Fair Cost Allocation in Energy Communities: A DLMP-based Bilevel Optimization with a Shapley Value Approach

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Main Authors: Park, Hyeongon, Kwag, Kyuhyeong, Molzahn, Daniel K., Gupta, Rahul K.
Format: Preprint
Published: 2025
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author Park, Hyeongon
Kwag, Kyuhyeong
Molzahn, Daniel K.
Gupta, Rahul K.
author_facet Park, Hyeongon
Kwag, Kyuhyeong
Molzahn, Daniel K.
Gupta, Rahul K.
contents Energy communities (ECs) are emerging as a promising decentralized model for managing cooperative distributed energy resources (DERs). As these communities expand and their operations become increasingly integrated into the grid, ensuring fairness in allocating operating costs among participants becomes a challenge. In distribution networks, DER operations at the community level can influence Distribution Locational Marginal Prices (DLMPs), which in turn affect system's operation cost. This interdependence between local decisions and system-level pricing introduces new challenges for fair and transparent cost allocation. Despite growing interest in fairness-aware methods, most methods do not account for the impact of DLMPs. To fill this gap, we propose a bilevel optimization model in which a Community Energy Aggregator (CEA) schedules DERs across multiple ECs while a Distribution System Operator (DSO) determines DLMPs through network-constrained dispatch. Leveraging the Karush-Kuhn-Tucker (KKT) conditions and strong duality, the bilevel model is reformulated into a tractable single-level problem. We achieve fairness in the cost allocation by applying the Shapley value to quantify each community's marginal contribution to system-wide cost savings. The effectiveness of the proposed method is validated through simulations on several benchmark distribution systems.
format Preprint
id arxiv_https___arxiv_org_abs_2510_22321
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fair Cost Allocation in Energy Communities: A DLMP-based Bilevel Optimization with a Shapley Value Approach
Park, Hyeongon
Kwag, Kyuhyeong
Molzahn, Daniel K.
Gupta, Rahul K.
Systems and Control
Energy communities (ECs) are emerging as a promising decentralized model for managing cooperative distributed energy resources (DERs). As these communities expand and their operations become increasingly integrated into the grid, ensuring fairness in allocating operating costs among participants becomes a challenge. In distribution networks, DER operations at the community level can influence Distribution Locational Marginal Prices (DLMPs), which in turn affect system's operation cost. This interdependence between local decisions and system-level pricing introduces new challenges for fair and transparent cost allocation. Despite growing interest in fairness-aware methods, most methods do not account for the impact of DLMPs. To fill this gap, we propose a bilevel optimization model in which a Community Energy Aggregator (CEA) schedules DERs across multiple ECs while a Distribution System Operator (DSO) determines DLMPs through network-constrained dispatch. Leveraging the Karush-Kuhn-Tucker (KKT) conditions and strong duality, the bilevel model is reformulated into a tractable single-level problem. We achieve fairness in the cost allocation by applying the Shapley value to quantify each community's marginal contribution to system-wide cost savings. The effectiveness of the proposed method is validated through simulations on several benchmark distribution systems.
title Fair Cost Allocation in Energy Communities: A DLMP-based Bilevel Optimization with a Shapley Value Approach
topic Systems and Control
url https://arxiv.org/abs/2510.22321