**1. Introduction**

With the implementation of the dual-carbon target, it has become clear that large-scale renewable energy generation, specifically through wind and photovoltaic power, is the direction and necessary choice for new power systems in the future [1–3]. To achieve the strategic goals of building a new power system, China has proposed to further build REBs to facilitate the high-quality and rapid development of RE. The "14th Five-Year Plan for China's Economic and Social Development and the Long-Range Objectives through the Year 2035" released in March 2021 proposes to focus on developing nine clean energy bases and four offshore wind power bases during the duration of the 14th Five-Year Plan. In June 2022, the National Development and Reform Commission and nine other departments issued the "14th Five-Year Plan for the Development of RE", which explicitly proposes active steps to promote the development of wind and solar power generation facilities, and expedite the construction of large-scale REB projects, with a particular emphasis on desert, Gobi, and other barren regions [4–6]. However, the "anti-peak" characteristic of wind power and the weather impact on photovoltaic power generation have increased volatility of the net load curve, which imposes higher requirements on flexible resources for the new power system. Several provinces have implemented policies mandating that RE plants

install a specific percentage of ES to reduce the influence of RE integration on the safety and stability of the power grid. The integration of energy storage systems with renewable energy sources addresses the mismatch between renewable energy generation and load demand and reduces the uncertainty of renewable energy output, thereby enhancing the overall operational efficiency of the grid, lowering power supply costs, improving system stability, and enhancing power quality [7–9].

Due to the instability of RE, ES is needed to improve the total efficiency and stability of the power grid, reduce electricity supply costs, and enhance the utilization rate of RE. Currently, EES is the main ES technology, and its application has become increasingly widespread as its technology continues to develop and costs continue to decline [10]. Nevertheless, when ES is solely coupled with REBs, its usage rate is comparably low, making it challenging to recoup the expenses of ES, particularly in the present scenario where raw material costs are surging while RE project prices continue to fall [11,12]. The utilization rate of ES will further decrease when coupled solely with REBs, thereby hindering the promotion of the development of RE. To address the low utilization rate and poor economics of ES paired only with REBs, SES can provide an effective solution. By using SES, ES expenses can be reduced and utilization rates can be increased, thereby better supporting the development of RE [13–15].

A large-scale REB is composed of multiple wind and photovoltaic units, as well as their collection and transmission networks. Essentially, configuring SES for REBs means meeting the ES needs of various RE units within the base. Therefore, we need to consider the differences in ES needs of different RE units within the base to achieve fair distribution of ES costs. The core of the SES mechanism for REBs is how to quantify the contribution of SES to the ES capacity requirements of various RE units and then share the cost of SES accordingly [7]. Several studies have been conducted on the modes of operation for SES and cost allocation among RE units. Some researchers have investigated the impact of performance quality and prediction errors of renewable energy units on the demand for energy storage capacity and the allocation of energy storage costs [16]. Ref. [17] proposed a wind power cluster and SES coordination optimization mechanism, and allocated the benefits of each member of the alliance to demonstrate that the coordination optimization mechanism is conducive to reducing operating costs of each member and ensuring fairness of benefit distribution. In [18], a novel non-cooperative game mechanism is proposed, which optimally regulates the operation of distributed generation and flexibility resources by considering economic factors and electric power quality. Ref. [19] introduced a new twostage credit-based model for SES which, considering time accumulation effects, developed an SES pricing strategy and a capacity planning scheme, and demonstrated the advantages of the proposed novel shared model in the field of economic efficiency and the utilization rate of ES. The research results indicate that SES has enormous potential value, not only for configuring SES in REBs but also for applying SES to various links in the power supply chain. Ref. [20] aimed to examine the real advantages of implementing SES in residential neighborhoods, established optimization operation models for independent and SES, compared and analyzed the optimal energy operations of the two, and developed an efficient control strategy suitable for the use of SES to demonstrate the advantages of SES in saving electricity costs and improving the ES utilization rate. Some studies have also proposed transactional operation mechanisms for energy storage systems based on non-cooperative game theory [21,22]. In [22], an interactive energy management scheme is defined for multiple SES systems and users to achieve information sharing. These studies have provided certain theoretical support and a decision-making basis for the formulation of SES modes among a considerable quantity of RE units within a large REB. Existing research has primarily focused on optimal capacity allocation and economic benefits of SES among renewable energy units while neglecting the impact of cost allocation mechanisms on the sustainable operation of SES. Therefore, this paper formulates a fair cost allocation mechanism considering the differential ES demands of each renewable energy unit within the base, aiming to achieve equitable distribution of ES costs.

EES, mainly consisting of energy storage batteries, is one of the most economically advantageous ES technologies among existing RE storage technologies. However, it should be noted that EES has the characteristic of dynamic degradation of its lifespan. Although SES operation modes can improve ES utilization rate, they can accelerate the degradation of the lifespan of EES. However, in the research on SES for renewable energy integration currently, the influence of shared operation on energy storage battery lifespan degradation is often overlooked or simplified. For instance, some studies consider the working efficiency of energy storage batteries as a constant value, disregarding the dynamic changes in charging and discharging efficiencies [23,24]. However, in actual operation, energy storage batteries experience dynamic changes in charging and discharging efficiencies due to power losses generated during operation to meet load demand [25,26]. Additionally, to simplify the complex degradation variations in practical operation, certain studies assume the same degree of lifespan degradation under different operating conditions, without accounting for the nuanced degradation of ES capacity under different operational scenarios [27]. However, it is clear that the lifespan of EES will gradually shorten with changes in the state of charge (SOC) and the number of charging-and-discharging cycles. To more accurately estimate the degradation of the lifespan of energy storage batteries, equivalent circuit models, empirical models, and aging mechanism models are currently mainly used [28]. Ref. [29] proposed a method to detect the decay of the available capacity of energy storage batteries using the discharge curve and capacity data based on a first-order Thevenin equivalent circuit model. Ref. [30] established a calendar aging model of energy storage batteries based on experimental data and quantified the impact of SOC, temperature, and battery operating time on the degree of battery life decay. Ref. [31] studied the dynamic performance changes of energy storage batteries under different environmental conditions in a residential photovoltaic energy storage battery system, and analyzed the impact of charging-and-discharging curves on battery aging. Moreover, existing research tends to focus on the lifespan degradation characteristics of distributed independent energy storage systems, lacking investigations on the impact of dynamic degradation characteristics of SES on system operation. This paper, however, conducts a refined analysis of the dynamic degradation characteristics in the actual operation of EES.

Moreover, due to the diverse output characteristics of different renewable energy units, there are variations in the capacity requirements for SES. Existing research has primarily focused on optimal capacity allocation and economic benefits of SES among renewable energy units while neglecting the impact of cost allocation mechanisms on the sustainable operation of SES. To analyze the influence of dynamic degradation characteristics on the operational strategies and capacity allocation of electrochemical shared energy storage in REBs, and to address the issue of uneven cost allocation resulting from differences in ES capacity requirements, this paper presents a refined modeling of SES lifespan degradation. Building upon the health status of EES, known as the state of health (SoH), this research investigates the optimization of operational strategies and cost allocation mechanisms for SES in REBs by considering dynamic degradation characteristics. The main innovations can be summarized in the following three aspects:


and reduces the assessment cost of real-time balancing markets. The design of this framework can better promote the sustainable development of renewable energy generation.

• A shared energy storage cost allocation mechanism is proposed for renewable energy bases based on the marginal contribution in both the day-ahead and the real-time market. This mechanism can meet the energy storage demands of different renewable energy generators and incentivize compatibility. The numerical results demonstrate a positive correlation between the shared energy storage costs allocated to different renewable energy generators and their corresponding energy storage demands. The implementation of this mechanism can better promote the coordinated optimization of renewable energy and shared energy storage operations, achieving a win-win situation.

The rest of this paper is structured in the following manner. The SES operation framework for a REB is proposed in Section 2. The refined model of dynamic life decay of EES is introduced in Section 3. In Section 4, an optimized operational approach for SES in a REB is presented, taking into account the dynamic degradation characteristics of EES. The SES cost allocation mechanism based on the marginal contribution in both the day-ahead and real-time markets is introduced in Section 5. Section 6 contains the conclusions and future prospects of this study.

#### **2. Framework of Energy Storage Sharing**

A two-stage optimal collaborative operation strategy for a REB and SES is proposed by combining day-ahead optimization and real-time optimization. This strategy includes two stages: during the first stage, the optimization of day-ahead scheduling is carried out, and each unit in the REB optimizes its day-ahead operation strategy based on the day-ahead output prediction data. In the second stage, the charging and discharging operation statuses of SES vary according to real-time electricity prices and the uncertainty of wind power output, then embedded it into the day-ahead optimization model of the first stage. Meanwhile, the dynamic degradation characteristics of the SES's lifespan are taken into account, and the influence of battery health status changes on ES capacity allocation is considered. Considering the differential SES capacity demands of different units within the REB, this paper measures the contribution of each member to the overall alliance and allocates the investment and operational costs of SES among various renewable energy units within the base. This allocation is performed in a manner that reflects the varying needs of different units and ensures a fair distribution of the investment and operational costs associated with SES. This strategy aims to optimize the overall operation of the system, fully consider the uncertainty and fluctuations of wind power output in actual operation, and improve the efficiency and economic viability of RE generation. The Operation framework for energy storage sharing in a renewable energy base is shown in Figure 1.

**Figure 1.** Operation framework for energy storage sharing in a renewable energy base.

#### **3. Dynamic Degradation Model in Battery Energy Storage Sharing**

To alleviate the impact of large-scale RE, such as wind and solar power, it may be necessary to frequently adjust the charge and discharge states of RE batteries and the power flow in and out of the grid. Therefore, the capacity degradation caused by the changes in charge and discharge behavior of RE batteries in a brief span of time cannot be ignored. It is necessary to consider the influence of changes in charge and discharge power on the performance and lifespan of ES devices. Therefore, the fine-grained dynamic degradation characteristics of EES are of great significance. In this section, the dynamic degradation characteristics of EES will be finely modeled to provide more theoretical support for the subsequent research on operation and cost allocation mechanisms of SES in REB.
