Integrated Optimization and Game Theory Framework for Fair Cost Allocation in Community Microgrids
K. Victor Sam Moses Babu, Pratyush Chakraborty, Mayukha Pal

TL;DR
This paper introduces a combined optimization and game theory framework for fair cost sharing in community microgrids, improving efficiency and participant satisfaction through equitable benefit distribution.
Contribution
It presents a novel integrated approach using mixed-integer programming and Shapley value analysis for fair, efficient microgrid cost allocation, validated with real-world data.
Findings
Peak demand reductions of 7.8% to 62.6%
Solar utilization rates up to 114.8%
Cooperative gains of up to $1,801.01 per day
Abstract
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…
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Taxonomy
TopicsSmart Grid Energy Management · Microgrid Control and Optimization · Electric Vehicles and Infrastructure
