Optimal configuration of shared energy storage for multi-microgrid systems: Integrating battery decommissioning value and renewable energy economic consumption

With the development of renewable energy, energy storage has become one of the key technologies to solve the uncertainty of power generation and the disorder of power consumption and shared energy storage has become the focus of attention for its cost-effective characteristics. However, it is always difficult to quantify the coupling relationship between charge and discharge strategy and life expectancy in energy storage configuration. Based on this, this paper proposes an industrial user-side shared energy storage optimal configuration model, which takes into account the coupling characteristics of life and charge and discharge strategy. Firstly, the life loss model of lithium iron phosphate battery is constructed by using the rain-flow counting method. In order to further optimize the user-side shared energy storage configuration in the multi-user scenario, a two-layer model of energy storage configuration is built, and the Big M method and the Karush-Kuhn-Tucker (KKT) conditions are used to equivalently transform the constraints. Based on the predicted life of energy storage and the dichotomy method, the optimal energy storage configuration results are obtained. Comparing the energy cost of users under the three scenarios of no storage configuration, storage configuration according to fixed storage life, and storage configuration according to the model proposed in this paper, the results show that the proposed method can help accurately describe the energy storage model, increase the utilization rate of the power station, and improve the electricity economy of users.

With the increasingly severe global energy crisis and environmental pollution problems, new energy vehicles, as an important alternative to traditional fuel vehicles, have achieved rapid development. As of January 2024, the total number of charging infrastructure nationwide has reached 8.861 million units, a year-on-year increase of 63.7%, and there are 3624 battery swap stations. The popularity of new energy vehicles puts forward higher requirements for charging infrastructure. As an important supply station for new energy vehicles, public charging, and swapping stations have new energy access, energy storage configuration, and topology that directly affect charging efficiency, grid stability, and economy. This paper profoundly studies the new energy access, storage configuration, and public charging and swapping station topology. Analysis shows that new energy access has significant advantages. Experimental data show that in some areas with sufficient sunlight, using solar photovoltaic panels as the primary energy access method can provide up to 30% of energy supply, significantly reducing operating costs and carbon emissions. Energy storage system configuration is equally critical. By establishing an optimization model, the influence of different energy storage devices on the operating efficiency of charging and swapping stations is analyzed. Experimental results show that using a 100 kWh lithium-ion battery energy storage system, combined with appropriate charging and discharging strategies, can significantly improve energy utilization and response speed, provide power support during peak hours, smooth power grid fluctuations, and improve stability.

This paper aims to meet the challenges of large-scale access to renewable energy and increasingly complex power grid structure, and deeply discusses the application value of energy storage configuration optimization scheme in power grid frequency modulation. Based on the equivalent full cycle model and a large number of actual operation data, various energy storage technologies are technically analyzed, and the economic and environmental performance of different energy storage configuration schemes are comprehensively evaluated. On this basis, this paper puts forward a set of efficient and economical energy storage configuration optimization strategies to meet the demand of power grid frequency modulation and promote the wide application of energy storage technology. After an in-depth analysis, it is found that the optimized energy storage configuration scheme is excellent in technology, economy, and environmental protection. Specifically, in terms of technical performance, the optimization scheme has significantly improved key indicators such as energy storage efficiency, capacity and power, and response speed, which can better meet the requirements of power grid frequency modulation. Through the verification of actual operation data, it is found that the overall efficiency of the optimized energy storage configuration scheme is above 55%, which is helpful to the stability and efficiency of power grid frequency modulation. In terms of economic performance, although the initial investment cost of the optimization scheme may be high, it is found that it has good economy through the evaluation of long-term operation benefits. Considering that the energy storage system can reduce the operating cost of the power grid, improve the energy utilization rate, and achieve the optimization of cost-effectiveness in the long run, this scheme is economically feasible and attractive. In terms of environmental performance, the optimization scheme effectively reduces the negative impact on the environment by improving energy storage efficiency, reducing emissions, and optimizing resource utilization. This is not only conducive to the sustainable development of the power grid but also in line with the current global trend of promoting green and low-carbon transformation. To sum up, this paper not only provides an efficient and economical energy storage allocation optimization strategy for power grid frequency modulation but also provides a scientific basis for relevant decision-making departments. By promoting the practical application and development of energy storage technology, this paper is helpful to improve the frequency modulation ability of power grid, optimize energy structure, and reduce environmental pollution, and thus achieve the goal of sustainable energy development. The data results and in-depth analysis of this paper provide strong support for the practical application of energy storage configuration optimization scheme and also provide important reference for the further innovation and development of energy storage technology.

Energy storage technology already has the potential advantages of being mobile, modular, and "plug and play". The results of existing energy storage planning of the Distribution Network (DN) are energy storage configurations with fixed access points and capacity. There is still a lot of room for the flexibility and value of energy. With many renewable energies distributed generation (DG) connected to the distribution network, it can be divided into different operating scenarios according to the seasonality of distributed power and loads in the distribution network. This paper proposes a Mobile Energy Storage (MES) configuration planning method of the DN. Through this method, the MES devices are dynamically allocated between different operating scenarios of the DN regarding the varying load demands as well as DG outputs. The access points, capacities and operation modes of MES devices in various scenarios are taken as the decision variables, the maximum comprehensive economic benefit brought by MES is taken as the objective, and thus the mixed-integer second-order cone programming(MISOCP) model for MES configuration is constructed. Case studies are performed in the modified IEEE 33-node distribution systems. The feasibility and effectiveness of the proposed method are verified The proposed method can be treated as a useful expansion to the flexible operation of energy storage device, through which the MES can well service for various operating scenarios of the DN and thus its value can be fully developed.

The configuration of energy storage helps to promote renewable energy consumption, but the high cost of energy storage becomes a major factor limiting its development. Through shared energy storage, the utilization rate of energy storage can be improved and the recovery of energy storage investment costs can be accelerated. This paper first introduces the application scenarios of the proposed shared energy storage, then analyzes the characteristics of shared energy storage. Furthermore, the transaction process between new energy and shared energy storage is put forward, and the clearing model of shared energy storage market is established. To minimize the consumption cost of new energy generators by coordinating the sharing of idle energy storage capacity. Finally, the proposed method is verified through examples to analyze the benefits of shared energy storage for investors and new energy generators, as well as the changes in new energy consumption.

Research on the collaborative operation strategy of shared energy storage and virtual power plant based on double layer optimization

With the large-scale access of renewable energy, the randomness, fluctuation and intermittency of renewable energy have great influence on the stable operation of a power system. Energy storage is considered to be an important flexible resource to enhance the flexibility of the power grid, absorb a high proportion of new energy and satisfy the dynamic balance between the supply and demand of a system. At present, the cost of energy storage is still high, and how to achieve the optimal energy storage configuration is the primary problem to be solved. Therefore, the current research progress in energy storage application scenarios, modeling method and optimal configuration strategies on the power generation side, grid side and user side are summarized in this paper. On this basis, the shortcomings that still exist of energy storage configuration research are summarized, and the future research direction for energy storage configuration is prospected. This review can provide reference for the latest development and future research and innovation direction for energy storage configuration.

A double-layer robust optimization method for capacity configuration of shared energy storage considering cluster leasing of wind farms in a market environment is proposed based on the autonomy and profitability of shared energy storage. The feasibility of the leasing model of shared energy storage in the current market environment in China is discussed, and a commercial operation model for shared energy storage to provide leasing services and participate in spot market transactions is proposed. A robust optimization model of a master-–slave game for the capacity configuration of shared energy storage is constructed, considering output uncertainties of wind-driven generators and spot prices at multiple time scales. The upper layer of the model aims to minimize the annual cost of shared energy storage and determines the leasing prices and capacity-planning schemes for each period of shared energy storage in the scenario of an interactive game of wind farm clusters. The lower level of the model aims to minimize the assessment cost of the wind farm cluster and updates the leasing capacity for each time period by utilizing the leasing prices and the leasing demand of the wind turbine output power in the worst scenario. By comparing and analyzing multiple scenarios, the master–slave-game-formed lease improves the shared-storage lease benefit by $1.46 million compared to the fixed tariff, and the multi-timescale uncertainty promotes the shared-storage cost-effectiveness to be reduced by 8.7%, while the configuration result is more robust, providing new ideas for optimizing the capacity configuration of shared energy storage in multiple application scenarios.

In the context of increasing renewable energy penetration, energy storage configuration plays a critical role in mitigating output volatility, enhancing absorption rates, and ensuring the stable operation of power systems. This paper proposes a benefit evaluation method for self-built, leased, and shared energy storage modes in renewable energy power plants. First, energy storage configuration models for each mode are developed, and the actual benefits are calculated from technical, economic, environmental, and social perspectives. Then, the CRITIC method is applied to determine the weights of benefit indicators, and the TOPSIS method is used to rank the overall benefits of each mode. Simulation results validate the effectiveness of the proposed method and compare the benefits of the three modes, showing that the leased mode provides the highest overall benefit. This study provides a quantitative reference for the rational selection of energy storage modes in renewable energy projects.

Techno-economic comparison of different energy storage configurations for renewable energy combined cooling heating and power system

In the process of decarbonization, the configuration of renewable energy and energy storage plays a crucial role. In current research, there is often a singular focus on the isolated optimization of either renewable energy configurations or energy storage configurations, resulting in limitations within the optimized outcomes. Therefore, we propose a collaborative configuration approach for renewable energy and energy storage under fixed investment, considering the impact of uncertainty on optimization results. By employing the W/S (wind-to-solar ratio) and E/P (energy-to-power ratio) and constructing a model with an hourly granularity, we can obtain the configurations of renewable energy and energy storage at crucial time points. Using the UK as a case study, we calculate the configurations for renewable energy and energy storage from 2020 to 2050, offering effective recommendations for the decarbonization efforts in the UK.

How to accurately calculate the return on investment (ROI) of integrated energy service providers (IESPs) is an urgent problem to improve the efficiency of energy storage allocation and operation economy. In this paper, an integrated energy storage configuration method for IESP considering ROI and medium- and long-term demand response (MLTDR) is proposed. It is applied to electricity, gas, and heat multi-type energy storage configuration of IESP with integrated energy distribution network. Firstly, the basic operation structure and energy storage configuration principle of IESP are given, and the calculation method of ROI and MLTDR is put forward. Secondly, an integrated energy storage configuration model considering ROI and MLTDR is established to realize the location and capacity of electricity, gas and heat multi-type energy storage. The configuration scheme and operation mode of integrated energy storage are given to improve the efficiency of energy storage configuration. Finally, the results of calculation simulation show that the proposed method improves 43.75% ROI under the condition of ensuring the same operating income increment. The effectiveness of the proposed method is verified.

In the planning of hybrid energy storage in wind farms, considering the service life of the battery in the operation stage, a bi-level optimal configuration method of hybrid energy storage in wind farms considering the service life of the battery is proposed. The upper optimization model takes the optimal energy storage configuration cost as the goal, takes the configuration power and capacity of battery and supercapacitor as variables, and takes the configuration power and capacity of battery and supercapacitor satisfying their respective energy storage power instruction sequence as the constraint condition. The lower optimization model takes the maximum service life of the battery in the running stage as the goal, takes the power instruction sequence of the battery and the super-capacitor as variables, and takes the battery and supercapacitor power instruction sequence not exceeding the limit as the constraint condition. The upper optimization model is solved by the linear programming method, and the lower optimization model is solved by particle swarm optimization algorithm. Finally, the proposed method is compared with the energy storage configuration method based on frequency band demarcation. The results show that the proposed method can reduce the cost of energy storage configuration during planning and prolong the service life of the battery during operation.

With the electricity market opening gradually in China, end-users transit to prosumers and the complementarity of multiple energy increases continuously, thus cloud energy storage business model may become a new form of user-side energy storage in the future. In this paper, the business model of load aggregator (LA) is applied to the comprehensive optimal configuration of multiple energy storage in the integrated energy system (IES), and the energy storage behavior of users is considered. Firstly, the LA model is summarized, the energy hub (EH) structure is established, and the transformation relationship between input and output is analyzed. Then, a two-stage multi energy storage optimization model is proposed. In the first stage, the electric and thermal energy storage requirements of all users are optimized from the perspective of users. In the second stage, all users’ energy storage requirements from the previous stage are integrated, and the configuration of electric and thermal energy storage are comprehensively optimized from the perspective of LA. Finally, this model is applied to three different scenarios and solved by CPLEX. The results of case studies verify that the comprehensive optimal configuration of electric and thermal energy storage in LA mode can utilize energy resources more efficiently and reduce costs. Also, user, LA and power grid can achieve mutual benefit and win-win situation.

In recent years, the rapid development of new energy sectors, particularly photovoltaic and wind power, has introduced significant challenges stemming from their inherent randomness and volatility. This paper presents a systematic approach for effective evaluation of energy storage configurations. The study begins by examining the anticipated evolution of the power grid in alignment with China’s energy policies, focusing on the annual growth rates of wind power, photovoltaic systems, and energy demand. This analysis establishes a foundation for planning energy storage installations. Next, a forecasting method is employed to predict the output of both photovoltaic and wind energy resources. Building on this, a novel control strategy is proposed for integrating renewable energy sources into the grid, facilitating the determination of optimal energy contributions to ensure a stable power supply. A comprehensive energy storage configuration model is then developed, accompanied by a multi-faceted analytical framework to assess energy storage from perspectives such as environmental impact, economic feasibility, operational flexibility, and technological advancement. Ultimately, this research provides a scientific assessment of energy storage configurations, grounded in grid development projections and resource output forecasts.