負荷シフトに基づくデマンドサイドマネジメントを備えたペリカン最適化アルゴリズムを用いたマイクログリッドのエネルギー管理システム
An Energy Management System for Microgrid Using Pelican Optimization Algorithm with Demand Side Management Based on Load Shifting (原題)
Jamal S, Pasupuleti J, Maghami MR, Yaghoubi E
🤖 gxceed AI 要約
日本語
本研究は、マイクログリッドのエネルギー管理システム（EMS）を最適化し、運用コストを削減することを目的とする。ペリカン最適化アルゴリズム（POA）を用いて、再生可能エネルギー源と蓄電池の組み合わせ、および負荷シフトによるデマンドサイドマネジメント（DSM）の効果を検証した。シミュレーションの結果、蓄電池とDSMを併用したシナリオ4で最小コスト（11.889 USD）を達成し、POAは比較対象のアルゴリズムより優れた性能を示した。
English
This study optimizes a microgrid energy management system (EMS) to reduce operating costs. Using the Pelican Optimization Algorithm (POA), it evaluates combinations of renewable sources, battery storage, and demand-side management (DSM) via load shifting. Simulation results show that Scenario 4 (with battery and DSM) achieves the lowest cost (11.889 USD), and POA outperforms benchmark algorithms in all scenarios.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の再生可能エネルギー導入拡大と分散型電源の増加に伴い、マイクログリッドEMSの最適化は電力コスト削減と系統安定化に寄与する。本研究成果は、地域エネルギー管理や需給調整市場への応用が期待され、日本のエネルギー政策（第7次エネルギー基本計画）やカーボンニュートラル目標に沿うものである。
In the global GX context
Globally, this research contributes to the growing literature on microgrid optimization and demand-side flexibility, which are key to integrating high shares of renewables. The proposed algorithm offers a cost-effective solution for energy management, aligning with international efforts to achieve affordable and clean energy (SDG 7) and enhance grid resilience.
👥 読者別の含意
🔬研究者:Provides a novel optimization algorithm (POA) for microgrid EMS with DSM, offering a benchmark for future research.
🏢実務担当者:Offers a practical approach to reduce energy costs and improve renewable utilization in microgrid operations.
🏛政策担当者:Supports policies promoting distributed energy resources and demand-side management for grid stability and decarbonization.
📄 Abstract（原文）
<title>Abstract</title> <p>Microgrids (MGs) have recently emerged as a solution to enhance power network management. This study investigates strategies for optimizing MG generation and demand management to reduce overall operating costs. Optimizing the energy management system (EMS) controller is essential for identifying the most effective approach to dispatching available generation sources; thus, the Pelican Optimization Algorithm (POA) is developed based on a single-objective problem to achieve optimal scheduling of generation sources for the MG system. Moreover, Demand-Side Management (DSM) has been incorporated using a load shifting strategy to reduce MG energy costs. This study considers four distinct scenarios: (1) optimizing total operating costs with hybrid renewable energy sources (RES) without battery storage (BS); (2) optimizing costs with hybrid RES, no BS, and DSM through load shifting; (3) optimizing costs with hybrid RES and BS; and (4) optimizing costs with hybrid RES, BS, and DSM through load shifting. The simulation results demonstrate that the minimum cost using the proposed POA is achieved in Scenario 4 (11.889 USD). Furthermore, to examine the effectiveness of the proposed POA, two benchmark algorithms, namely the Bat Algorithm (BA) and the Differential Evolutionary Algorithm (DEA) have been considered. The simulation results indicate that the proposed POA outperforms both DEA and BA across all scenarios, achieving lower costs and faster convergence. The proposed EMS enables more efficient use of RES and demand-side flexibility, from a sustainable development perspective, to help achieve the sustainable development goals (SDGs) 7 which are affordable and clean energy goals.</p>
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.21203/rs.3.rs-10606671/v1first seen 2026-09-04 04:43:38 · last seen 2026-09-17 04:20:43
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