Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction

The goal of this paper is to optimally combine day-ahead solar and demand forecasts for the optimal battery schedule of a hybrid solar and battery farm connected to a distribution station. The objective is to achieve the maximum daily peak load reduction and charge battery with maximum solar photovo...

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Autores principales:	Gergo Barta, Benedek Pasztor, Venkat Prava
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	forecasting competition battery scheduling electric load forecasting solar power forecasting hybrid solar plant Technology T
Acceso en línea:	https://doaj.org/article/40e9cc23d3c844a8b5fa892ac6aaf47f
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id	oai:doaj.org-article:40e9cc23d3c844a8b5fa892ac6aaf47f
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spelling	oai:doaj.org-article:40e9cc23d3c844a8b5fa892ac6aaf47f2021-11-25T17:28:49ZOptimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction10.3390/en142277941996-1073https://doaj.org/article/40e9cc23d3c844a8b5fa892ac6aaf47f2021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7794https://doaj.org/toc/1996-1073The goal of this paper is to optimally combine day-ahead solar and demand forecasts for the optimal battery schedule of a hybrid solar and battery farm connected to a distribution station. The objective is to achieve the maximum daily peak load reduction and charge battery with maximum solar photovoltaic energy. The innovative part of the paper lies in the treatment for the errors in solar and demand forecasts to then optimize the battery scheduler. To test the effectiveness of the proposed methodology, it was applied in the data science challenge Presumed Open Data 2021. With the historical Numerical Weather Prediction (NWP) data, solar power plant generation and distribution-level demand data provided, the proposed methodology was tested for four different seasons. The evaluation metric used is the peak reduction score (defined in the paper), and our approach has improved this KPI from 82.84 to 89.83. The solution developed achieved a final place of 5th (out of 55 teams) in the challenge.Gergo BartaBenedek PasztorVenkat PravaMDPI AGarticleforecasting competitionbattery schedulingelectric load forecastingsolar power forecastinghybrid solar plantTechnologyTENEnergies, Vol 14, Iss 7794, p 7794 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	forecasting competition battery scheduling electric load forecasting solar power forecasting hybrid solar plant Technology T
spellingShingle	forecasting competition battery scheduling electric load forecasting solar power forecasting hybrid solar plant Technology T Gergo Barta Benedek Pasztor Venkat Prava Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
description	The goal of this paper is to optimally combine day-ahead solar and demand forecasts for the optimal battery schedule of a hybrid solar and battery farm connected to a distribution station. The objective is to achieve the maximum daily peak load reduction and charge battery with maximum solar photovoltaic energy. The innovative part of the paper lies in the treatment for the errors in solar and demand forecasts to then optimize the battery scheduler. To test the effectiveness of the proposed methodology, it was applied in the data science challenge Presumed Open Data 2021. With the historical Numerical Weather Prediction (NWP) data, solar power plant generation and distribution-level demand data provided, the proposed methodology was tested for four different seasons. The evaluation metric used is the peak reduction score (defined in the paper), and our approach has improved this KPI from 82.84 to 89.83. The solution developed achieved a final place of 5th (out of 55 teams) in the challenge.
format	article
author	Gergo Barta Benedek Pasztor Venkat Prava
author_facet	Gergo Barta Benedek Pasztor Venkat Prava
author_sort	Gergo Barta
title	Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
title_short	Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
title_full	Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
title_fullStr	Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
title_full_unstemmed	Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction
title_sort	optimized charge controller schedule in hybrid solar-battery farms for peak load reduction
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/40e9cc23d3c844a8b5fa892ac6aaf47f
work_keys_str_mv	AT gergobarta optimizedchargecontrollerscheduleinhybridsolarbatteryfarmsforpeakloadreduction AT benedekpasztor optimizedchargecontrollerscheduleinhybridsolarbatteryfarmsforpeakloadreduction AT venkatprava optimizedchargecontrollerscheduleinhybridsolarbatteryfarmsforpeakloadreduction
_version_	1718412279761862656

Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction

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