Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty

Abstract This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass‐based Distributed Generation (DG) units in distributi...

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Autores principales:	Mansur Khasanov, Salah Kamel, Claudia Rahmann, Hany M. Hasanien, Ahmed Al‐Durra
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Acceso en línea:	https://doaj.org/article/462a4f4d05ec4747b67e8531ae42295b
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spelling	oai:doaj.org-article:462a4f4d05ec4747b67e8531ae42295b2021-11-16T15:47:59ZOptimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty1751-86951751-868710.1049/gtd2.12230https://doaj.org/article/462a4f4d05ec4747b67e8531ae42295b2021-12-01T00:00:00Zhttps://doi.org/10.1049/gtd2.12230https://doaj.org/toc/1751-8687https://doaj.org/toc/1751-8695Abstract This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass‐based Distributed Generation (DG) units in distribution systems (DS). The main objective function is to minimize the total power and energy losses. Power loss‐sensitivity factor (PLSF) is used with the ROA to determine the suitable candidate buses and accelerate the solution process. The Weibull and Beta probability distribution functions (PDF) are employed to characterize the variability of wind speed and solar radiation, respectively. The high penetration of intermittent renewable resource together with demand variations has introduced many challenges to distribution systems such as power fluctuations, voltage rise, high losses, and low voltage stability, therefore battery energy storage (BES) and dispatchable Biomass are considered to smooth out the fluctuations and improve supply continuity. The standard 33 and 69‐bus test systems are used to verify the effectiveness of the proposed technique compared with other well‐known optimization techniques. The results show that the developed approach accelerates to the near‐optimal solution seamlessly, and in steady convergence characteristics compared with other techniques.Mansur KhasanovSalah KamelClaudia RahmannHany M. HasanienAhmed Al‐DurraWileyarticleDistribution or transmission of electric powerTK3001-3521Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENIET Generation, Transmission & Distribution, Vol 15, Iss 24, Pp 3400-3422 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
spellingShingle	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841 Mansur Khasanov Salah Kamel Claudia Rahmann Hany M. Hasanien Ahmed Al‐Durra Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
description	Abstract This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass‐based Distributed Generation (DG) units in distribution systems (DS). The main objective function is to minimize the total power and energy losses. Power loss‐sensitivity factor (PLSF) is used with the ROA to determine the suitable candidate buses and accelerate the solution process. The Weibull and Beta probability distribution functions (PDF) are employed to characterize the variability of wind speed and solar radiation, respectively. The high penetration of intermittent renewable resource together with demand variations has introduced many challenges to distribution systems such as power fluctuations, voltage rise, high losses, and low voltage stability, therefore battery energy storage (BES) and dispatchable Biomass are considered to smooth out the fluctuations and improve supply continuity. The standard 33 and 69‐bus test systems are used to verify the effectiveness of the proposed technique compared with other well‐known optimization techniques. The results show that the developed approach accelerates to the near‐optimal solution seamlessly, and in steady convergence characteristics compared with other techniques.
format	article
author	Mansur Khasanov Salah Kamel Claudia Rahmann Hany M. Hasanien Ahmed Al‐Durra
author_facet	Mansur Khasanov Salah Kamel Claudia Rahmann Hany M. Hasanien Ahmed Al‐Durra
author_sort	Mansur Khasanov
title	Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
title_short	Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
title_full	Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
title_fullStr	Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
title_full_unstemmed	Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
title_sort	optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/462a4f4d05ec4747b67e8531ae42295b
work_keys_str_mv	AT mansurkhasanov optimaldistributedgenerationandbatteryenergystorageunitsintegrationindistributionsystemsconsideringpowergenerationuncertainty AT salahkamel optimaldistributedgenerationandbatteryenergystorageunitsintegrationindistributionsystemsconsideringpowergenerationuncertainty AT claudiarahmann optimaldistributedgenerationandbatteryenergystorageunitsintegrationindistributionsystemsconsideringpowergenerationuncertainty AT hanymhasanien optimaldistributedgenerationandbatteryenergystorageunitsintegrationindistributionsystemsconsideringpowergenerationuncertainty AT ahmedaldurra optimaldistributedgenerationandbatteryenergystorageunitsintegrationindistributionsystemsconsideringpowergenerationuncertainty
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Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty

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