This study establishes a bi-level operational optimization framework for distribution networks integrating distributed renewables, shared energy storage, and a P2P energy trading
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VDER has proven to be a valuable alternative to the wholesale market, due in large part to its fixed revenue components, high capacity revenue potential, and ability to facilitate shorter development
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User-side distributed energy storage has the ability to optimize user power load curve and coordinate renewable energy generation at the consumption system side. In this paper, a user
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As an emerging flexible resource in the power market, distributed energy storage systems (DESSs) play the dual roles of generation and consumption (Kalantar-Neyestanaki and Cherkaoui, 2021; Li et al., 2021), thereby complicating the market dynamics for energy storage users.
However, individual producers and prosumers are small in scale and often exist in a distributed form, making it difficult to effectively integrate resources . In recent years, shared energy storage mechanisms and peer-to-peer (P2P) trading markets have become important solutions to this problem .
As shown in Figure 1, the market participants primarily include prosumers, the DSO, and the shared energy storage systems managed by the DSO. Prosumers are users who possess both generation capacity and load demand, such as energy communities and industrial campuses.
Problem oriented. Achieve P2P energy trading between residential and commercial multi-energy prosumers with a generalized model including commonly used energy supply technologies and multiple demand-side management measures, e.g., demand response, electricity storage, and thermal storage. Method-oriented.
Energy storage systems can quickly store or release electricity, playing the role of “peak shaving and valley filling” for the power system. Therefore, prosumers can utilize energy storage devices to consume excess renewable energy or to fill the power gap when there is a shortage of renewable energy .
This can be an effective strategy for energy storage systems because it allows the system to capture the price difference between low and high electricity prices and can generate revenue for the system owner (Badanjak and Pandžić, 2021, Hussein et al., 2012).
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