Optimal Sizing of Marine Energy Microgrids under Resource Uncertainties
資源不確実性下における海洋エネルギーマイクログリッドの最適規模設定 (AI 翻訳)
Iwakin, Oluwabunmi, Villacres, Daniela, Gilan Nejad, Mehregan, Moazeni, Farrah, Khazaei, Javad, Banarjee, Arindam
🤖 gxceed AI 要約
日本語
本論文は、太陽光・風力・波力を統合した沿岸マイクログリッドの最適規模設定のための確率最適化フレームワークを提案する。資源変動性を考慮し、レベル化エネルギーコスト最小化と信頼性・環境持続性のトレードオフを分析。ニュージャージー州の海岸でのケーススタディにより手法の有効性を実証。
English
This paper proposes a stochastic optimization framework for optimal sizing of hybrid solar-wind-wave coastal microgrids, accounting for resource intermittency. It minimizes levelized cost of energy while ensuring reliability and environmental sustainability, demonstrated via a case study on the New Jersey shore.
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
日本でも洋上風力や波力発電の導入が進む中、沿岸マイクログリッドの設計手法は関連性が高い。ただし、日本の海域特性や系統連系要件に合わせた調整が必要。
In the global GX context
This study contributes to the global GX context by providing a robust design framework for renewable energy microgrids in coastal areas, supporting the transition away from fossil fuels. It is relevant for regions with high wave energy potential.
👥 読者別の含意
🔬研究者:A stochastic optimization method for hybrid renewable microgrid sizing under uncertainty, useful for further research in coastal energy systems.
🏢実務担当者:Provides a decision-support tool for planning cost-effective and reliable renewable microgrids in coastal communities.
📄 Abstract(原文)
Coastal microgrids powered by renewable energy sources offer sustainable and resilient solutions for meeting energy demands in geographically disadvantaged coastal regions. Their high complementarity makes them a cost-effective alternative to conventional energy sources, particularly with the growing interest in harnessing coastal wave energy through wave energy converters (WECs) to enhance renew- able energy penetration. However, the inherent variability of solar, wind, and wave resources introduces significant uncertainty in system design and operation, particularly at high penetration. This study presents a stochastic optimization framework for the optimal sizing of a hybrid solar-wind-wave coastal microgrid, accounting for resource intermittency and system constraints. The framework integrates a multi-period optimization strategy with a techno-environmental economic analysis to minimize the expected levelized cost of energy (LCOE) while ensuring system reliability and environmental sustain- ability via emissions costs. Key constraints, including resource availability, energy storage capacity, and operational limits, are incorporated to enhance the microgrid performance under diverse conditions. The effectiveness of the proposed methodology is demonstrated through case studies on a coastal microgrid in New Jersey Shore subject to varying climatic conditions. The findings highlight critical trade-offs between cost, reliability, and renewable energy utilization, providing valuable insights into the design of robust and adaptive microgrid systems. This study contributes to the development of resilient coastal energy infrastructures with well-informed technical specifications that can withstand uncertainties while promoting sustainability and reducing dependence on fossil fuels. Acknowledgement: This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Water Power Technlogies Office (WPTO) Award Number DE-EE00011379. The view expressed herein do not necessarily represent the view of the U.S. Department of Energy or the United States Government.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20534103first seen 2026-06-04 04:26:10 · last seen 2026-06-05 04:17:20
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。