ハイブリッドマイクログリッドの持続可能なサイジング,配送,およびレジリエンスプランニングは,Arctic Puffin Optimizationを使用しています
Ahmed H Yakout1, Amr S Mashaal2, Adel M Alfons2
1Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt. ahmed.yakout@eng.asu.edu.eg.
Scientific reports
|February 22, 2026
まとめ
この研究は,ハイブリッドマイクログリッドの設計,コンポーネントサイズとエネルギー配送の最適化,コストと排出量を削減し,孤立した地域における信頼性の高い電力供給を確保するために,北極パフィン最適化 (APO) フレームワークを導入します.
科学分野:
- 再生可能エネルギーシステム
- オプティマイゼーション アルゴリズム
- テクノ・エコノミック・アナリスト
背景:
- PV,WT,DG,BESSを備えたハイブリッドマイクログリッドは,孤立した地域でも信頼性の高い低炭素エネルギーを提供します.
- 最適なサイズと配送は,再生可能エネルギーの断続性,バッテリーの劣化,および経済環境のトレードオフのために複雑です.
研究 の 目的:
- 独立したハイブリッドマイクログリッドの技術的経済計画のための新しい北極パフィン最適化 (APO) ベースの枠組みを提案する.
- 年間システムコスト (ASC),CO2排出量,および電力供給の損失確率 (LPSP) を同時に最小限に抑える.
主な方法:
- APOアルゴリズムを使用して,統合されたコンポーネントサイズと配送最適化.
- システムの複雑さを管理するための適応的な制約処理.
- 1時間毎の太陽光,風力,負荷データを用いた実用ケーススタディを用いた検証.
主要な成果:
- APOはGWO,ALO,SFOAを上回り,ASCを8%低く,再生可能エネルギーの浸透率を17%高めました.
- このフレームワークでは,LPSPがゼロとなり,信頼性が向上しました.
- 感受性分析は,さまざまな条件下で最適化された構成の堅実性を確認しました.
結論:
- APOベースのフレームワークは,ハイブリッドマイクログリッドの技術経済計画のための堅牢で効率的な方法を提供します.
- オフグリッドアプリケーションの現実的で,経済的に実行可能で,環境に配慮したシステム設計を保証します.
- このアプローチは,コスト,排出量,および信頼性の目標を効果的にバランスします.
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