Optimal trading strategy for community-based photovoltaic prosumers: Harnessing shared energy storage and dual incentive-driven response

This study investigates the optimal market trading strategy for community-based photovoltaic (PV) prosumers by leveraging shared energy storage (SES) and controllable loads. Specifically, a joint optimization framework is proposed for the community-based PV prosumers, combining resource configuration and market decision-making; concurrently, load resource configuration is modeled using a dual-incentive mechanism. Considering the multi-time scale characteristics of PV-storage-load resources, a bi-level optimal trading model is developed. The upper level determines the optimal annual capacity configurations of both the SES and controllable loads under typical scenarios, while the lower level optimizes seasonal power declarations, daily storage strategies, and incentive-driven load responses. An economic allocation model factoring the SES recovery preference is introduced for cooperative profit-sharing among PV prosumers, ensuring market participation of every prosumer. Comparisons and analyses of different case scenarios demonstrate that the proposed model increases annual revenue by 15.06 % compared to a baseline model without controllable resources. Moreover, simulation results confirm that the proposed approach can effectively enhance the market competitiveness of PV prosumers and enable equitable distribution of shared profits.