Bi-Level Optimal Planning of Soft Open Points Integrated with Energy Storage in Distribution Networks Considering Dynamic Electro-Carbon Factors
動的電気・炭素要因を考慮した配電網におけるエネルギー貯蔵統合型ソフトオープンポイントの二段階最適計画 (AI 翻訳)
K. Cheng, Haitao Liu, Yu Ji, Changjun Jiang, Nan Zheng, Geng Niu
🤖 gxceed AI 要約
日本語
本研究は、再生可能エネルギー高普及配電網における電気・炭素連携の深化と柔軟性不足に対処するため、動的電気・炭素要因を考慮した二段階協調計画戦略を提案する。上部計画ではE-SOPの最適配置・容量決定を行い、下部計画では動的段階的炭素取引メカニズムと連続価格ベース需要応答を導入する。改良IEEE33ノードシステムでのケーススタディにより、年間総コスト12.3%削減と炭素取引支出を純収益に転換できることを実証した。
English
This paper proposes a bi-level collaborative planning strategy for soft open points integrated with energy storage (E-SOP) in distribution networks, considering dynamic electro-carbon factors. The upper level optimizes siting and sizing to minimize annualized cost; the lower level incorporates a dynamic stepped carbon trading mechanism and price-based demand response. Case studies on an IEEE 33-node system show 12.3% cost reduction and carbon trading net revenue.
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
日本では再生可能エネルギーの導入拡大に伴い配電網の柔軟性確保と炭素価格メカニズムの統合が課題となっている。本論文の動的炭素取引と需要応答を組み合わせた二段階計画手法は、日本の配電事業者や系統運用者にとって低炭素化と経済性の両立に向けた実践的知見を提供する。
In the global GX context
This paper contributes to global discourse on low-carbon distribution system planning by embedding a dynamic carbon trading mechanism into a bi-level optimization framework. The novel approach of converting carbon expenditure into net revenue through coordinated planning of E-SOPs and demand response offers insights for utilities in carbon-constrained jurisdictions.
👥 読者別の含意
🔬研究者:Proposes a bi-level optimization framework integrating dynamic carbon trading and demand response for distribution network planning, relevant for researchers in power system decarbonization.
🏢実務担当者:Distribution system operators can use the methodology to evaluate E-SOP deployment and carbon trading strategies for cost-effective low-carbon operations.
🏛政策担当者:Demonstrates how carbon pricing mechanisms can be operationalized at the distribution level, informing policy design for carbon market integration in power systems.
📄 Abstract（原文）
To address the deepening electro-carbon coupling and flexibility shortages in active distribution networks with high renewable energy penetration, this paper proposes a bi-level collaborative planning strategy considering dynamic electro-carbon factors. First, considering the spatial–temporal correlation of wind and solar outputs, typical renewable energy scenarios are generated using the Frank-Copula function and clustering algorithms. Second, a bi-level planning model for the Soft Open Point integrated with an Energy Storage System (E-SOP) is established: the upper level optimizes the siting and sizing of E-SOPs to minimize the annualized comprehensive cost; the lower level incorporates a dynamic stepped carbon trading mechanism and a continuous price-based demand response (PBDR) mechanism to achieve optimal operational economy. For model solving, a hybrid bi-level decomposition strategy combining the Dhole Optimization Algorithm (DOA) and second-order cone programming (SOCP) is adopted, utilizing a coordinated dual-level solution interaction to favorably support numerical stability. Case studies on a modified IEEE 33-node system demonstrate that the proposed scheme reduces the annualized comprehensive cost by 12.3% and transforms the carbon trading expenditure into a net revenue, thereby significantly enhancing the low-carbon economic efficiency and operational flexibility of the distribution network.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/electronics15122693first seen 2026-06-21 05:40:49
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