Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids

Studies on forecasting and optimal exploitation of renewable resources (especially within microgrids) were already introduced in the past. However, in several research papers, the constraints regarding integration within real applications were relaxed, i.e., this kind of research provides impractica...

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Autores principales:	Hamidreza Mirtaheri, Piero Macaluso, Maurizio Fantino, Marily Efstratiadi, Sotiris Tsakanikas, Panagiotis Papadopoulos, Andrea Mazza
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	microgrids energy management system forecast artificial intelligence neural networks recurrent neural networks Technology T
Acceso en línea:	https://doaj.org/article/e4b399b1c7b7491eaefc78ab07d5dcb8
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spelling	oai:doaj.org-article:e4b399b1c7b7491eaefc78ab07d5dcb82021-11-11T16:00:37ZHybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids10.3390/en142172521996-1073https://doaj.org/article/e4b399b1c7b7491eaefc78ab07d5dcb82021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/7252https://doaj.org/toc/1996-1073Studies on forecasting and optimal exploitation of renewable resources (especially within microgrids) were already introduced in the past. However, in several research papers, the constraints regarding integration within real applications were relaxed, i.e., this kind of research provides impractical solutions, although they are very complex. In this paper, the computational components (such as photovoltaic and load forecasting, and resource scheduling and optimization) are brought together into a practical implementation, introducing an automated system through a chain of independent services aiming to allow forecasting, optimization, and control. Encountered challenges may provide a valuable indication to make ground with this design, especially in cases for which the trade-off between sophistication and available resources should be rather considered. The research work was conducted to identify the requirements for controlling a set of flexibility assets—namely, electrochemical battery storage system and electric car charging station—for a semicommercial use-case by minimizing the operational energy costs for the microgrid considering static and dynamic parameters of the assets.Hamidreza MirtaheriPiero MacalusoMaurizio FantinoMarily EfstratiadiSotiris TsakanikasPanagiotis PapadopoulosAndrea MazzaMDPI AGarticlemicrogridsenergy management systemforecastartificial intelligenceneural networksrecurrent neural networksTechnologyTENEnergies, Vol 14, Iss 7252, p 7252 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	microgrids energy management system forecast artificial intelligence neural networks recurrent neural networks Technology T
spellingShingle	microgrids energy management system forecast artificial intelligence neural networks recurrent neural networks Technology T Hamidreza Mirtaheri Piero Macaluso Maurizio Fantino Marily Efstratiadi Sotiris Tsakanikas Panagiotis Papadopoulos Andrea Mazza Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
description	Studies on forecasting and optimal exploitation of renewable resources (especially within microgrids) were already introduced in the past. However, in several research papers, the constraints regarding integration within real applications were relaxed, i.e., this kind of research provides impractical solutions, although they are very complex. In this paper, the computational components (such as photovoltaic and load forecasting, and resource scheduling and optimization) are brought together into a practical implementation, introducing an automated system through a chain of independent services aiming to allow forecasting, optimization, and control. Encountered challenges may provide a valuable indication to make ground with this design, especially in cases for which the trade-off between sophistication and available resources should be rather considered. The research work was conducted to identify the requirements for controlling a set of flexibility assets—namely, electrochemical battery storage system and electric car charging station—for a semicommercial use-case by minimizing the operational energy costs for the microgrid considering static and dynamic parameters of the assets.
format	article
author	Hamidreza Mirtaheri Piero Macaluso Maurizio Fantino Marily Efstratiadi Sotiris Tsakanikas Panagiotis Papadopoulos Andrea Mazza
author_facet	Hamidreza Mirtaheri Piero Macaluso Maurizio Fantino Marily Efstratiadi Sotiris Tsakanikas Panagiotis Papadopoulos Andrea Mazza
author_sort	Hamidreza Mirtaheri
title	Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
title_short	Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
title_full	Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
title_fullStr	Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
title_full_unstemmed	Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids
title_sort	hybrid forecast and control chain for operation of flexibility assets in micro-grids
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e4b399b1c7b7491eaefc78ab07d5dcb8
work_keys_str_mv	AT hamidrezamirtaheri hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT pieromacaluso hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT mauriziofantino hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT marilyefstratiadi hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT sotiristsakanikas hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT panagiotispapadopoulos hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids AT andreamazza hybridforecastandcontrolchainforoperationofflexibilityassetsinmicrogrids
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Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids

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