Optimal Dispatch in Hybrid PV/Diesel/Hydro/Battery Energy Storage Systems for Minimizing Power Losses, CO2 Emissions and Operating Cost
ハイブリッドPV/ディーゼル/水力/バッテリーエネルギー貯蔵システムにおける電力損失、CO2排出、運用コスト最小化のための最適運用 (AI 翻訳)
Kakule Mathe C, Kimani Irungu G, Ikuzwe A
🤖 gxceed AI 要約
日本語
本研究は、IEEE 30バスシステムを対象に、政策目標（損失8%以下、CO2削減40%以上、コスト削減20%以上）を組み込んだMINLP最適運用フレームワークを提案。太陽光・水力・ディーゼル・バッテリーのハイブリッドシステムにおいて、損失半減、排出40%削減、コスト20%削減を実現し、パレート最適解がグローバル政策目標と一致することを示した。
English
This study proposes a policy-embedded MINLP dispatch framework for a hybrid PV/diesel/hydro/battery system on the IEEE 30-bus system, targeting losses ≤8%, CO2 reduction ≥40%, and cost reduction ≥20%. Results show these thresholds are feasible with losses halved, emissions cut by 40%, and costs lowered by 20%. Pareto analysis confirms that global policy targets align with achievable trade-offs.
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
本論文は日本の再エネ導入拡大や地域マイクログリッド設計に示唆を与えるが、SSBJや有報などの開示制度との直接的な関連は薄い。日本でも離島や山間部でのハイブリッドシステム設計の参考として有用。
In the global GX context
This paper contributes to the technical literature on hybrid renewable system optimization, offering a replicable benchmark that aligns dispatch modeling with global sustainability targets. While not directly tied to TCFD/ISSB disclosures, it provides quantitative evidence that policy-driven emission and cost caps can be operationalized in grid operations.
👥 読者別の含意
🔬研究者:Provides a novel MINLP framework with policy-embedded constraints and a reproducible benchmark for hybrid system design.
🏢実務担当者:Offers actionable design insights for grid operators deploying PV/hydro/battery/diesel systems with explicit emission and cost targets.
🏛政策担当者:Demonstrates that global CO2 reduction targets (≥40%) are technically achievable in hybrid dispatch, supporting evidence-based policy setting.
📄 Abstract（原文）
The increasing penetration of renewable energy sources demands dispatch strategies that balance technical reliability, environmental sustainability, and economic efficiency. While Hybrid Photovoltaic/Hydro/Diesel/Battery Energy Storage (BESS) systems have been studied, most existing works focus on single-objective optimization or genetic multi-objective trade-offs without explicit integration of global sustainability thresholds. This study introduces a novel policy-embedded Mixed Integer Nonlinear Programming (MINLP) dispatch framework that embeds policy-aligned constraints (losses ≤ 8%, CO₂ reduction ≥ 40%, and cost reduction ≥ 20%) directly into the optimization model of the IEEE 30-bus system. Unlike prior studies, the framework establishes a replicable benchmark for hybrid generator placement and sizing, combining renewable-first dispatch logic with explicit emission and cost caps.Results demonstrate that policy thresholds are achievable within technical feasibility, with losses halved, emissions reduced by over 40%, and costs lowered by 20%. Pareto frontier analysis reveals that global policy targets coincide with the frontier of achievable trade-offs, providing new evidence that sustainability agendas can be operationalized in dispatch optimization. This contribution advances hybrid system research by bridging technical modeling with global energy policy, offering actionable insights for grid operators, policymakers, and researchers. By systematically locating PV+BESS at Bus 19/30, Hydropower at Bus 6/11 and Diesel at Bus 2/5, the study provides a reproducible design logic that future researchers can adopt. This benchmark moves beyond abstract optimization to offer a practical system design contribution.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202605.1013.v1first seen 2026-05-21 04:22:09 · last seen 2026-05-29 04:22:22
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