Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant

This paper has tried to execute accurate demand forecasting by utilizing big data visualization and proposes a flexible and balanced electric power production big data virtualization based on a photovoltaic power plant. First of all, this paper has tried to align electricity demand and supply as muc...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Seung-Mo Je, Hyeyoung Ko, Jun-Ho Huh
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	electric power production model power generation systems web crawling game theory renewable photovoltaic power plant Technology T
Acceso en línea:	https://doaj.org/article/4238241d800a4be1bace2c08b79b6f98
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:4238241d800a4be1bace2c08b79b6f98
record_format	dspace
spelling	oai:doaj.org-article:4238241d800a4be1bace2c08b79b6f982021-11-11T15:45:01ZAccurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant10.3390/en142169151996-1073https://doaj.org/article/4238241d800a4be1bace2c08b79b6f982021-10-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/6915https://doaj.org/toc/1996-1073This paper has tried to execute accurate demand forecasting by utilizing big data visualization and proposes a flexible and balanced electric power production big data virtualization based on a photovoltaic power plant. First of all, this paper has tried to align electricity demand and supply as much as possible using big data. Second, by using big data to predict the supply of new renewable energy, an attempt was made to incorporate new and renewable energy into the current power supply system and to recommend an efficient energy distribution method. The first presented problem that had to be solved was the improvement in the accuracy of the existing electricity demand for forecasting models. This was explained through the relationship between the power demand and the number of specific words in the paper that use crawling by utilizing big data. The next problem arose because the current electricity production and supply system stores the amount of new renewable energy by changing the form of energy that is produced through ESS or that is pumped through water power generation without taking the amount of new renewable energy that is generated from sources such as thermal power, nuclear power, and hydropower into consideration. This occurs due to the difficulty of predicting power production using new renewable energy and the absence of a prediction system, which is a problem due to the inefficiency of changing energy types. Therefore, using game theory, the theoretical foundation of a power demand forecasting model based on big data-based renewable energy production forecasting was prepared.Seung-Mo JeHyeyoung KoJun-Ho HuhMDPI AGarticleelectric power production modelpower generation systemsweb crawlinggame theoryrenewablephotovoltaic power plantTechnologyTENEnergies, Vol 14, Iss 6915, p 6915 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	electric power production model power generation systems web crawling game theory renewable photovoltaic power plant Technology T
spellingShingle	electric power production model power generation systems web crawling game theory renewable photovoltaic power plant Technology T Seung-Mo Je Hyeyoung Ko Jun-Ho Huh Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
description	This paper has tried to execute accurate demand forecasting by utilizing big data visualization and proposes a flexible and balanced electric power production big data virtualization based on a photovoltaic power plant. First of all, this paper has tried to align electricity demand and supply as much as possible using big data. Second, by using big data to predict the supply of new renewable energy, an attempt was made to incorporate new and renewable energy into the current power supply system and to recommend an efficient energy distribution method. The first presented problem that had to be solved was the improvement in the accuracy of the existing electricity demand for forecasting models. This was explained through the relationship between the power demand and the number of specific words in the paper that use crawling by utilizing big data. The next problem arose because the current electricity production and supply system stores the amount of new renewable energy by changing the form of energy that is produced through ESS or that is pumped through water power generation without taking the amount of new renewable energy that is generated from sources such as thermal power, nuclear power, and hydropower into consideration. This occurs due to the difficulty of predicting power production using new renewable energy and the absence of a prediction system, which is a problem due to the inefficiency of changing energy types. Therefore, using game theory, the theoretical foundation of a power demand forecasting model based on big data-based renewable energy production forecasting was prepared.
format	article
author	Seung-Mo Je Hyeyoung Ko Jun-Ho Huh
author_facet	Seung-Mo Je Hyeyoung Ko Jun-Ho Huh
author_sort	Seung-Mo Je
title	Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
title_short	Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
title_full	Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
title_fullStr	Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
title_full_unstemmed	Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant
title_sort	accurate demand forecasting: a flexible and balanced electric power production big data virtualization based on photovoltaic power plant
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4238241d800a4be1bace2c08b79b6f98
work_keys_str_mv	AT seungmoje accuratedemandforecastingaflexibleandbalancedelectricpowerproductionbigdatavirtualizationbasedonphotovoltaicpowerplant AT hyeyoungko accuratedemandforecastingaflexibleandbalancedelectricpowerproductionbigdatavirtualizationbasedonphotovoltaicpowerplant AT junhohuh accuratedemandforecastingaflexibleandbalancedelectricpowerproductionbigdatavirtualizationbasedonphotovoltaicpowerplant
_version_	1718434080476889088

Accurate Demand Forecasting: A Flexible and Balanced Electric Power Production Big Data Virtualization Based on Photovoltaic Power Plant

Ejemplares similares