Multi-Objective Residential Load Scheduling Approach Based Pelican Optimization Algorithm with Multi-Criteria Decision Making
The existing energy grid faces challenges in meeting the escalating energy demands driven by annual population growth and the proliferation of energy-consuming devices in the contemporary era. This research proposes an optimum multi-objective pelican optimization method for smart grid load control....
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| Published in: | Journal of engineering and sustainable development (Online) Vol. 29; no. 2; pp. 242 - 254 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
01.03.2025
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| ISSN: | 2520-0917, 2520-0925 |
| Online Access: | Get full text |
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| Summary: | The existing energy grid faces challenges in meeting the escalating energy demands driven by annual population growth and the proliferation of energy-consuming devices in the contemporary era. This research proposes an optimum multi-objective pelican optimization method for smart grid load control. The proposed algorithm effectively explores diverse solutions by minimizing customer energy costs and reducing peak loads for utility companies, identifying a Pareto front that represents optimal trade-offs among the three objectives: energy cost minimization, peak load reduction, and a third objective (user inconvenience). An ELimination ET Choix Traduisant la REalite (ELECTRE) method then rigorously ranks the Pareto-optimal solutions, guiding the selection of the most advantageous alternative that harmonizes the competing objectives. Energy bills are reduced by more than 42.66% using the proposed method. Additionally, the reduction in peak energy consumption by 20.66% has benefited the power suppliers for a sampling time of (30 minutes). When applied (60 minutes) sampling time, energy bills are reduced to 40.74 % and peak load to 30% with acceptable levels of inconvenience. Furthermore, the proposed load management provides 42.66 % and 20.66% cost and peak savings compared to other work in the state of the arts. |
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| ISSN: | 2520-0917 2520-0925 |
| DOI: | 10.31272/jeasd.2447 |