Descrizione del progetto
Chiarire le sfide dell’integrazione delle energie rinnovabili
Mentre l’UE è fortemente impegnata a raggiungere i suoi ambiziosi obiettivi in materia di clima ed energia, incombe la sfida dell’integrazione delle fonti di energia rinnovabile. Gli obiettivi europei in tal ambito richiedono un’elevata integrazione di questo tipo, il che rende la flessibilità operativa più importante che mai per gestire la variabilità e l’incertezza della generazione rinnovabile. In quest’ottica, il progetto THINKPV, finanziato dal programma MSCA, mira a migliorare la previsione della generazione fotovoltaica sviluppando un sistema probabilistico basato sull’apprendimento automatico. Grazie allo sfruttamento dei dati ricavati dalla rete di distribuzione, questa soluzione innovativa migliorerà l’accuratezza, supportando l’integrazione di impianti fotovoltaici su larga scala e la manutenzione predittiva. I test operativi condotti presso il Laboratorio di Sistemi energetici elettrici del Politecnico di Atene dimostreranno l’efficacia della soluzione progettuale per una società di gestione e manutenzione del fotovoltaico in Italia.
Obiettivo
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.
Campo scientifico
- 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
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF-EF-ST - Standard EFCoordinatore
106 82 ATHINA
Grecia