Hybrid Metaheuristic-Based Probabilistic Planning of Weak Power Grids with Renewable Generation and Hydrogen Energy Storage

再生可能エネルギーと水素エネルギー貯蔵を備えた弱電力系統のハイブリッドメタヒューリスティックに基づく確率的計画 (AI 翻訳)

Ayman Hussein Badawi, Mohamed M. Zakaria Moustafa, Mostafa S. Hamad, A. S. Abdel-Khalik, Ragi A. R. Hamdy

Energies📚 査読済 / ジャーナル2026-03-04#水素

DOI: 10.3390/en19051288

原典: https://doi.org/10.3390/en19051288

🤖 gxceed AI 要約

日本語

弱い送電網における風力・太陽光発電の大規模導入による不確実性と安定性問題に対処するため、グリーン水素エネルギー貯蔵システム(HESS)の確率的計画フレームワークを提案。FVSIとSSIに基づくセキュリティ制約を最適化ループに組み込み、炭素フットプリントと電力損失の最小化を図る。改良IEEE39母線システムでの検証により、PSOやGA/PSOベースライン比で9.2%および5.3%の炭素フットプリント改善を達成。HESS設計は電解槽296.9MW、燃料電池262.7MW、水素貯蔵28,012kgとなる。

English

Proposes a probabilistic planning framework for green hydrogen energy storage (HESS) in weak grids with high wind and solar penetration. Couples Monte Carlo power flow with voltage stability (FVSI) and system strength (SSI) constraints in the optimization loop to minimize life-cycle carbon footprint and losses. A hybrid metaheuristic (Whale + Osprey optimization) solves the problem. On a modified IEEE 39-bus system, achieves 22.16 Mt CO2eq/yr carbon footprint, improving 9.2% over PSO and 5.3% over GA/PSO, with HESS design of 296.9 MW electrolyzer, 262.7 MW fuel cell, and 28,012 kg H2 storage.

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

本論文は弱い系統における水素貯蔵の最適計画手法を示しており、日本の水素基本戦略や再生可能エネルギー大量導入時の系統安定性対策に参考となる。特に、電圧安定性指標（FVSI）と系統強度指標（SSI）を制約として扱う点が新しい。日本でも北海道などの弱い系統への適用が考えられるが、本論文はIEEE39母線システムを用いており、実際の日本系統への適用にはさらなる検討が必要。

In the global GX context

This paper contributes to the global literature on hydrogen storage for grid support by coupling renewable uncertainty with stability constraints in a unified optimization. The explicit minimization of carbon footprint aligns with GX goals, and the hybrid metaheuristic offers a methodological advance. While not directly addressing disclosure standards, it provides quantitative benchmarks for system planners integrating hydrogen into weak grids.

👥 読者別の含意

🔬研究者:Advances the state-of-the-art in probabilistic planning for hydrogen storage with security constraints; the hybrid metaheuristic and coupled stability indices are notable.

🏢実務担当者:Provides a concrete design framework for HESS sizing and siting in weak grids with high renewables; the reported numbers (296.9 MW electrolyzer etc.) offer benchmarks.

🏛政策担当者:Demonstrates the viability of hydrogen storage to mitigate stability issues from renewable integration, supporting policy for hydrogen infrastructure in weak grid areas.

📄 Abstract（原文）

The large-scale integration of wind turbine generators (WTGs) and photovoltaic (PV) generation increases operational uncertainty and can exacerbate stability limitations in weak transmission networks, motivating the use of green hydrogen energy storage systems (HESS). This paper presents a probabilistic planning framework for the joint siting and sizing of HESS to support hybrid WTG–PV integration under stochastic wind, solar irradiance, and load conditions. The proposed framework explicitly couples Monte Carlo-based probabilistic power flow with weak-grid security constraints by enforcing FVSI-based voltage-stability limits and an SSI-based system-strength requirement within the optimization loop, rather than treating these indices as post-analysis checks. The planning problem is formulated using a weighted-sum scalarization to minimize life-cycle carbon footprint and active power losses, subject to security constraints based on the Fast Voltage Stability Index (FVSI) and a system-strength constraint expressed through a System Strength Index (SSI). To solve the resulting constrained, nonlinear optimization problem, a sequential hybrid metaheuristic that couples Whale Optimization (exploration) with Osprey Optimization (exploitation) is developed. The framework is implemented in MATLAB using MATPOWER and evaluated on a modified IEEE 39-bus system. Simulation results report an annual carbon footprint of 22.16 Mt CO2eq/yr, an improvement of 9.2% and 5.3% relative to PSO and GA/PSO baselines, respectively, while increasing the weakest-bus SSI to 4.68 (bus 7). The resulting HESS design comprises a 296.9 MW electrolyzer, a 262.7 MW fuel cell, and 28,012 kg of hydrogen storage.

🔗 Provenance — このレコードを発見したソース

semanticscholar https://doi.org/10.3390/en19051288first seen 2026-05-15 19:41:30

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