Author
Listed:
- Song, Xiaoling
- Wu, Han
- Zhang, Huqing
- Guo, Jianxin
- Zhang, Zhe
- Peña-Mora, Feniosky
Abstract
Utilizing shared energy storage services presents a viable solution for microgrids to manage the increasing integration of distributed energy resources in retail electricity markets. By optimizing time-varying pricing, it is possible to impact the internal operations of microgrids that involve shared energy storage through price signals, as electricity retailers seek to aid in the deregulation of retail markets. This paper presents a bi-level optimization model that captures the interactions between electricity retailers and microgrid operators. At the upper level, the electricity retailer’s objective is to maximize economic profits by making day-ahead hourly strategic pricing decisions in the retail market and determining electricity purchases in the wholesale market. Meanwhile, at the lower level, the microgrid operator aims to minimize total costs by coordinating energy storage services among multiple internal aggregators and making decisions in the retail market. The microgrid operator oversees the centralized day-ahead operation decisions between the shared energy storage operator and various aggregators. Each aggregator manages a specific number of prosumers/customers and shares energy storage facilities. To achieve an equilibrium solution for the pricing strategies of electricity retailers and the operational challenges faced by microgrid operators, a bi-level nested genetic algorithm is proposed. This algorithm aims to identify effective pricing strategies for the electricity retailer, which will encourage multiple aggregators to utilize shared energy storage systems within the microgrid. The findings indicate that the electricity retailer can boost their profits by a minimum of 48.8% by adopting the proposed pricing approach. Additionally, the direct incentives within the pricing strategies play a crucial role in motivating aggregators to participate in providing energy storage services, resulting in a 26.1% reduction in costs for the microgrid operator.
Suggested Citation
Song, Xiaoling & Wu, Han & Zhang, Huqing & Guo, Jianxin & Zhang, Zhe & Peña-Mora, Feniosky, 2025.
"Can retail electricity pricing promote microgrid operators to leverage shared energy storage services among internal aggregators?,"
Energy, Elsevier, vol. 314(C).
Handle:
RePEc:eee:energy:v:314:y:2025:i:c:s0360544224039380
DOI: 10.1016/j.energy.2024.134160
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