A Metaheuristic Approach to Analyze the Techno-Economical Impact of Energy Storage Systems on Grid-Connected Microgrid Systems Adapting Load-Shifting Policies

Battery energy storage systems (BESSs) and plug-in hybrid electric vehicles (PHEVs) are essential for microgrid operations to be financially viable. PHEVs can serve as mobile storage devices, storing excess energy during times of low demand and delivering it during times of high demand. By offering reliable on-site energy storage, BESSs improve cost efficiency by allowing the microgrid to store cheap, off-peak electricity and release it when prices increase. To minimize generation costs and alleviate grid stress during periods of high demand, load-shifting policies shift inelastic loads to off-peak hours when energy prices are lower. When combined, these tactics support dependable, affordable, and effective microgrid management. A recently developed RIME algorithm is used as the optimization tool to reduce the total operating cost (TOC) of an MG system for three cases and three situations. The cases emphasize a modified load demand style influenced by the optimal load-shifting method (OLSM) and order characteristics load-shifting policy (OCLSP), whereas the situations refer to the inclusion of ESS in the MG system. The TOC decreased from $2624 without ESS to $2611 and $2331 with PHEVs and BESSs, respectively. These costs were further reduced to $1192, $1162, and $1147, respectively, when OLSM was implemented to restructure the base load demand. Additionally, a balance between a minimal TOC and carbon emission was obtained when an OLSM-based load demand model was used with BESSs. The RIME algorithm outperformed many recently developed algorithms and is consistent and robust, yielding better quality solutions.

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Publication Details

Journal
Processes
Published
2024-12-31
DOI
https://doi.org/10.3390/pr13010065
Citations
7
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
2.30

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article

A Metaheuristic Approach to Analyze the Techno-Economical Impact of Energy Storage Systems on Grid-Connected Microgrid Systems Adapting Load-Shifting Policies

Mukovhe Ratshitanga, Senthil Krishnamurthy, Bishwajit Dey, Nande Fose et al.
7 citations
Processes
Microgrid Control and Optimization
2.30
article

A Metaheuristic Approach to Analyze the Techno-Economical Impact of Energy Storage Systems on Grid-Connected Microgrid Systems Adapting Load-Shifting Policies

Mukovhe Ratshitanga, Senthil Krishnamurthy, Bishwajit Dey, Nande Fose, Prathaban Moodley
article en
7 citations

Abstract

Battery energy storage systems (BESSs) and plug-in hybrid electric vehicles (PHEVs) are essential for microgrid operations to be financially viable. PHEVs can serve as mobile storage devices, storing excess energy during times of low demand and delivering it during times of high demand. By offering reliable on-site energy storage, BESSs improve cost efficiency by allowing the microgrid to store cheap, off-peak electricity and release it when prices increase. To minimize generation costs and alleviate grid stress during periods of high demand, load-shifting policies shift inelastic loads to off-peak hours when energy prices are lower. When combined, these tactics support dependable, affordable, and effective microgrid management. A recently developed RIME algorithm is used as the optimization tool to reduce the total operating cost (TOC) of an MG system for three cases and three situations. The cases emphasize a modified load demand style influenced by the optimal load-shifting method (OLSM) and order characteristics load-shifting policy (OCLSP), whereas the situations refer to the inclusion of ESS in the MG system. The TOC decreased from $2624 without ESS to $2611 and $2331 with PHEVs and BESSs, respectively. These costs were further reduced to $1192, $1162, and $1147, respectively, when OLSM was implemented to restructure the base load demand. Additionally, a balance between a minimal TOC and carbon emission was obtained when an OLSM-based load demand model was used with BESSs. The RIME algorithm outperformed many recently developed algorithms and is consistent and robust, yielding better quality solutions.

ProcessesVol. 13(1)
Cape Peninsula University of Technology (ZA), South African National Energy Development Institute (ZA)
Cape Peninsula University of Technology
Affordable and clean energy
Openalex Percentile: Top 11%
Microgrid Control and Optimization
2.30
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