Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm
Optimal scheduling of distributed energy resources (DERs) of a low-voltage utility-connected microgrid system is studied in this paper. DERs include both dispatchable fossil-fueled generators and non-dispatchable renewable energy resources. Various real constraints associated with adjustable loads,...
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MDPI AG
2020-07-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/13/13/3500 |
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author | Bishwajit Dey Fausto Pedro García Márquez Sourav Kr. Basak |
author_facet | Bishwajit Dey Fausto Pedro García Márquez Sourav Kr. Basak |
author_sort | Bishwajit Dey |
collection | DOAJ |
description | Optimal scheduling of distributed energy resources (DERs) of a low-voltage utility-connected microgrid system is studied in this paper. DERs include both dispatchable fossil-fueled generators and non-dispatchable renewable energy resources. Various real constraints associated with adjustable loads, charging/discharging limitations of battery, and the start-up/shut-down time of the dispatchable DERs are considered during the scheduling process. Adjustable loads are assumed to the residential loads which either operates throughout the day or for a particular period during the day. The impact of these loads on the generation cost of the microgrid system is studied. A novel hybrid approach considers the grey wolf optimizer (GWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) to minimize the overall generation cost of the microgrid system. It has been found that the generation costs rise 50% when the residential loads were included along with the fixed loads. Active participation of the utility incurred 9–17% savings in the system generation cost compared to the cases when the microgrid was operating in islanded mode. Finally, statistical analysis has been employed to validate the proposed hybrid Modified Grey Wolf Optimization-Sine Cosine Algorithm-Crow Search Algorithm (MGWOSCACSA) over other algorithms used. |
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institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-03-10T18:38:48Z |
publishDate | 2020-07-01 |
publisher | MDPI AG |
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spelling | doaj.art-acdee5f3d28a4b449d107cfc3274fca62023-11-20T06:02:26ZengMDPI AGEnergies1996-10732020-07-011313350010.3390/en13133500Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA AlgorithmBishwajit Dey0Fausto Pedro García Márquez1Sourav Kr. Basak2Department of Electrical Engineering, Indian Institute of Technology (ISM), Dhanbad 826004, IndiaIngneium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, SpainDepartment of Electrical Engineering, Indian Institute of Technology (ISM), Dhanbad 826004, IndiaOptimal scheduling of distributed energy resources (DERs) of a low-voltage utility-connected microgrid system is studied in this paper. DERs include both dispatchable fossil-fueled generators and non-dispatchable renewable energy resources. Various real constraints associated with adjustable loads, charging/discharging limitations of battery, and the start-up/shut-down time of the dispatchable DERs are considered during the scheduling process. Adjustable loads are assumed to the residential loads which either operates throughout the day or for a particular period during the day. The impact of these loads on the generation cost of the microgrid system is studied. A novel hybrid approach considers the grey wolf optimizer (GWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) to minimize the overall generation cost of the microgrid system. It has been found that the generation costs rise 50% when the residential loads were included along with the fixed loads. Active participation of the utility incurred 9–17% savings in the system generation cost compared to the cases when the microgrid was operating in islanded mode. Finally, statistical analysis has been employed to validate the proposed hybrid Modified Grey Wolf Optimization-Sine Cosine Algorithm-Crow Search Algorithm (MGWOSCACSA) over other algorithms used.https://www.mdpi.com/1996-1073/13/13/3500microgridenergy managementrenewable energy sourcesgrey wolf optimizersine cosine algorithmcrow search algorithm |
spellingShingle | Bishwajit Dey Fausto Pedro García Márquez Sourav Kr. Basak Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm Energies microgrid energy management renewable energy sources grey wolf optimizer sine cosine algorithm crow search algorithm |
title | Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm |
title_full | Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm |
title_fullStr | Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm |
title_full_unstemmed | Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm |
title_short | Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm |
title_sort | smart energy management of residential microgrid system by a novel hybrid mgwoscacsa algorithm |
topic | microgrid energy management renewable energy sources grey wolf optimizer sine cosine algorithm crow search algorithm |
url | https://www.mdpi.com/1996-1073/13/13/3500 |
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