Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid

Abstract This study proposes a holistic data‐driven method for the optimal sizing and operation of a building‐level islanded microgrid with renewable energy resources in an urban setting. Firstly, various metres are integrated on an energy monitoring platform where field data are collected. A random...

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Autores principales:	Xue Feng, King Jet Tseng
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Energy industries. Energy policy. Fuel trade HD9502-9502.5 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Acceso en línea:	https://doaj.org/article/a87714ab4b9c4075b3550ee2688f0b95
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spelling	oai:doaj.org-article:a87714ab4b9c4075b3550ee2688f0b952021-11-22T16:30:08ZHolistic data‐driven method for optimal sizing and operation of an urban islanded microgrid2634-158110.1049/enc2.12029https://doaj.org/article/a87714ab4b9c4075b3550ee2688f0b952021-09-01T00:00:00Zhttps://doi.org/10.1049/enc2.12029https://doaj.org/toc/2634-1581Abstract This study proposes a holistic data‐driven method for the optimal sizing and operation of a building‐level islanded microgrid with renewable energy resources in an urban setting. Firstly, various metres are integrated on an energy monitoring platform where field data are collected. A randomised learning‐based forecasting model is designed for supply/demand prediction in the microgrid. Based on the forecasting results, data‐driven uncertainty modelling is used to characterise the uncertainties associated with renewable energy supply and loads. An optimal sizing approach is then proposed to determine the optimal sizes for energy storage systems (ESSs) and distributed generators with the overall aim of minimising the investment and maintenance costs. Based on the optimal sizing and uncertainty scenarios, a two‐stage coordinated energy management method is proposed to minimise the operating cost under uncertainties. To validate the proposed method, it is compared with a benchmark method. Simulation results show that the proposed method can reduce the system cost while preserving the ESS lifetime. The developed methods are packaged onto a real‐time platform for implementation.Xue FengKing Jet TsengWileyarticleEnergy industries. Energy policy. Fuel tradeHD9502-9502.5Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENEnergy Conversion and Economics, Vol 2, Iss 3, Pp 133-144 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Energy industries. Energy policy. Fuel trade HD9502-9502.5 Production of electric energy or power. Powerplants. Central stations TK1001-1841
spellingShingle	Energy industries. Energy policy. Fuel trade HD9502-9502.5 Production of electric energy or power. Powerplants. Central stations TK1001-1841 Xue Feng King Jet Tseng Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
description	Abstract This study proposes a holistic data‐driven method for the optimal sizing and operation of a building‐level islanded microgrid with renewable energy resources in an urban setting. Firstly, various metres are integrated on an energy monitoring platform where field data are collected. A randomised learning‐based forecasting model is designed for supply/demand prediction in the microgrid. Based on the forecasting results, data‐driven uncertainty modelling is used to characterise the uncertainties associated with renewable energy supply and loads. An optimal sizing approach is then proposed to determine the optimal sizes for energy storage systems (ESSs) and distributed generators with the overall aim of minimising the investment and maintenance costs. Based on the optimal sizing and uncertainty scenarios, a two‐stage coordinated energy management method is proposed to minimise the operating cost under uncertainties. To validate the proposed method, it is compared with a benchmark method. Simulation results show that the proposed method can reduce the system cost while preserving the ESS lifetime. The developed methods are packaged onto a real‐time platform for implementation.
format	article
author	Xue Feng King Jet Tseng
author_facet	Xue Feng King Jet Tseng
author_sort	Xue Feng
title	Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
title_short	Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
title_full	Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
title_fullStr	Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
title_full_unstemmed	Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
title_sort	holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/a87714ab4b9c4075b3550ee2688f0b95
work_keys_str_mv	AT xuefeng holisticdatadrivenmethodforoptimalsizingandoperationofanurbanislandedmicrogrid AT kingjettseng holisticdatadrivenmethodforoptimalsizingandoperationofanurbanislandedmicrogrid
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Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid

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