| Under the background of the new power system,energy storage has a wide range of applications in generation,transmission,distribution and utilization.However,its development still faces problems such as high investment costs and low equipment utilization.As a new paradigm for improving resource utilization efficiency and intensive development,shared energy storage provides a new solution to these problems.This paper focuses on the shortcomings of shared energy storage research under three modes: shared energy storage application for multiple ancillary services,centralized energy storage multi-user shared application,and user-owned distributed energy storage shared application.The research is carried out from the aspects of business model,optimal configuration,optimal scheduling,etc.The main contents are as follows:(1)Based on the shared energy storage application mode for multiple ancillary services,an optimal configuration method for shared energy storage oriented to multiple auxiliary services under an intergrated multi-station scenario is proposed.The typical operation modes of intergrated multi-station are discussed,and the application mode of shared energy storage for multiple auxiliary services of energy storage stations under multi-station fusion mode is proposed.Its applications include renewable energy intergration,data center UPS replacement,and backup substations.An autoregressive sliding average model is used to generate wind power output sampling scenarios.And an optimal configuration method for shared energy storage based on stochastic optimization is proposed.(2)Based on the centralized energy storage multi-user shared application mode,and considering the application of heterogeneous multi-energy source shared energy storage,a centralized electric-heat heterogeneous shared energy storage service pricing method is proposed.A quasi-dynamic model for heat transfer is established to analyze the virtual energy storage potential of the heat network.On this basis,a centralized heterogeneous electric-heat shared energy storage model is constructed to describe the shared energy storage formation mechanism with the heat network as a schedulable energy storage resource.The shared energy storage operator can make full use of the characteristics of physical energy storage and heat network energy storage to reduce physical energy storage construction costs and increase benefits.Furthermore,a pricing mechanism for centralized electric-heat heterogeneous shared energy storage services is proposed,which is a two-level stackelberg game problem between the shared energy storage operator and energy storage users.In the upper-level model,the the shared energy storage operator determines the pricing of unit power capacity and unit energy capacity for energy storage services.In the lower-level model,users decide their energy storage leasing capacity and electricity usage plan.The bi-level optimization problem is solved by diagonalization method,and a heuristic method based on binary search is used to solve oscillation problems.The convergence of the algorithm is improved.(3)Based on the user-owned distributed energy storage shared application mode,considering the uncertainty of renewable energy sources,a robust optimization-based configuration model for distributed shared energy storage on the generation side based on cooperative games is proposed.A shared energy storage model on the generation side is established to describe the supply-demand mechanism of energy storage resources.renewable energy power stations form coalition and play cooperative games to maximize coalition benefits by making decisions on rated power capacity and rated energy capacity for each participant.Furthermore,a two-stage robust optimization-based configuration model for shared energy storage is established.The min-max-min problem is solved by using nested column and constraint generation(Nested C&CG)technology to improve system flexibility and robustness.Shapley value method is applied to formulate profit distribution plan to ensure that all coalition participants receive reasonable benefits.(4)Based on the user-owned distributed energy storage shared application mode,considering the limitations of traditional robust optimization and the coupling relationship between output power and time of energy storage,in response to situations where there are insufficient/excessive energy storage capacity or SOC cannot be adjusted in real time due to uncertainty in renewable energies and limitations in energy storage capacity during intraday stages,a three-layer robust optimization scheduling method based on optimal SOC interval for distributed shared generation-side energy storage is proposed to decouple time-coupling constraints of energy storage capacity.After obtaining optimal SOC operating interval in day-ahead stage,shared energy storage optimizes scheduling within SOC interval range according to short-term prediction during intraday stage.A mode where distributed generation-side shared energy storage participates in multiple auxiliary services is proposed: using idle capacity to participate in frequency regulation auxiliary services while reducing deviation assessment costs.Nested C&CG method is used for solving the proposed model.Shapley value method is applied for formulating reasonable profit distribution plan.(5)Based on bounded rationality of market participants and limited information acquisition in shared energy storage market scenarios,an evolutionary game-based shared-energy-storage market model and multi-agent behavior analysis method are proposed.The evolutionary dynamic process of different interest entities in shared-energy-storage market are analyzed;stability analysis of three-party evolutionary game equilibrium with more complex dynamics are discussed;complete system dynamics behavior of three-party evolutionary game are analyzed;further discussion on various factors affecting evolutionary games such as shared energy storage revenue coefficient,self-use benefit function coefficient and strategy initial state are conducted.And qualitatively compare and analyze the applicability of traditional game theory and evolutionary game theory in the shared energy storage market.. |
