Shared energy storage helps lower user investment costs and enhances energy efficiency,which is considered a pivotal driver in accelerating the green transition of energy sectors.In view of the increasing demand for h...Shared energy storage helps lower user investment costs and enhances energy efficiency,which is considered a pivotal driver in accelerating the green transition of energy sectors.In view of the increasing demand for hydrogen,this paper proposes a bi-level optimization of configurations and scheduling for combined cooling,heating,and power(CCHP)microgrid systems considering shared hybrid electric-hydrogen energy storage service.The upper-level model addresses the capacity allocation problem of energy storage stations,while the lower-level model optimizes the operational strategies for the multi-microgrid system(MMS).To resolve the complexity of the coupled bi-level problem,Karush-Kuhn-Tucker(KKT)conditions and the Big-M method are applied to reformulate it into a solvable mixed-integer linear programming(MILP)model,compatible with CPLEX.The economic viability and rationality of the proposed approach are verified through comparisons of three cases.Numerical results show that the proposed approach reduces user annual costs by 20.15%compared to MMS without additional energy storage equipment and achieves 100%renewable absorption.For operators,it yields 5.71 M CNY annual profit with 3.02-year payback.Compared to MMS with electricity sharing,it further cuts user costs by 3.84%,boosts operator profit by 60.71%,and shortens payback by 15.88%.展开更多
文摘Shared energy storage helps lower user investment costs and enhances energy efficiency,which is considered a pivotal driver in accelerating the green transition of energy sectors.In view of the increasing demand for hydrogen,this paper proposes a bi-level optimization of configurations and scheduling for combined cooling,heating,and power(CCHP)microgrid systems considering shared hybrid electric-hydrogen energy storage service.The upper-level model addresses the capacity allocation problem of energy storage stations,while the lower-level model optimizes the operational strategies for the multi-microgrid system(MMS).To resolve the complexity of the coupled bi-level problem,Karush-Kuhn-Tucker(KKT)conditions and the Big-M method are applied to reformulate it into a solvable mixed-integer linear programming(MILP)model,compatible with CPLEX.The economic viability and rationality of the proposed approach are verified through comparisons of three cases.Numerical results show that the proposed approach reduces user annual costs by 20.15%compared to MMS without additional energy storage equipment and achieves 100%renewable absorption.For operators,it yields 5.71 M CNY annual profit with 3.02-year payback.Compared to MMS with electricity sharing,it further cuts user costs by 3.84%,boosts operator profit by 60.71%,and shortens payback by 15.88%.
