低炭素・経済・安全目標と蓄電市場駆動を協調する二層型電源・蓄電協調計画手法
Two-Layer Source–Storage Coordinated Planning Method Coordinating Low-Carbon Economic Security Objectives and Energy Storage Market Driving (原題)
Gang Lü, Bo Yuan, Wenying Liu
🤖 gxceed AI 要約
日本語
新電力システムにおける電源・蓄電協調計画のための二層最適化モデルを提案。上層で投資コストと炭素排出量を最小化し、下層で運用コストと蓄電市場収益を最適化する。NSGA-IIによる反復解法で、有効・無効電力市場の結合効果を考慮。New England 39母線系統でのシミュレーションにより、市場駆動を考慮すると新エネ導入容量が55%増加し、出力抑制率は1.7%に低減することを実証。
English
This paper proposes a two-layer optimization model for source-storage coordinated planning in new power systems. The upper layer minimizes investment cost and carbon emissions, while the lower layer optimizes operation cost and storage market revenue. Using NSGA-II, the model captures the coupling of active and reactive power markets. Simulations on the New England 39-bus system show that market-driven storage increases renewable capacity by 55% and reduces curtailment to 1.7%.
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
日本の電力システム改革や再エネ大量導入の進展に伴い、蓄電設備の市場参加と計画の統合が重要となっている。本手法は、容量市場や需給調整市場など日本の市場設計にも応用可能な知見を提供し、SSBJやGX経済移行債の下での電力部門の脱炭素投資計画に示唆を与える。
In the global GX context
As power systems globally integrate higher shares of renewables, coordinated planning of generation and storage with market mechanisms is critical. This method demonstrates how storage market participation can enhance renewable deployment and reduce curtailment, offering insights for capacity markets and system planning under ISSB-aligned transition plans.
👥 読者別の含意
🔬研究者:Provides a novel two-layer optimization framework that integrates low-carbon, economic, and security objectives with storage market dynamics, useful for power system planning research.
🏢実務担当者:Offers a planning tool for utilities and grid operators to optimize storage investments and market participation, potentially improving renewable integration and cost efficiency.
🏛政策担当者:Highlights the value of market mechanisms for storage in achieving renewable targets, informing capacity market design and decarbonization policy.
📄 Abstract（原文）
In the new-type power system, the traditional generation planning paradigm has shifted to a new paradigm of source–storage collaborative planning. However, source–storage coordinated planning is facing deep-seated structural challenges of unbalanced multi-objective coordination and insufficient adaptability to market mechanisms. This paper first designs a source–storage coordinated planning framework with a two-layer structure of planning decision-making and operation verification, which takes into account multiple low-carbon, economic, and security planning objectives, and considers the dual market driving of energy storage participating in active-power and reactive-power regulations. Secondly, a two-layer optimal planning model is constructed: the upper-layer aims at minimizing the investment cost of new source–storage and minimizing annual carbon emissions, while the lower-layer aims at minimizing the comprehensive operation cost and maximizing the revenue of the energy storage market. The feature of this model is that it can simultaneously consider the coupling effect of the active-power market and the reactive-power market. Thirdly, a two-layer closed-loop iterative solution method based on Non-dominated Sorting Genetic Algorithm II is adopted to generate the source–storage coordinated planning scheme. Finally, simulation calculations are performed on the modified New England 39-bus system. The results show that, when considering the market driving of energy storage in both active-power and reactive-power regulations, the installed capacity of new energy reaches 465 MW, which is 55% higher than that in the no-market scenario, while the renewable energy curtailment rate is only 1.7%. The correctness and effectiveness of the proposed two-layer source–storage coordinated planning method in this paper are verified.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/pr14162607first seen 2026-08-19 04:41:35
🔔 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。