Abstract
Prosumers’ deployment of distributed energy resources (DER) is shaped by market incentives and budget constraints. Effective DER integration can reduce the long-term need for distribution network infrastructure, thereby diminishing
overall electricity costs. Nevertheless, it may negatively impact cost allocation among users from different socioeconomic backgrounds. To analyze the efficiency and distributional aspects of DER deployment across different socioeconomic groups, this study employs a novel equilibrium model based on Stackelberg games. The model simulates interactions between a proactive low-voltage distribution network planner and prosumers who may invest in photovoltaic systems and batteries. Prosumers aim to minimize expenses based on tariffs, without knowledge of their peers’ decisions. Due to the non-linearities introduced by the tariff structure, a Gauss-Seidel algorithm is employed to reduce model complexity. The study examines six tariff combinations, revealing that cost allocation varies significantly depending on the tariff design. In this regard, the results show the risks associated with certain tariff designs, including potential losses in efficiency or unfair cost allocation. Likewise, the results highlight the value of cost-reflective tariffs in reducing unintended cross-subsidies. These findings underscore the importance of thoughtful tariff design and network planning in promoting both a distributional fairness DER deployment and system-wide efficiency.
overall electricity costs. Nevertheless, it may negatively impact cost allocation among users from different socioeconomic backgrounds. To analyze the efficiency and distributional aspects of DER deployment across different socioeconomic groups, this study employs a novel equilibrium model based on Stackelberg games. The model simulates interactions between a proactive low-voltage distribution network planner and prosumers who may invest in photovoltaic systems and batteries. Prosumers aim to minimize expenses based on tariffs, without knowledge of their peers’ decisions. Due to the non-linearities introduced by the tariff structure, a Gauss-Seidel algorithm is employed to reduce model complexity. The study examines six tariff combinations, revealing that cost allocation varies significantly depending on the tariff design. In this regard, the results show the risks associated with certain tariff designs, including potential losses in efficiency or unfair cost allocation. Likewise, the results highlight the value of cost-reflective tariffs in reducing unintended cross-subsidies. These findings underscore the importance of thoughtful tariff design and network planning in promoting both a distributional fairness DER deployment and system-wide efficiency.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Energy Markets, Policy and Regulation |
| DOIs | |
| Publication status | Published - 1 Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- bilevel programming
- distributed generation
- electricity tariffs
- prosumer
- Stackelberg games
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