An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles

Microgrid (MG) is capable of accommodating renewable energy sources (RESs) with high flexibility. With the rapid development of MGs, plug-in hybrid electric vehicles (PHEVs) are gaining increasing attention since they can alleviate pollution and reduce energy consumption. The appearance of PHEVs w...

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Main Author: QIU, C.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2024-02-01
Series:Advances in Electrical and Computer Engineering
Subjects:
Online Access:http://dx.doi.org/10.4316/AECE.2024.01005
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author QIU, C.
author_facet QIU, C.
author_sort QIU, C.
collection DOAJ
description Microgrid (MG) is capable of accommodating renewable energy sources (RESs) with high flexibility. With the rapid development of MGs, plug-in hybrid electric vehicles (PHEVs) are gaining increasing attention since they can alleviate pollution and reduce energy consumption. The appearance of PHEVs would exacerbate the power supply shortages and bring new challenges to the power system. This paper develops an effective day-ahead optimal scheduling of a MG, taking into account RESs, storage devices and PHEVs. The Monte Carlo simulation is utilized to model the uncertainties of PHEVs. A smart charging/discharging strategy incorporating the V2G technique is proposed to smooth the demand curve and reduce the operational costs. To handle the MG scheduling problem in the presence of PHEVs, an improved sine cosine algorithm with simulated annealing based local search operator and chaotic opposition learning strategy (CSCASA) is proposed to minimize the total costs. The proposed algorithm can keep a better balance between global and local search abilities. CSCASA is first validated on some benchmark problems. Then, CSCASA is employed to generate optimal schedule of a grid-connected MG with PHEVs. The experimental results demonstrate the superior performance of CSCASA in the optimal MG scheduling problem with and without PHEVs.
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spelling doaj.art-6b5d1e3682714622aa88e0c684b718c62024-03-03T05:56:19ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002024-02-01241415010.4316/AECE.2024.01005An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric VehiclesQIU, C.Microgrid (MG) is capable of accommodating renewable energy sources (RESs) with high flexibility. With the rapid development of MGs, plug-in hybrid electric vehicles (PHEVs) are gaining increasing attention since they can alleviate pollution and reduce energy consumption. The appearance of PHEVs would exacerbate the power supply shortages and bring new challenges to the power system. This paper develops an effective day-ahead optimal scheduling of a MG, taking into account RESs, storage devices and PHEVs. The Monte Carlo simulation is utilized to model the uncertainties of PHEVs. A smart charging/discharging strategy incorporating the V2G technique is proposed to smooth the demand curve and reduce the operational costs. To handle the MG scheduling problem in the presence of PHEVs, an improved sine cosine algorithm with simulated annealing based local search operator and chaotic opposition learning strategy (CSCASA) is proposed to minimize the total costs. The proposed algorithm can keep a better balance between global and local search abilities. CSCASA is first validated on some benchmark problems. Then, CSCASA is employed to generate optimal schedule of a grid-connected MG with PHEVs. The experimental results demonstrate the superior performance of CSCASA in the optimal MG scheduling problem with and without PHEVs.http://dx.doi.org/10.4316/AECE.2024.01005energy managementmicrogridsoptimization methodsrenewable energy sourcesscheduling
spellingShingle QIU, C.
An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
Advances in Electrical and Computer Engineering
energy management
microgrids
optimization methods
renewable energy sources
scheduling
title An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
title_full An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
title_fullStr An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
title_full_unstemmed An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
title_short An Improved Sine Cosine Algorithm for the Day-ahead Microgrid Management in the Presence of Electric Vehicles
title_sort improved sine cosine algorithm for the day ahead microgrid management in the presence of electric vehicles
topic energy management
microgrids
optimization methods
renewable energy sources
scheduling
url http://dx.doi.org/10.4316/AECE.2024.01005
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