodowska-Curie, se pretende mejorar la previsión de la generación fotovoltaica (FV, o PV por sus siglas en inglés) mediante el desarrollo de un sistema probabilístico basado en el aprendizaje automático. Esta solución innovadora, que emplea datos de la red de distribución, mejorará la precisión y respaldará la integración de FV a gran escala y el mantenimiento predictivo. Las pruebas operativas llevadas a cabo en el Laboratorio de Sistemas de Energía Eléctrica de la Universidad Técnica Nacional de Atenas demostrarán la eficacia de la solución del proyecto para una empresa de explotación y mantenimiento de sistemas PV de Italia.
Objetivo
The European Union policy for climate and energy imposes significant targets for a high integration of renewable energy sources in the period from 2020 to 2030. System operators have to deal with operational flexibility to respond to variability and to uncertainty of the renewable generation, ensuring the network reliability and security. While significant efforts have been made into the developing accurate forecasts, much work remains to integrate the forecasting in the electric system operations. The successful incorporation of forecasts into grid operation emerges as an important challenge. Accurate photovoltaic (PV) generation forecasts are major themes of the research roadmap of many international task forces, as Smart Grids SRA 2035 to support the flexibility increasing of the power systems. In this context, the project aims to support large scale integration of PV systems in countries with a high solar resource and a significant potential of small capacity PV systems such as Greece. The Institute of Communication and Computer Systems (ICCS) is the most important Hellenic research institute, committed to support Hellenic Electricity Distribution Network Operator S.A. (HENDO) that is dealing with a radical modernization of the existing network. The THINKPV project encourages the ICCS and its industrial partners to facilitate PV grid integration by the development of a probabilistic forecasting system based on machine learning, taking advantage of data that can be measured in the distribution network, in order to improve forecast accuracy compared to the state of art. The model will be assembled into a solar power forecasting system that will be operational at the Electric Energy Systems Laboratory (EESL) of the ICCS to operate directly with tools for simulating power system operations. A prototype of operational solar forecasting systems will be demonstrated for HENDO, providing also a training program for its efficiency and correct application.
Ámbito científico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectrical engineeringelectric energy
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energysolar energyphotovoltaic
Programa(s)
Régimen de financiación
MSCA-IF-EF-ST - Standard EFCoordinador
106 82 ATHINA
Grecia