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An emerging problem associated with the increased global demand for electric vehicles (EVs) is the post-use of lithium-ion batteries installed in them. Discarded batteries maintain 70–80% of their performance; thus, they are highly valuable recycling resources. Accordingly, technologies that complement the intermittency of renewable energy by integrating discarded EV batteries into battery energy storage systems (BESSs) are receiving attention. Here, the economic feasibility of a residential solar photovoltaic (PV) + reused BESS (RBESS) integrated system in three emerging countries (Philippines, Indonesia, and Vietnam) was analyzed by comparing its performance with that of diesel power generation and central grid-supplied power. The proposed system had a higher economic feasibility than diesel power generation (55.9% lower LCOE) but a lower economic feasibility than the central grid-supplied power (282.7% higher LCOE) in all three countries. Additionally, we conducted a sensitivity analysis by incorporating the investment cost, government subsidy, and social cost of greenhouse gas emissions. In conclusion, the Philippines is the best country for grid parity with the integrated system, following Indonesia and Vietnam. This study examined both the economic and social benefits of the proposed system as a countermeasure to climate change and the virtuous resource cycle.

Frequency regulation (FR) using a battery energy storage system (BESS) has been expanding because of the growth of renewable energy. This study introduces the wear density function, which considers battery degradation factors such as the rate of current, temperature, and depth of discharge (DOD) to provide a precise lifespan prediction. Furthermore, an equivalent system model is developed to evaluate the FR performance of the BESS for various operating parameters. Finally, a quantitative tradeoff relationship between performance and battery lifecycle is derived from the analysis using operational data of the actual BESS for FR.

It is recognized by academia and industry that second‐life batteries retired from electric vehicles still have use values and can be effectively used for supporting less demanding applications. At present, there lacks investigation on the applications of re‐using retired batteries on serving residential sector's energy management. Motivated by this, this paper studies the scenario of assembling retired batteries to be second‐life battery energy storage systems (SL‐BESSs) and using them to serve the energy demand of residential communities in an affordable manner. Based on an established SL‐BESS model, a two‐level community energy management framework is proposed, which optimizes the schedules of a SL‐BESS and other energy resources in a community subjected to a variety of short‐term operational objectives. In the upper level, a many‐objective optimization model is formulated, which comprehensively integrates four objectives covering the community's multi‐scale operational considerations. A NSGA‐III‐based solving approach is developed to find the non‐dominated solutions of the model. In the lower level, the optimal community scale load reshaping decisions and energy costs obtained from the upper level are allocated to individual houses. Extensive numerical case studies are conducted, and the results show that the proposed system can realize better trade‐off among the different operational considerations with less computational cost.

26650 LiFePO4 battery, as an ideal energy storage battery for the smart grid system, has the shortcomings of fast aging speed and large dispersion of aging trend, which is the reason for accelerating the 26650 battery system aging. However, it is noted that the 26650 LiFePO4 battery with high aging trend dispersion shows the characteristics of grouping. Therefore, to prolong the 26650 battery system life, this paper proposes a state-of-charge (SOC) and state-of-health (SOH) double-layer equalization scheme for 26650 LiFePO4 batteries based on a multi-agent blackboard system (MABS) that utilizes these characteristics. Based on MABS, the battery units with similar SOH are clustered into a group by a hierarchical-clustering algorithm. Then, SOH balancing is performed by changing the depth of charge and discharge (DOD) between groups, and SOC balancing is performed within the group. MATLAB simulation results verify the effectiveness of the proposed scheme in ensuring the balance of battery charge and discharge and prolonging the life of the battery energy storage system (BESS).

As a key component of transportation decarbonization, the adoption of electric vehicles (EVs) is rapidly increasing. However, EV batteries are typically retired once their state of health drops to around 80%, usually after 10 to 20 years of use. Despite this decline, retired EV batteries still retain 70–80% of their original capacity. Reusing these retired batteries as second-life batteries (SLBs) for battery energy storage systems can offer significant economic and environmental benefits. This article provides a comprehensive analysis of the technical challenges and solutions, economic feasibility, environmental impacts, and case studies of existing projects. It also explores the current battery recycling process. The article concludes with an overview of the feasibility assessment, future development trends, market potential, and policy recommendations for the battery energy storage market.

Nonlinear characteristics of a battery energy storage system (BESS) may cause errors in the stored energy between the operation plan and the actual operation. These errors may hinder the reliability of the power system especially in environments such as microgrids with limited power generation resources and high uncertainty. This study proposes a method to alleviate the occurrence of such errors in the charging/discharging scheduling process of the BESS by piecewise linearizing its nonlinear characteristics. Specifically, the stored energy in a BESS that changes nonlinearly according to the size of the charging/discharging power was modeled using the special ordered set of the type 2 (SOS2) method. The proposed model and the typical BESS-operation models with constant power conditioning system (PCS) input/output power efficiency were applied to the unit commitment (UC) problem in a microgrid environment, and the results were compared with the actual operation results. The proposed model operated similarly to the actual operation compared to the typical model, reducing the error in charging/discharging energy. Consequently, the proposed model was made cost-effective by reducing the cost of error correction and reduced the risk of deviating from operating range of the BESS. This study demonstrates that the proposed method can efficiently solve the operational problems caused by the nonlinear characteristics of BESS.

In this study, the active and reactive power control of a battery energy storage system (BESS) using fuzzy logic control to maintain the voltage and frequency stability of the islanded Mae Sariang microgrid is presented. The main scope of the presented study is to cogitate the effectiveness of the BESS controller in view of fluctuations of frequency/voltage subjected to a disturbance occurring in the islanded microgrid. In the Mae Sariang microgrid system, the electricity is produced from two renewable energy resources (RESs), i.e., hydro and solar PV. The use of these clean energy sources has become a main problem, envisaging the output power uncertainties from RESs. Further, such power uncertainty raises power quality problems and leads to power failure. To overcome such problems, the proposed fuzzy logic control (FLC) approach is applied for the BESS controller to improve the stability of the islanded Mae Sariang microgrid. The proposed FLC is intended to provide the BESS with well-established attributes of dynamical response to disturbance, which is analyzed by a predictive model. The proposed FLC has been investigated and compared with the robust control method, which is analyzed by a mathematical model using the system identification technique. The modeling of the microgrid system with BESS is implemented and verified on the DIgSILENT PowerFactory software. The simulation result illustrates that both of the control approaches allow the dynamic stability of the microgrid and the maintenance of frequency and voltage within acceptable ranges. However, the proposed BESS fuzzy logic control is less prone to uncertainty than the BESS robust control. Furthermore, in the proposed BESS fuzzy logic control, the microgrid frequency and voltage rapidly return to their normal steady-state condition and the size of the BESS is smaller than the BESS robust control.

Energy storage is one of the key means for improving the flexibility, economy and security of power system. It is also important in promoting new energy consumption and the energy Internet. Therefore, energy storage is expected to support distributed power and the micro-grid, promote open sharing and flexible trading of energy production and consumption, and realize multi-functional coordination. In recent years, with the rapid development of the battery energy storage industry, its technology has shown the characteristics and trends for large-scale integration and distributed applications with multi-objective collaboration. As a grid-level application, energy management systems (EMS) of a battery energy storage system (BESS) were deployed in real time at utility control centers as an important component of power grid management. Based on the analysis of the development status of a BESS, this paper introduced application scenarios, such as reduction of power output fluctuations, agreement to the output plan at the renewable energy generation side, power grid frequency adjustment, power flow optimization at the power transmission side, and a distributed and mobile energy storage system at the power distribution side. The studies and application status of a BESS in recent years were reviewed. The energy management, operation control methods, and application scenes of large-scale BESSs were also examined in the study.

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

The use of battery energy storage system (BESS) is one of the methods employed in solving the major challenge of overvoltage, experienced on distribution networks with high penetration of photovoltaics (PV). The overvoltage problem limits the penetration levels of PV into the distribution network, and the benefits that could be gained. This study presents three loosely‐related schemes for the coordination of multiple BESSs in such networks. Through the efficient selection, coordination and timing of charge and discharge operations of the BESS, the scheme maintains bus voltages within statutory ranges during periods of high PV power generation and high network load demand. Network segmentation was used in two of the schemes to encourage more even utilisation of the BESS in order to maximise the economic benefits of the BESS. The algorithms for the schemes were implemented and demonstrated on two different distribution networks. Simulation results showed that the schemes met the objectives of mitigating overvoltage and more even cycling of the BESSs during their operating lifetimes.