需要応答と電力・炭素取引を考慮したアクティブ配電網の低炭素計画
Low-Carbon Planning of Active Distribution Networks Considering Demand Response and Electricity-Carbon Trading (原題)
Li-Xiang Lin, Chang Xu, Chen-Xi Zhang, Yuan-Liang Zhang, Tian-Yang Zhao, Qi-Ling Zhou, Jin-Ping Zhang, Xiang-Bang Cheng, Wei Jia
🤖 gxceed AI 要約
日本語
本論文は、需要応答（DR）、蓄電池（BESS）計画、電力・炭素取引（ECT）を協調させるアクティブ配電網の低炭素計画手法を提案する。動的な購入電力炭素排出係数をECTコストと炭素排出目的に導入し、年間総コスト・電圧偏差・購入炭素排出量の三目的最適化をC-TAEAで解く。中国昆明の季節代表日を用いたIEEE 33バス系統のケーススタディで、電圧偏差40.22%減、ネットワーク損失25.25%減、購入炭素排出量51.09%減を達成した。
English
This paper proposes a low-carbon planning method for active distribution networks coordinating demand response (DR), battery storage (BESS) planning, and electricity–carbon trading (ECT). A dynamic grid-purchased carbon emission factor is embedded in the ECT cost and carbon objective, forming a three-objective optimization solved with C-TAEA. Case studies on the IEEE 33-bus system using Kunming, China seasonal data show 40.22% lower voltage deviation, 25.25% lower network losses, and 51.09% lower purchased carbon emissions.
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
炭素排出係数を電力取引コストに組み込む手法は、日本における電力市場と炭素市場の連携設計や、SSBJのScope 2排出量算定における市場ベース手法の精緻化に示唆を与える。配電網レベルでのDR・蓄電池・炭素取引の統合最適化は、地域電力会社の脱炭素投資計画に実務的な参考となる。
In the global GX context
The integration of a dynamic grid carbon emission factor into electricity trading costs offers a quantitative framework relevant to emerging carbon pricing and electricity market coupling debates under ISSB/TCFD disclosure. It demonstrates how distribution-level planning can operationalize Scope 2 decarbonization and renewable accommodation, informing transition finance and grid investment decisions.
👥 読者別の含意
🔬研究者:配電網計画と炭素取引を統合した多目的最適化のモデリング手法と、動的炭素排出係数の導入方法を参考にできる。
🏢実務担当者:需要応答・蓄電池・炭素取引を組み合わせた配電網運用が、電圧品質改善と炭素排出削減を両立し得ることを投資計画の根拠にできる。
🏛政策担当者:電力・炭素市場の連携設計や、配電網レベルでの脱炭素インセンティブ制度の検討に活用できる。
📄 Abstract（原文）
: This paper proposes a low-carbon planning method for active distribution networks (ADNs) that coordinates demand response (DR), battery energy storage system (BESS) planning, and electricity–carbon trading (ECT). A multi-period BESS model is developed for siting, sizing, and state-of-charge operation, while DR is modeled via a time-of-use tariff and price-elasticity matrix to shift flexible demand across peak, flat, and valley periods. A dynamic grid-purchased carbon emission factor is introduced into the ECT cost formulation and carbon emission objective, forming a constrained three-objective optimization model that minimizes annual comprehensive cost, voltage deviation, and purchased carbon emissions. The constrained two-archive evolutionary algorithm (C-TAEA) is applied to obtain the Pareto solution set, and a compromise solution is selected via the analytic hierarchy process. Case studies are performed on the IEEE 33-bus system using four weighted typical seasonal days from Kunming, China to represent annual operation. For the selected solution, voltage deviation decreases by 40.22% (from 0.020774 to 0.012418 p.u.), annual network loss reduces by 25.25% (from 306.94 to 229.44 MWh), daily load fluctuation drops by 16.22% (from 9.3479 to 7.8320 MW/day), and wind-PV curtailment falls from 1.31 to 0 MWh/year. Notably, annual grid-purchased carbon emissions decrease from 12,295.95 to 6014.19 tCO 2 /year with a reduction rate of 51.09%. These results verify that coordinated DR and BESS operation can simultaneously improve voltage quality, reduce network losses, smooth load profiles, enhance renewable accommodation, and achieve significant decarbonization under the ECT mechanism.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://www.techscience.com/files/onlinefirst/2026/10.13/TSP_EE_89828/TSP_EE_89828.pdffirst seen 2026-10-18 05:08:42 · last seen 2026-11-06 05:19:23
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