An optimization model for low carbon electricity transition planning: a case study from India
低炭素電力系統への移行計画のための最適化モデル：インドのケーススタディ (AI 翻訳)
Varun Jyothiprakash, Balachandra Patil, Abhishek Das
🤖 gxceed AI 要約
日本語
本論文は、動的な供給と需要のバランスを取るための線形計画法に基づく最適化モデルを提案。インド・カルナータカ州の電力系統で検証し、実際よりも低コストで再生可能エネルギー利用率が高い結果を示した。柔軟性、計算効率、スケーラビリティに優れ、政策立案に有益。
English
This paper proposes a linear programming optimization model for balancing dynamic supply and demand in low-carbon electricity transition. Validated on Karnataka, India's power system, it achieves lower cost (Rs. 2.04/kWh vs. 2.13) and higher renewable utilization. The model is flexible, computationally efficient, and scalable, offering insights for policymakers.
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
インドの電力系統移行計画に関する実証研究だが、日本の電力自由化や再生可能エネルギー大量導入の計画策定にも応用可能なフレームワークを示している。特に、高時間解像度での需給バランス最適化は、日本の地域間連系線活用やVPP（仮想発電所）設計に示唆を与える。
In the global GX context
While focused on India, this optimization model addresses a universal challenge in electricity transition planning: balancing variable renewable supply with dynamic demand. Its emphasis on spatial and temporal resolution and computational efficiency is relevant for global grid operators and regulators, especially in emerging economies.
👥 読者別の含意
🔬研究者:Provides a novel, less data-intensive optimization model for electricity transition that can be adapted to other regions.
🏢実務担当者:Grid planners and utilities can use the model's hourly resolution approach to improve renewable integration and cost efficiency.
🏛政策担当者:Offers a quantitative tool to evaluate least-cost generation mixes and support policy decisions for low-carbon transition.
📄 Abstract（原文）
Introduction: Globally, achieving net-zero carbon is the new target set for energy systems. Consequently, the energy systems are undergoing a paradigm shift from least cost, robust, carbon-intensive, on-demand and firm power conventional systems to uncertain, intermittent, and variable renewable energy-integrated low-carbon electricity systems. Hence, the needs of planning and operations in transitioning electricity systems have changed from balancing “static supply with dynamic demand” to balancing “dynamic supply with dynamic demand”. Materials and methods: This study proposes a novel linear programming-based optimisation model as a tool for planning electricity system transitions. The objective is to balance dynamic supply with dynamic demand at minimum cost and address the inherent challenges of renewable energy (RE) integration. It is designed to evaluate the technical characteristics of various supply technologies, their temporal and spatial resource potential, availability, and economics, thereby curating the least-cost generation mix at hourly resolution. Results: The model has been validated on the electricity system of Karnataka, India, and the results were within an acceptable standard error of ±10%. The modelled system shows a lower economic cost of generation (Rs. 2.04/kWh) compared to the actual system performance (Rs. 2.13/kWh), in addition to higher utilisation of renewable resources than the actual system. Conclusions: The advantages of our proposed model over its counterparts are flexibility, simplicity, inter-operability, less data-intensive, higher computational efficiency, scalability, and the ability to integrate resource planning and socio-economic and environmental aspects, making it a valuable tool for electricity transition planning, offering critical insights for policymakers and planners.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.20935/acadenergy8383first seen 2026-06-29 05:13:47 · last seen 2026-06-29 05:13:48
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