Blockchain and Zero‐Sum Game‐Based Energy Trading Scheme for Optimal EV Charging
ブロックチェーンとゼロサムゲームに基づく最適なEV充電のためのエネルギー取引スキーム (AI 翻訳)
Riya Kakkar, Smita Agrawal, Sudeep Tanwar
🤖 gxceed AI 要約
日本語
本論文では、電気自動車（EV）の充電スケジューリングを最適化するために、ハイブリッドゲーム理論とブロックチェーンを組み合わせた手法を提案する。ステージ1では連合ゲームによりEVのクラスターを形成し、ステージ2ではゼロサムゲームにより最適なペアを選択する。ブロックチェーンを用いて取引の安全性を確保し、Pythonシミュレーションにより有効性を確認した。
English
This paper proposes a hybrid game theory and blockchain approach for optimal EV charging scheduling. Stage 1 uses coalition games to form EV clusters, and Stage 2 applies zero-sum game to select the optimal pair. Blockchain secures transactions, and Python simulations validate the effectiveness.
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EV普及に伴い、充電インフラの効率的運用が課題となっている。本手法は、ブロックチェーンを用いた安全なエネルギー取引とゲーム理論による充電最適化を提供し、日本のEV充電ネットワークの信頼性向上に寄与する可能性がある。
In the global GX context
Globally, the integration of blockchain and game theory in EV charging aligns with trends in decentralized energy systems and smart grids. This work offers a technical framework for efficient and secure charging coordination, relevant to regions expanding EV infrastructure.
👥 読者別の含意
🔬研究者:Researchers interested in game theory and blockchain applications for EV charging can explore the hybrid approach and its simulation results.
🏢実務担当者:Practitioners in energy trading or charging station management can consider the scheme for secure and efficient EV scheduling.
📄 Abstract（原文）
In recent years, the growth and popularity of electric vehicles (EVs) has soared owing to the facilitation of zero‐emission carbon for people commuting on the road, preserving the environment from air pollution and hazardous gases. However, uncertain EV energy demands and their dynamic arrival times impact the ancillary operations and stability of the charging station (CS). Thus, it becomes a challenging task to schedule EVs for charging with their dynamic charging prices, traveling time, and waiting time efficiently and optimally. Thus, we propose an optimal EV selection scheme for trustworthy charging by implementing the hybrid game theory. The hybrid game theory is bifurcated into stage 1 and stage 2, in which stage 1 includes a coalition game to generate EV clusters or coalitions based on the parameters of state‐of‐charge (SoC), energy demand, and penalty factor. Then, the trust values are determined to select the EV pair fairly. Furthermore, stage 2 highlights the zero‐sum game theory, which aims to optimize the payoff at saddle point and formulate strategies for EV pair (generated in stage 1), ensuring the optimal EV selection for trustworthy charging. Moreover, we have utilized the blockchain network to secure the EV optimal payoff by implementing smart contract in Remix Integrated Development Environment (IDE). The hybrid game theory ensures the optimal and efficient EV selection using coalition game to select EV pair then apply zero‐sum game to optimize the payoff at saddle point condition. Next, we implement the hybrid game theory in Python 3.9 to simulate the results with the help of various factors such as trust value comparison, profit comparison based on strategies, convergence comparison, and profit comparison with the traditional approach.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/est2.70316first seen 2026-05-05 22:50:26
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