用博弈论公平分摊微电网成本,提升系统效率与用户满意度。
Integrated Optimization and Game Theory Framework for Fair Cost Allocation in Community Microgrids
- 结合优化调度与夏普利值分配收益,兼顾效率与公平。
- 实测峰值负荷降低7.8%至62.6%,太阳能利用率超114.8%。
- 适合研究微电网协同运行与公平激励机制的学者参考。
社区微电网中的公平成本分摊仍面临挑战,因多参与者负载特性、分布式能源及储能系统差异导致互动复杂。传统方法难以应对参与方贡献与收益的动态变化,易引发成本分配不公与参与度下降。本文提出一种融合多目标优化与合作博弈论的新型框架,通过混合整数线性规划实现资源最优调度,并利用夏普利值(Shapley value)进行收益公平分配,保障系统效率与参与者满意度。基于六种真实运行场景数据验证,结果表明峰值需求降幅达7.8%至62.6%,通过有效储能整合使太阳能利用率高达114.8%,每日协作收益最高达1,801.01美元。基于夏普利值的分配方案使各负载类型净收益分布于-16.0%至+14.2%之间,实现可持续合作。
原文摘要 · Abstract (English)
Fair cost allocation in community microgrids remains a significant challenge due to the complex interactions between multiple participants with varying load profiles, distributed energy resources, and storage systems. Traditional cost allocation methods often fail to adequately address the dynamic nature of participant contributions and benefits, leading to inequitable distribution of costs and reduced participant satisfaction. This paper presents a novel framework integrating multi-objective optimization with cooperative game theory for fair and efficient microgrid operation and cost allocation. The proposed approach combines mixed-integer linear programming for optimal resource dispatch with Shapley value analysis for equitable benefit distribution, ensuring both system efficiency and participant satisfaction. The framework was validated using real-world data across six distinct operational scenarios, demonstrating significant improvements in both technical and economic performance. Results show peak demand reductions ranging from 7.8% to 62.6%, solar utilization rates reaching 114.8% through effective storage integration, and cooperative gains of up to $1,801.01 per day. The Shapley value-based allocation achieved balanced benefit-cost distributions, with net positions ranging from -16.0% to +14.2% across different load categories, ensuring sustainable participant cooperation.
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