Optimization configuration method for shared energy storage considering economic consumption of new energy

• Shared energy storage is planned and modeled in a regional micro energy grid cluster. • The new energy economy consumption index is first used in SES capacity allocation decisions. • A bi-level model considering two different time scales is established for SES station sizing and operation. • The impact of new energy consumption rates on SES configuration results is analyzed. • A comparative analysis reveals the proposed method’s feasibility and superiority. In the context of the energy internet, the integration of large-scale shared energy storage (SES) within regional multiple micro energy grids (MMEGs) can effectively enhance the cooperative consumption level of local new energy. To scientifically and rationally configure the parameters of SES systems with a moderate investment scale, this study proposes an SES capacity optimization configuration method that accounts for the economic consumption of new energy for the first time. Initially, the operational service model of the SES system under the interconnection of MMEGs is constructed, and its profitability mechanisms under the economic consumption index are analyzed. Subsequently, for a type of combined cooling, heating, and power micro energy grid cluster (CCHP-MEGC), a bi-level optimization configuration model considering two different time scales is established. The upper-layer model addresses the configuration issues of the SES station during the planning period, while the lower-layer model solves the economic consumption rate and optimization operation problems of the MMEGC system during the dispatch period. Lastly, through case analysis, the economic viability and effectiveness of the proposed configuration method are validated, and the impact of the new energy consumption rate on the SES configuration results is explored. The results demonstrate that compared to full new energy consumption, implementing a moderate power curtailment rate can effectively reduce the required configuration capacity of the SES system and the operational costs of the CCHP-MEGC system, while also shortening the payback period for the SES operator. The findings affirm that the optimal power and capacity of the SES serving multi-energy systems should strive to match the optimal new energy consumption targets to facilitate mutually beneficial outcomes for all participating entities.