Lithium-ion Battery Energy Storage System Research Articles

DEVELOPMENT OF ULTRA CAPACITOR BASED REGENERATIVE BRAKING SYSTEM FOR ELECTRIC VEHICLES

Regenerative braking is a technique for converting a moving vehicle's kinetic energy into usable form while slowing it down. When an automobile brakes violently, it usually emits heat. If we could conserve energy rather than waste it, that would be amazing, right? That's where regenerative braking technology comes in handy, especially for electric vehicles. It stores the wasted energy in a battery or ultra-capacitor, so it can be used later to start or accelerate the vehicle. In our project, we looked at how effective regenerative braking is during both braking and starting modes. We compared starting the motor with a battery, ultra-capacitor, or a combination of both (HESS), and also analyzed how storing energy during braking works with these systems. Although not all of the regenerated energy is reinvested in the battery, the motor acts as a generator, charging the vehicle's battery. To move the vehicle forward, regenerative braking uses the kinetic energy it temporarily stores during deceleration. We used a lithium-ion battery and ultra-capacitor module energy storage system coupled to a BLDC motor via a converter. These brakes help batteries last longer without needing to be charged externally. They enable efficient power transfer during regenerative braking and acceleration. Our project discusses whether regenerative braking increases or decreases efficiency. of state of charge of battery and ultra- capacitor when starting and braking applied in discharging(in running of motor) and charging(in regenerative braking of motor). And also BLDC motor speed control in starting and braking mode. The model is simulated using MATLAB Simulink software. Keywords: Regenerative braking, kinetic energy, electric vehicles, energy storage, battery, ultra-capacitor, starting mode, braking mode, Hybrid Energy Storage System (HESS), efficiency, motor generator

Investment Decision for Long-Term Battery Energy Storage System Using Least Squares Monte Carlo

The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of power systems and achieving greenhouse gas reduction goals. However, ESSs are not being installed because of Korea’s fuel-based electricity market. To address this issue, this paper presents a method for determining the optimal investment timing of Battery Energy Storage Systems (BESSs) using the Least Squares Monte Carlo (LSMC) method. A case study is conducted considering the System Marginal Price (SMP) and Capacity Payment (CP), which are electricity rates in Korea. Revenue is calculated through the arbitrage of a 10 MW/40 MWh lithium-ion BESS, and linear programming optimization is performed for ESS scheduling to maximize revenue. The ESS revenue with uncertainty is modeled as a stochastic process using Geometric Brownian Motion (GBM), and the optimal time to invest in an ESS is determined using an LSMC simulation considering investment costs. The proposed method can be used as a decision-making tool for ESS investors to provide information on facility investments in arbitrage situations.

Adsorption behavior of CuO doped GeS monolayer on the thermal runaway gas evolution in lithium battery energy storage systems

Considering that the thermal runaway failure of lithium battery energy storage system will cause serious safety accidents, and lithium battery thermal runaway will precipitate various detectable gases through the safety gas valve. Effective monitoring of the precipitated gas can ensure the safe operation of the energy storage system. In this study, the adsorption behavior of CuO-GeS towards the main precipitated gases CO, CO2, CH4, and C2H4 in Lithium battery before thermal runaway is systematically studied based on DFT. The adsorption structure, DOS, DCD, and ELF are analyzed to explore the interactions between CuO-GeS monolayer and the gases. The results show that CuO-GeS monolayer achieves strong adsorption of CO and C2H4 and highly sensitive monitoring of CO2 and CH4. Furthermore, the relative molecular mass ratios of CxHy and CxHy-1F (x = 1, 2 y=2, 4, 6) gases to doped CuO can satisfy Smoothing Spline with adsorption energy and charge transfer, which can be used to estimate the adsorption properties of the homologous gases. The potential application of CuO-GeS monolayer in lithium battery energy storage systems lays a theoretical research foundation for the adsorption and detection of thermal runaway gas in lithium battery energy storage systems.

Control Optimization Method for Ship Direct Current Microgrid Based on Impedance Reshaping

In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First, a simplified small-signal diagram of a lithium battery energy storage system converter is analyzed. Combining active damping control technology, an impedance regulator is introduced, and its parameters are optimized to effectively reduce the output impedance magnitude on the power source side. Subsequently, a ship DC microgrid simulation model is constructed using MATLAB R2022a/Simulink for validation, and comparative analysis is conducted on the anti-interference ability of the DC bus voltage before and after impedance reshaping. Finally, a model is built on a semi-physical simulation platform to experimentally verify the proposed method. The research results indicate that the proposed control optimization method can effectively increase the system’s stability margin, suppress DC bus oscillations, and enhance the anti-interference ability of the ship DC microgrid’s bus voltage when facing significant power load variations.

The Cobalt Supply Chain and Environmental Life Cycle Impacts of Lithium-Ion Battery Energy Storage Systems

Lithium-ion batteries (LIBs) deployed in battery energy storage systems (BESS) can reduce the carbon intensity of the electricity-generating sector and improve environmental sustainability. The aim of this study is to use life cycle assessment (LCA) modeling, using data from peer-reviewed literature and public and private sources, to quantify environmental impacts along the supply chain for cobalt, a crucial component in many types of LIBs. The study seeks to understand where in the life cycle stage the environmental impacts are highest, thus highlighting actions that can be taken to improve sustainability of the LIB supply chain. The system boundary for this LCA is cradle-to-gate. Impact assessment follows ReCiPe Midpoint (H) 2016. We assume a 30-year modeling period, with augmentation occurring at the end of the 3rd, 7th, and 14th years of operations, before a complete replacement in the 21st year. Three refinery locations (China, Canada, and Finland), a range of ore grades, and five battery chemistries (NMC111, NMC532, NMC622, NMC811, and NCA) are used in scenarios to better estimate their effect on the life cycle impacts. Insights from the study are that impacts along nearly all pathways increase according to an inverse power-law relationship with ore grade; refining outside of China can reduce global warming potential (GWP) by over 12%; and GWP impacts for cobalt used in NCA and other NMC battery chemistries are 63% and 45–74% lower than in NMC111, respectively. When analyzed on a single-score basis, marine and freshwater ecotoxicity are prominent. For an ore grade of 0.3%, the GWP values for the Canada route decrease at a rate of 58% to 65%, and those for Finland route decrease by 71% to 76% from the base case. Statistical analysis shows that cobalt content in the battery is the highest predictor (R2 = 0.988), followed by the ore grade (R2 = 0.966) and refining location (R2 = 0.766), when assessed for correlation individually. The results presented here point to areas where environmental burdens of LIBs can be reduced, and thus they are helpful to policy and investment decision makers.

Transfer operation ride though control strategy of the aircraft power supply system with lithium battery energy storage

The aircraft power supply system turns towards multi-source, and transfer operation will likely happen during flight missions and fault conditions. The transfer may lead to voltage interruptions and current surges, adversely affecting power quality. This paper proposes incorporating a lithium battery energy storage system (ESS) into the aircraft high-voltage direct current (HVDC) power system. The ESS employs a voltage control model with a lower voltage reference base, facilitating a smooth transfer operation during power interruptions. This approach reduces voltage fluctuations in the power supply system, enhances power quality, and enables seamless power transfer during the transfer operation.

Techno-economic analysis of renewable energy generation at the South Pole

Transitioning from fossil-fuel power generation to renewable energy generation and energy storage in remote locations has the potential to reduce both carbon emissions and cost. This study presents a techno-economic analysis for implementation of a hybrid renewable energy system at the South Pole in Antarctica, which currently hosts several high-energy physics experiments with nontrivial power needs. A tailored model of resource availability and economics for solar photovoltaics, wind turbine generators, lithium-ion energy storage, and long-duration energy storage at this site is explored in different combinations with and without existing diesel energy generation. The Renewable Energy Integration and Optimization (REopt) platform is used to determine the optimal system component sizing and the associated system economics and environmental benefit. We find that the least-cost system includes all three energy generation sources and lithium-ion energy storage. For an example steady-state load of 170 kW, this hybrid system includes 180 kW-DC of photovoltaic panels, 570 kW of wind turbines, and a 3.4 MWh lithium-ion battery energy storage system. This system reduces diesel consumption by 95% compared to an all-diesel configuration, resulting in approximately 1200 metric tons of carbon footprint avoided annually. Over the course of a 15-year analysis period the reduced diesel usage leads to a net savings of 57 million United States dollars, with a time to payback of approximately two years. All the scenarios modeled show that the transition to renewables is highly cost effective under the unique economics and constraints of this extremely remote site.

Inertia Emulation-Oriented Evaluation Method of Sustaining Power Boundary for Lithium-Ion Battery Energy Storage System

Inertia Emulation-Oriented Evaluation Method of Sustaining Power Boundary for Lithium-Ion Battery Energy Storage System

Physics-Aware Degradation Model of Lithium-ion Battery Energy Storage for Techno-Economic Studies in Power Systems

Power system operation and planning decisions for lithium-ion battery energy storage systems are mainly derived using their simplified linear models. While these models are computationally simple, they have limitations in how they estimate battery degradation, either using the energy throughput or the Rainflow method. This paper proposes a hybrid approach for lithium-ion battery system modeling suitable for use in power system studies that enhances representation of battery degradation at a reasonable computational cost. The proposed hybrid model combines a physics-based model for improved degradation estimates with a simple and linear energy reservoir model commonly used to represent a battery storage system. The advantage of constructing the battery model with this vision is that it allows its smooth integration into the mixed-integer optimization frameworks. The proposed model is evaluated using both power- and energy-based use cases from the electrical grid. The simulations demonstrate that degradation could be reduced by 45% compared to other modeling strategies while generating the same level of operation profits. The net result of using the proposed hybrid model could be an extended lifespan through better informed planning and operating decisions for energy storage assets.

Diagnostics of Safety Hazardous Ageing Conditions for Commercial Lithium-Ion Pouch Cells

It is well-known that Lithium-ion cells can have safety issues. A large number of battery fire incidents have been reported the last years within e.g. battery energy storage systems [1], electric and hybrid-electric ships [2], electric vehicles and mobile phones [3]. The causes for these incidents are numerous and can include internal shortage of the Li-ion cell, external shortage of the battery system, over-heating or over-charging. All these causes result in overheating which can lead to an eventual thermal runaway which again could lead to a severe fire and explosion. We report on changes in thermal stability due to different ageing mechanisms in abstract Lian (#176439) and in Lian [4]. A decrease in thermal stability due to battery ageing could be hazardous and might be an end-of-life criteria. It is thus of vital importance to develop diagnostic tools capable of detecting a potentially hazardous drop in thermal stability for aged lithium-ion cells.This study is based on results from a battery life study performed on a large renowned Li-ion pouch cell with an initial capacity of 64 Ah. More than 100 cells were tested following a selected test matrix including different temperatures, currents, and State-of-Charge windows. All cells were tested until they reached a remaining capacity of between 60 to 80 % State-of-Health. A large dataset with diagnostic data was recorded during ageing, including e.g., dQ/dV (incremental capacity analysis) and DC resistances. Thermal properties of selected new and aged cells were studied in an Accelerated Rate Calorimeter (ARC), see Lian (abstract #176439). A post-mortem study of selected new and aged cells was performed to relate the collected diagnostics data to different ageing paths and safety properties. Based on detailed cell characterization, an experimental parameter set for an electrochemical pseudo-two-dimensional (P2D) model was established.Based on the dQ/dV (ICA) analysis, a distinct change in diagnostic patterns was observed for cells aged and cycled at low temperature (5-15 °C) compared to cells cycled at higher temperatures (35 -45 °C). This correlates to the observed differences in thermal stability reported by Lian (abstract #176439). To verify the observed ageing mechanisms from the post-mortem studies, emulated ageing modelling was performed both based on the Alawa tool [5], as well as the P2D model coupled with different ageing mechanisms. References McKinnon, M.B., S. DeCrance, and S. Kerber, Four Firefigheters Injured In Lithium-Ion Battery Energy Storage System Explosion - Arizona, U. Laboratories, Editor. 2020, Underwriters Laboratories: Columbia, MD. p. 66.Norwegian Maritime Authority, Supporting preliminary findings after battery incident. 2019: Norwegian Maritime Authority.BBC, Samsung confirms battery faults as cause of Note 7 fires, in BBC. 2017, BBC.Lian, T., et al., (Invited) Changes in Thermal Stability of Cyclic Aged Commercial Lithium-Ion Cells. ECS Transactions, 2019. 89(1): p. 73-81.Dubarry, M., et al., State of health battery estimator enabling degradation diagnosis: Model and algorithm description. Journal of Power Sources, 2017. 360: p. 59-69.

An Open-Source Energy Arbitrage Model Involving Price Bands for Risk Hedging with Imperfect Price Signals

The increased uptake of variable renewable energy sources has increased electricity price volatility in many energy pool markets, providing an opportunity for storage systems to profit through energy arbitrage. Comparison between the cost or value of storage systems engaging in energy arbitrage should be performed on a levelised basis due to differences in system lifetime. Existing energy arbitrage models with bid/offer curves and imperfect forecasting are typically computationally expensive and are impractical for calculating lifetime levelised cost metrics. In this work, an open-source modular energy arbitrage model with bid and offer curve inputs was developed for a lithium-ion battery energy storage system (BESS) and pumped hydro system (PHS) to analyse lifetime levelised cost and revenue. The mixed integer linear program scheduling module included a new piece-wise linearised description of PHS charging behaviour for rapid optimisation. A one-at-a-time sensitivity analysis indicated that levelised cost and revenue were highly sensitive to discharging efficiency. In a case study based on Australia’s National Electricity Market, imperfect forecasting with no risk hedging was found to increase levelised costs by up to 24% and decrease levelised revenue by up to 50% relative to perfect price forecasting, despite 95% of prices being forecast to be within $35/MWh of the actual trading price. BESS levelised costs were more significantly correlated with consistent low risk bids (Kendall Tau-b of 0.75), since the undiscounted capital costs contribute to a larger proportion of the overall costs than in the PHS systems.

Grid-connected lithium-ion battery energy storage system towards sustainable energy: A patent landscape analysis and technology updates

Presently, as the world advances rapidly towards achieving net-zero emissions, lithium-ion battery (LIB) energy storage systems (ESS) have emerged as a critical component in the transition away from fossil fuel-based energy generation, offering immense potential in achieving a sustainable environment. This study conducts an in-depth analysis of grid-connected LIB ESS patents published from 1998 to 2022, aiming to comprehend essential developments and trends in the technology landscape while identifying key players and inventors. Employing extensive keyword searches within the Lens database, 95 patent documents were extracted along with the bibliometric data. The research highlights two prominent factors in the field of grid-connected LIB ESS patents. Firstly, a detailed patent bibliometric analysis including patent growth trends, keyword analysis, patent distribution over jurisdiction, and subject categories was presented. Moreover, the research identifies key owners, inventors and hierarchical jurisdiction in patent document publishing and evaluates the possibilities for future research sustainability. Secondly, detailed updates regarding technological advancements that are driving sustainable grid-connected LIB ESS development in various sectors such as; gird connected ESS, power conversion system (PCS), energy management system (EMS) and transportation sector are provided. The study concluded that the patents related to grid-connected ESS, minimizing voltage and frequency regulation to achieve grid stability and EMS of LIB are the key trending topics in the field of grid-connected LIB ESS. The comprehensive analysis not only illuminates crucial trends but also provides valuable guidance to future researchers and industry stakeholders, facilitating the path towards sustainable grid-connected LIB ESS and paving the way for a more environmentally conscious energy landscape.

Techno-economic assessment of small-size residential solar PV + battery systems under different tariff structures in Brazil

This paper proposes a methodology to assess the energy and economic impact of adopting small-scale residential photovoltaic (PV) systems paired with lithium-ion battery energy storage (BESS) systems in single-family homes, under the current energy feed-in legislation. The suggested methodology was applied to a case study of a prosumer unit (PU) in Brazil. Data from energy bills, measured PV generation, BESS behaviour, and energy consumption were analysed to compare different viewpoints and estimate key economic indicators. As a result, the PV + BESS combination increases residential users' energy self-consumption and self-sufficiency, resulting in respective increases of 15 % and 2 %. Under the conventional tariff, adopting the PV + BESS system led to an average 29 % reduction in electricity costs compared to scenarios without PV + BESS. Furthermore, by transitioning to the white tariff mode in conjunction with PV + BESS, the PU achieved a 49 % reduction. This result emphasizes the advantages of time-of-use adoption for PV + BESS consumers. A greater discrepancy between tariff periods enhances the feasibility of storing off-peak energy for use during peak periods. Currently, BESS implementation costs impede competitiveness, with attractive LCOS metrics achieved only at costs below $600.00/kWh and MRAs below 9 %. BESS + PV lowers generation costs compared to off-peak rates, increasing the viability of shared usage. Integrating PV + BESS systems with rate switching significantly diminishes electricity expenses. The substantial BESS implementation cost necessitates a noteworthy rate differential for viability, which could potentially impact non-PV and non-BESS consumers.

Alternative Energy Options for a Thai Durian Farm: Feasibility Study and Experiments for the Combination of Solar Photovoltaics and Repurposed Lithium-Ion Batteries

This research examines the viability of incorporating a second-life lithium-ion battery energy storage system with a solar photovoltaic power source to facilitate energy acquisition in two irrigation scenarios at a durian farm located in Thailand. The first option entails selecting the battery with suitable dimensions to effectively harness solar energy following morning irrigation, while the second option involves sizing the battery specifically for storing solar energy solely for the purpose of powering the motor pump. This study conducts an analysis on the degradation of the battery, focusing on the influence of specific environmental conditions and its specification. The degradation analysis employs polynomial functions as an alternative to exponential semi-empirical stress models for fitting stress models. This approach demonstrates a robust fit, as evidenced by a high R-squared value of approximately 1. The economic analysis considers various factors, including solar irradiance derating factors, battery deterioration rate, and photovoltaic power ratings for all scenarios. The sensitivity analysis evaluates the variations in irradiance and costs associated with the battery. When solar radiation levels surpass 500 W/m2 and the cost of the battery remains below $100/kWh, the estimated payback period is approximately 5 years over the duration of the 10-year project lifespan.

A fast-response preheating system coupled with supercapacitor and electric conductive phase change materials for lithium-ion battery energy storage system at low temperatures

The electrochemical performance of lithium batteries deteriorates seriously at low temperatures, resulting in a slower response speed of the energy storage system (ESS). In the ESS, supercapacitor (SC) can operate at −40 °C and reserve time for battery preheating. However, the current battery preheating strategy has a slow heating rate and cannot preheat batteries to a comfortable temperature range during the time reserved by SC. This study proposes a preheating system that combines the instantaneous high-power discharge of SC with the efficient electro-to-thermal conversion of ECPCM, which has a super-fast preheating rate and contributes to the fast response of ESS at low temperatures. Under extreme conditions of −40 °C, the preheating system can recover >85 % discharge capacity and voltage of the battery system in 2 min. By adjusting SC capacitance and ECPCM resistance, the preheating rate of the battery system can reach 69.5 °C/min, and the temperature difference is less than 5 °C. Moreover, the pulse current of SC can reduce the temperature difference inside the battery within 5 °C. The preheating system can also enable the battery system quickly enter super-charging mode, greatly reducing the charging time. The total charging time was reduced by 72 % when the battery pack was preheated to 20 °C. Nevertheless, based on the outcome of this study, this preheating strategy can effectively improve the low-temperature response speed of the ESS and meet the requirements of the microgrid.

Research on frequency modulation capacity configuration and control strategy of multiple energy storage auxiliary thermal power unit

The rapid development of new energy sources has had an enormous impact on the existing power grid structure to support the “dual carbon” goal and the construction of a new type of power system, make thermal power units better cope with the impact on the original grid structure under the background of the rapid development of new energy sources, promote the consumption of new energy sources such as solar and wind energy, and further expand the channels for upgrading and flexibility transformation of thermal power energy storage, improve the stability, safety and economy of thermal power unit operation. Therefore, based on the research status at home and abroad, a hybrid energy storage system is added to solve the above problems. The lithium battery-flywheel control strategy and the regional dynamic primary frequency modulation model of thermal power units are proposed, and study the capacity configuration scheme of flywheel‑lithium battery hybrid energy storage system under a certain energy storage capacity, the frequency modulation performance is evaluated by the system frequency fluctuation degree, fluctuation peak range and other indicators. Study under a certain energy storage capacity thermal power unit coupling hybrid energy storage system to participate in a frequency modulation of the optimal capacity configuration scheme, and perform simulation verification using MATLAB/Simulink. When the thermal power unit is coupled with a 10.8612 MW/2.7151 MWh flywheel energy storage system and a 4.1378 MW/16.5491 MWh lithium battery energy storage system, while adaptive variable coefficient droop control is adopted, the system frequency range is 0.00328 p.u.Hz, and the fluctuation degree of the output power of the thermal power units is 0.00498 p.u.MW, compared to the individual frequency regulation of thermal power units, it reduces 52.07 % and. The results show that when the thermal power unit is disturbed by external load, hybrid energy storage assisted thermal power unit frequency modulation reduces the mechanical loss of thermal power unit to a certain extent and extends the service life of the unit, effectively improve the operation stability and economy of thermal power units, further reduce the phenomenon of abandoning wind and light, and better promote the utilization of new energy.

Fire Accident Risk Analysis of Lithium Battery Energy Storage Systems during Maritime Transportation

The lithium battery energy storage system (LBESS) has been rapidly developed and applied in engineering in recent years. Maritime transportation has the advantages of large volume, low cost, and less energy consumption, which is the main transportation mode for importing and exporting LBESS; nevertheless, a fire accident is the leading accident type in the transportation process of LBESS. This paper applied fault tree analysis and Bayesian network methods to evaluate the fire accident risk of LBESS in the process of maritime transportation. The Bayesian network was constructed via GeNIe 2.3 software, and the probability of LBESS fire accidents during maritime transportation was calculated based on the probability of basic events occurring. The results showed that an unsuitable firefighting system for putting out lithium battery fires, high humidity, and monitoring equipment without a real-time alarm function have the most significant influence on the occurrence of LBESS fire accidents during maritime transportation. The research work of this paper provides a theoretical basis for the risk assessment of LBESS during maritime transportation.

State of health estimation of lithium-ion battery considering sensor uncertainty

The state of health (SOH) is closely related to the stable operation of lithium-ion (Li-ion) battery energy storage systems. Existing methods for SOH estimation assume a reliable multi-source sensor in the battery management system, yet the sensors are prone to failures leading to abnormal measurement data in practical applications. To alleviate the above issue, this paper proposes a detection before fusion multi-model framework (DFMF) considering the uncertainties of multi-source sensor data. Firstly, a density-based spatial clustering of applications with noise is adopted to identify the working states of sensors via detecting the faults from their raw data. Then, the working states of sensors are fed to a state machine to realize the fault isolation. Finally, a data-driven SOH estimation based on multi-source sensors is developed, which includes both the single-sensor mode and the multi-sensor joint mode. The proposed DFMF is validated on two degradation datasets from different aging conditions and chemistries. The experimental results demonstrate the proposed DFMF has a high accuracy and strong robustness in Li-ion SOH estimation. It is noted that the DFMF can provide SOH estimation results with the root mean squared error within 1.68 % and 1.17 % on the two datasets, respectively.

Research on Safety Operation and Maintenance Management and Health Status Assessment for Lithium Battery Energy Storage System

The safe operation and maintenance of lithium batteries not only needs to monitor the working status of lithium batteries timely and accurately, but also needs to evaluate its health status and automatically switch the backup battery when safety hazards are found. However, research on the safe operation and maintenance of lithium batteries is still lacking. In light of this, this paper constructs a safe operation and maintenance mechanism by monitoring the voltage and surface temperature of the lithium battery. In addition, a novel online health assessment model based on GRU-CNN is proposed to find out the potential safety hazards of lithium batteries timely. The working voltage, current and ambient temperature are used as the input features of the model to predict the degradation of lithium batteries in advance. In addition, a security operation and maintenance controller is designed to quickly switch the backup battery pack when a lithium battery pack appears to have performance degradation or security risks. The system realizes the real-time monitoring of the safe operation of lithium batteries and the rapid assessment of health status, providing technical guarantees for the reliable, stable, and safe operation of the lithium battery system. The experimental comparison verified that the proposed assessment model of the status of health (SOH for short) has less prediction error.

Operational risk analysis of a containerized lithium-ion battery energy storage system based on STPA and fuzzy evaluation

Lithium-ion battery energy storage system (BESS) has rapidly developed and widely applied due to its high energy density and high flexibility. However, the frequent occurrence of fire and explosion accidents has raised significant concerns about the safety of these systems. To evaluate the safety of such systems scientifically and comprehensively, this work focuses on a MW-level containerized lithium-ion BESS with the system-theoretic process analysis (STPA) method. The work identified 53 unsafe control actions and corresponding loss scenarios. By combining loss scenarios and expert evaluation opinions, the key risk factors for system operation are obtained. Finally, this work proposed corresponding countermeasures and suggestions to address the key risk factors and improve the safety and reliability of the entire system operation. This work discusses the operational risks of MW-class containerized lithium-ion BESS and provides technical guidance for engineers in system designs, safe operations, and engineering applications.