Multi-Objective BESS Siting and Sizing via NSGA-II and PTDF-Constrained DC Optimal Power Flow: Application to the Mali Transmission Network
NSGA-IIとPTDF制約付き直流最適潮流を用いたBESSの多目的立地・容量決定：マリ送電網への適用 (AI 翻訳)
Becerra AA, Fernández G, Egaña AR, Roncallo F, Mihetec M, Tsamba AJ, Matak N, Mahumane G
🤖 gxceed AI 要約
日本語
本論文は、マリの130母線送電網を対象に、蓄電池システム(BESS)の最適立地と容量を決定する多目的最適化フレームワークを提案。NSGA-IIを用いて収益最大化と電力損失最小化を同時に図り、Pareto最適解から支配的な立地を特定した。結果、SIRAKORO II変電所が最適と判明し、サブサハラ地域の再生可能エネルギー統合に有用な知見を提供する。
English
This paper proposes a multi-objective framework for optimal siting and sizing of Battery Energy Storage Systems (BESS) applied to the 130-bus Mali transmission network. Using NSGA-II and PTDF-constrained DC optimal power flow, it identifies Bus 91 (SIRAKORO II) as the dominant location, achieving daily revenue of ~€10,033 with minimal loss increment. The Pareto front provides a quantitative tool for balancing economic and environmental objectives in sub-Saharan energy transitions.
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
日本との直接的な関連は薄いが、途上国送電網における蓄電池導入の実証的枠組みとして、電力系統の安定化と再エネ統合の課題に取り組む日本の研究者・技術者に方法論的な示唆を与える。
In the global GX context
This paper demonstrates a practical, network-constrained BESS planning approach for weak grids in sub-Saharan Africa. While not directly applicable to developed grids, it offers a methodology for balancing investment returns and grid efficiency, relevant for global climate finance and energy access discussions.
👥 読者別の含意
🔬研究者:Useful methodology for multi-objective BESS planning in weak grid contexts.
🏛政策担当者:Provides insights for integrating storage in developing country transmission planning.
📄 Abstract（原文）
Expanding renewable energy capacity in sub-Saharan transmission systems is a cornerstone of sustainable development, yet weak grid infrastructure and the absence of flexible storage remain principal barriers to reliable and low-carbon energy access. This paper addresses the economic and environmental dimensions of that challenge by proposing a hierarchical multi-objective framework for the optimal siting and sizing of Battery Energy Storage Systems (BESS), applied to the 130-bus Mali transmission network within the EMERGE project. The upper level employs the NSGA-II evolutionary algorithm to simultaneously maximize daily price-arbitrage revenue—the economic sustainability indicator—and minimize active power losses—the environmental efficiency indicator. For each candidate design, the lower level solves a multi-period DC Optimal Power Flow (DC-OPF) via CasADi/IPOPT, with thermal branch constraints embedded as hard linear inequalities through the Power Transfer Distribution Factor (PTDF) matrix, and voltage-corrected loss estimates recovered via a vectorized Extended DC Power Flow (EDCPF) model. Over 500 NSGA-II generations, the framework identifies Bus 91 (SIRAKORO II, 150 kV) as the dominant storage location, achieving maximum daily revenue of approximately € 10,033 at a marginal loss increment of 6.7×10−3 MWh. The Pareto front provides Mali system planners with a quantitative tool for balancing private investment returns against grid-level environmental impact, demonstrating that rigorous network-constrained BESS planning is both technically tractable and economically viable in the resource-constrained context of sub-Saharan sustainable energy transitions.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202605.0797.v1first seen 2026-05-15 16:29:59 · last seen 2026-05-26 04:22:26
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