电力系统中电池储能系统接入技术可提高可再生能源消纳，加速实现“双碳”目标。然而，电化学储能系统初始经济性投入较高，考虑新能源（风光）各向异性，形成多能源（风光储）主体协调、储能系统共享利用结合的商业模式是提高电化学储能系统经济性的有效手段。本文聚焦风光储联合运行下的储能电站经济性评估与提升技术，开展电源侧调峰调频(Peak Shaving and Frequency Regulation, PSFR)及共享梯次利用电池储能参与用户群调度设计的运行优化策略研究，具体关键研究内容和策略如下：第二章：电池储能电站参与电源侧PSFR容量配置方法及经济性评估。以电池储能参与风光PSFR为研究对象采用“外-内”双层模型分析储能电站经济性和储能容量配置策略。外层模型中主要考虑电池储能系统的经济性指标、运行成本（电池退化成本、运维成本、日均投资成本）、调频指令的改善量、频率标准差等建立储能电站的经济性指标体系；内层模型考虑储能参与PSFR调度建立储能电站优化调度模型，并以电池储能配置容量和电源侧PSFR成本最低为目标，制定储能电站优化运行的控制策略。第三章：分布式共享储能参与用户侧辅助服务日优化调度。本部分主要聚焦于共享退役储能电池参与用户侧日优化调度。将i用户参与共享储能的优化调度服务，以用户侧购售电的经济性最优为目标。分别分析三种不同的案例：第一，用户侧不配置储能电站；第二，用户侧分别配置工商业区储能电站；第三，用户侧同时共同使用该地区配置的共享储能电站。通过分析不同的案例，提出共享储能的可行性及经济性。第四章：风光储联合运行下分阶段多场景下的平准化成本模型及敏感性分析。首先，通过物理特性评估方法筛选电池储能的类型；其次，建立储能成本构成的模型以及筛选最经济的储能类型来参与对象领域的经济可行性；再次，在储能效益及评估方面，将电池健康状态大于80%用于参与电源侧PSFR调度，60%-80%的健康状态用于共享储能电站参与用户侧的优化调度，并可得，电池储能不同梯级的经济收益，在结合平准化成本模型，建立新型的经济性分析。最后，考虑该储能电站相关的敏感性因素。综上所述，本文将电池储能参与风光储联合调度，逐步形成一套全生命周期的电池储能电站参与电源侧和用户群整个项目期间的经济评估。

The access technology of battery energy storage system in power system can improve the consumption of renewable energy and accelerate the realization of carbon peaking and carbon neutrality goal. However, the initial economic investment of electrochemical energy storage system is high. Considering the anisotropy of new energy, forming a business model of multi-energy subject coordination and shared utilization of energy storage system is an effective means to improve the economy of electrochemical energy storage system. This paper studies that in the first stage, the new battery energy storage participates in the peak shaving and frequency regulation (PSFR) on the power side, and in the second stage, the shared retired battery solves the daily scheduling of user groups and realizes the coordinated and optimal operation of all kinds of energy. It is an important research object for the sustainable development of new energy in the future. In this paper, the operation optimization strategy is designed for the participation of battery energy storage in PSFR at the power side and echelon utilization of battery energy storage in user group scheduling. The specific key research methods and strategies are as follows:Chapter 2: Battery energy storage participates in the economic evaluation and capacity allocation of PSFR on the power side. Battery energy storage is used to participate in wind and solar PSFR, which separated into outer and inner model respectively. The outer model mainly considers the economic index, operation cost (battery degradation cost, operation and maintenance cost, daily average cost), improvement amount of frequency modulation command and frequency standard deviation of battery energy storage system. The inner model is the optimal scheduling model of battery energy storage system. The scheduling model mainly considers the participation of energy storage in PSFR scheduling, and takes the optimal configuration capacity of battery energy storage as the goal to optimize the control strategy of operation.Chapter 3: Distributed shared energy torage (DSES) to participate in user side auxiliary service capacity allocation method and economic analysis. This part mainly focuses on sharing retired energy storage batteries and participating in user side auxiliary services. Each user side will participate in the scheduling service of shared energy storage, and the goal is to optimize the economy of power purchase and sales on the user side. Three different cases are analyzed: first case, the user side is not equipped with a battery to store energy; Second case, each user side is equipped with a commercial area energy storage power station; Third case, each user side uses the shared energy storage power station configured in the region at the same time. By analyzing different cases, the feasibility and economy of shared energy storage are put forward.Chapter 4: This chapter is based on the economy and sensitivity analysis of the levelized cost of energy (LCOE) under multiple scenarios. Firstly, the type of battery energy storage is screened by physical characteristic evaluation method. Secondly, establish the model of energy storage cost composition and screen the most economical energy storage types to participate in the economic feasibility of the object field. Thirdly, in terms of energy storage efficiency and evaluation, when the battery state of health (SOH) is greater than 80%, it is used to participate in PFSR scheduling on the power grid side, while SOH stands around 60%-80% of the capacity is used to share the energy storage power station to participate in the optimal scheduling on the user side. It can be obtained that the economic benefits of different steps of battery energy storage are combined with the LCOE to establish a new economic analysis. Finally, the sensitive factors related to the energy storage power station are considered.To sum up, this paper takes two different stages of battery energy storage as the economic dispatching analysis of power side and user side, analyzes the main key factors involved, and gradually generates a set of battery energy storage power station with full life cycle to participate in the economic evaluation of power side and user group during the whole project period.