Synergistic simulation of carbon benefit optimization and economic benefits of grid investment based on digital twin modeling
デジタルツインモデリングに基づくグリッド投資のカーボン便益最適化と経済便益の相乗シミュレーション (AI 翻訳)
Wenli Zhu
🤖 gxceed AI 要約
日本語
本論文は、デジタルツインモデルを用いて電力グリッド投資におけるカーボン便益と経済便益の同時最適化をシミュレーションする。直接マッピング、計算マッピング、推論マッピングの3段階で物理モデルと仮想モデルを構築し、炭素排出コストや取引コストなどを考慮した最適化を行う。Pareto最適解による検証で、デジタルツインモデルは粒子群最適化やビッグデータ分析よりも短時間で高い炭素削減効果を示した。
English
This paper uses a digital twin model to simulate the synergistic optimization of carbon benefits and economic benefits for grid investment. It constructs physical and virtual mapping models at three levels, incorporating carbon emission costs, trading costs, and governance costs. The digital twin model outperforms particle swarm optimization and big data analysis in Pareto frontier validation, achieving higher carbon reduction in shorter time.
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、電力グリッドの脱炭素化と投資効率の両立が重要課題である。本論文のデジタルツインによるカーボン・経済の協調最適化手法は、日本の電力会社やグリッド運用者にとって、投資判断の高度化に応用可能な枠組みを提供する。
In the global GX context
In the global context, this paper presents a novel digital twin approach for co-optimizing carbon and economic outcomes in grid investment. It offers a practical framework for utility companies and grid operators to enhance investment decisions under carbon constraints, contributing to the broader energy transition literature.
👥 読者別の含意
🔬研究者:Researchers in energy system optimization and carbon accounting can leverage the proposed digital twin co-optimization methodology for further extension to other infrastructure sectors.
🏢実務担当者:Corporate sustainability and grid investment teams can use this model to assess and optimize the carbon and economic impacts of their investment portfolios.
🏛政策担当者:Policymakers can consider digital twin-based tools for evaluating grid investment policies that align with national carbon reduction targets.
📄 Abstract（原文）
This paper constructs a physical model of carbon benefits and economic benefits of grid investment, as well as a virtual mapping relationship model from three levels: direct mapping, computational mapping, and inferential mapping. Based on the minimization of energy consumption cost and considering the constraints of benefit matching degree, the economic co-optimization model is designed. With the maximization of economic benefits as the optimization goal, the virtual model is realized as a closed loop of simulation, evaluation, analysis and co-optimization calculation. With the digital twin model as the framework, carbon emission cost, carbon trading cost, carbon governance cost, and total carbon cost are calculated, and the carbon benefit architecture of power grid equipment is analyzed to achieve the optimization of investment carbon benefit, considering the uncertainty in the process of equipment operation. With the digital twin as the core of the platform, we realize the carbon - economic collaborative deduction, quantitative analysis and management, and the optimal scheme at the level of integrated co-simulation. In the optimal Pareto frontier validation, the digital twin model carbon emission reduction rises from 85.2 tons in 1 million yuan to 1923 tons in 31 million yuan, with a maximum time of 19.5 s, while the particle swarm algorithm and the big data analysis require a maximum time of 38.3 s and 40.7 s. The transmission process emission reduction benefits of the digital twin model, the particle swarm optimization, and the big data analysis for the transmission process in 2024 are 402/104, 239/104t, and 379/104t, which is comprehensively better than the comparison method, and verifies the feasible path to realize the synergistic gain of carbon benefit and economic benefit when the digital twin model is used.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.65102/is2026990first seen 2026-05-15 17:15:02
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