Stationary Battery Energy Storage Research Articles

Enhanced Kullback–Leibler Divergence Based Pilot Protection for Lines Connecting Battery Energy Storage Stations

In light of the challenges faced by existing protection methods when battery energy storage station (BESS) and various nonideal conditions emerge, enhanced Kullback–Leibler divergence-based time-domain pilot protection is put forward in this article. Given the discrepancy in current waveforms between internal and external faults, KLD is employed to quantify the degree of similarity between two current waveforms, enabling the accurate distinction between internal and external faults. To eliminate the asymmetry of KLD, improved KLD(IKLD) is introduced. Whereafter, a technique is proposed to convert the current sampling sequence into a probability distribution that can be utilized by IKLD. To counteract the negative influence of current transformer(CT) saturation on IKLD-based protection, the time-domain waveform features of summation current are adequately employed to develop an enhanced KLD(EKLD). Further, high and low thresholds are legitimately designed to ensure both dependability and security. The flowchart of EKLD-based pilot protection is described, and its effectiveness is extensively validated by variation in fault resistance, location, type and operating mode of BESS using PSCAD and a hardware-in-the-loop(HIL) testing platform. Additionally, proposed protection outclasses power frequency component-based current differential protection and some up-to-date presented time-domain protection methods.

Explosion characteristics of two-phase ejecta from large-capacity lithium iron phosphate batteries

When a thermal runaway accident occurs in a lithium-ion battery energy storage station, the battery emits a large amount of flammable electrolyte vapor and thermal runaway gas, which may cause serious combustion and explosion accidents when they are ignited in a confined space. With the gradual development of large-scale energy storage batteries, the composition and explosive characteristics of thermal runaway products in large-scale lithium iron phosphate batteries for energy storage remain unclear. In this paper, the content and components of the two-phase eruption substances of 340Ah lithium iron phosphate battery were determined through experiments, and the explosion parameters of the two-phase battery eruptions were studied by using the improved and optimized 20L spherical explosion parameter test system, which reveals the explosion law and hazards of the two-phase battery eruptions. Studies have shown that in a two-phase system explosion, EMC can make the two-phase system more explosive and more powerful, and the thermal runaway gas expands its explosion concentration range. The coupling explosion of the two enhanced the sensitivity and explosive power of the two-phase ejecta. Increasing the concentration of any combustible in a two-phase system will cause the explosion intensity parameters of the system to increase. However, when the combustible concentration exceeds the optimal explosion concentration, the explosion intensity parameters will decrease or even no explosion will occur. Both explosion intensity parameters and sensitivity parameters are more sensitive to EMC concentration, and the higher the EMC concentration, the stronger its dominant role in the explosion of the two-phase system. This work can lay the foundation for revealing the disaster-causing mechanism of explosion accidents in lithium-ion battery energy storage power stations, guide the safe design of energy storage systems and the prevention and control of explosion accidents, and provide theoretical and data support for the investigation of explosion accidents in energy storage power stations.

High-uniformity liquid-cooling network designing approach for energy storage systems by graph-coupled genetic algorithm

Electrochemical battery energy storage stations have been widely used in power grid systems and other fields. Controlling the temperature of numerous batteries in the energy storage station to be uniform and appropriate is crucial for their safe and efficient operation. Thus, effective thermal management is required. In this work, an approach for rapid and efficient design of the liquid cooling system for the stations was proposed. A hydraulic solution model for the liquid-cooling network was established based on graph theory principles, and the genetic algorithm was employed for automatic system optimization to achieve high cost-effectiveness and ideal temperature distribution. Experiments were conducted to validate the accuracy of the hydraulic model and evaluate the efficacy of the optimization strategy. The flow rate calculated from the hydraulic model agreed well with the experiments, with a discrepancy smaller than 3.5 %, and the uniformity of flow rates was improved to as high as 70 % after the optimization. Furthermore, the applicability of this approach was also confirmed across various sizes of energy storage systems.

Fault diagnosis technology overview for lithium‐ion battery energy storage station

AbstractWith an increasing number of lithium‐ion battery (LIB) energy storage station being built globally, safety accidents occur frequently. Diagnosing faults accurately and quickly can effectively avoid safe accidents. However, few studies have provided a detailed summary of lithium‐ion battery energy storage station fault diagnosis methods. In this paper, an overview of topologies, protection equipment, data acquisition and data transmission systems is firstly presented, which is related to the safety of the LIB energy storage power station. Then, existing fault diagnosis technologies are reviewed in detail. Finally, the future developing trends of fault diagnosis technology are discussed.

Optimal allocation of autonomous PV-powered fast charging stations for electrified transportation considering traffic dynamics

In response to the imperative to reduce greenhouse gas emissions, global efforts are focusing on electrifying transportation and adopting renewable energy sources. This necessitates establishing reliable fast-charging stations (FCSs) for the widespread integration of electric vehicles (EVs). Indeed, the arbitrary distribution of FCSs can detrimentally affect the efficiency of traffic movement. Thus, this paper presents a planning methodology aimed at optimizing the allocation of FCSs within large-scale transportation networks. The energy system proposed includes an autonomous photovoltaic (PV)-powered FCS based on a DC microgrid, supplemented by a stationary battery energy storage system for backup power. The behavior of EVs within the traffic flow is modeled using a realistic traffic simulation software called Dynamic Network Assignment Simulation for Advanced Road Telematics (DYNASMAT). The conflicting objectives of minimizing total annual costs and EV average waiting time at stations are addressed through multi-objective optimization. To solve this optimization problem, the GAMS software is employed. A transportation network with 92 nodes and 284 links is utilized to test the proposed approach. The proposed autonomous PV-powered FCS is compared with Natural Gas-fired Distributed Generators (NGDG)-powered FCS. The simulation results show that while the NGDG-powered FCS exhibits higher emissions, the autonomous PV-powered equivalent operates emission-free. However, the annual cost of the autonomous PV-powered FCS is higher than that of the NGDG-powered FCS.

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer’s side of the utility’s service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it’s benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability.Lithium titanate (Li4Ti5O12, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LNMO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase.The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LNMO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding was provided by the U.S. Department of Energy's Vehicle Technologies Office under the Behind-the-Meter Storage (BTMS) Consortium directed by Samuel Gillard and managed by Anthony Burrell. The electrodes used in this manuscript are from Argonne's Cell Analysis, Modeling and Prototyping (CAMP) Facility, which is fully supported by the DOE Vehicle Technologies Office (VTO). The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

Long-Term Calendar Aging across Commercial Lithium-Ion Cell Chemistries - Part II: Modeling and Early Prediction

Lithium-ion (Li-ion) batteries are widely used in applications such as mobility, stationary grid systems, and various consumer and commercial systems. In electric vehicles (EVs), batteries often remain idle, with only about 10% utilization. Moreover, in stationary battery energy storage systems (BESS) designed for peak shaving, resting periods tend to cause more aging effects than the operational cycles. Consequently, quantifying the effect of calendar aging is crucial. However, current calendar aging models are inadequate for accurately modeling and predicting the diverse aging behaviors of commercial Li-ion batteries. In this study, we analyze a new, long-term Li-ion battery calendar aging dataset, which includes eight different commercial battery types. We compare and validate three calendar aging models—semi-empirical, symbolic regression, and Long Short-Term Memory Network (LSTM). We examine the transferability of these models across various commercial cell types, offering insights into their generalizability. Additionally, we introduce a novel trajectory-to-trajectory approach for early prediction of calendar aging lifetime. For the first time, we investigate the model's ability to interpolate and extrapolate aging behavior under different storage temperatures. This research provides practical insights for optimizing battery management strategies in conditions dominated by calendar aging.

Investigating the influence of erratic grid on stationary battery energy storage technologies in hybrid power systems: Techno-environ-economic perspectives

Several obstacles impede renewable energy penetration into the global energy sector. Amongst the apparent challenges which require credible research attention, is the selection of appropriate energy storage technologies in the context of intermittent renewable resources and frequent grid outages. Given these, the present study investigated the technical, economic, and environmental effects of an erratic national grid on four distinct battery technologies in hybrid wind, solar, and diesel energy systems. The study was conducted at Baze University Abuja, Nigeria using the Hybrid Optimization Model for Electric Renewables software. The battery types considered are vanadium redox flow battery (VRB), lead-acid battery, nickel-iron battery, and lithium-ion battery (LIB). The VRB-based hybrid energy systems demonstrated superior performances in meeting the electricity demands of the university at the lowest net present cost, levelized cost of energy, and carbon dioxide emissions of $6,328,003.00, $0.0722/kWh, and 21,754 kg/year respectively. This battery technology is characterized by storage depletion, throughput, and losses of 796 kWh/year, 406,570 kWh/year, and 182,757 kWh/year respectively. The sensitivity analysis showed that the frequency and duration of main grid outages affect the optimal systems’ economics, component sizes, battery energy losses, battery energy storage depletion, and renewable energy penetration.

Adaptive faulty phase selector for microgrids including battery energy storage stations

Battery energy storage stations (BESSs) hold promising market potential within microgrids, serving as a complementary solution to mitigate fluctuations in renewable distributed generations and providing backup power during microgrid outages or emergencies. However, the distinct fault signatures of BESSs, compared to conventional synchronous generator (SG)-based sources, can result in misoperation of the widely-used superimposed current magnitude (SCM)-based faulty phase selector (FPS), which has received limited attention in previous research. Moreover, the variable operation modes of the microgrid further deteriorate the working condition of the SCM-based FPS. As a consequence, the potential misidentification of faulty phase(s) in the presence of BESS violates the selective phase tripping requirements in existing microgrids. To achieve precise selection of faulty phase(s), this paper proposes a novel FPS based on the generalized magnitude ratio (GMR). Firstly, the proposed FPS applies a compensation method to SCM and extends it to the superimposed voltage magnitude (SVM), mitigating the adverse impacts caused by the unbalanced sequence impedance of BESS. Subsequently, the GMR, which integrates both the compensated SCM and SVM information, is constructed to enhance the adaptability of phase selection to the uncertain infeed level at the BESS side. Finally, the faulty type and specific faulty phase(s) are determined based on the sorted results of the GMR values for each phase. Comprehensive simulation results affirm the expected performance of the proposed FPS under various microgrid modes, as well as different BESS discharge/charge statuses.

A monitoring and early warning platform for energy storage systems based on big data analysis

This article focuses on the safe operation of lithium battery energy storage power stations and develops a data monitoring and safety warning platform for energy storage systems. The background, architecture, implementation methods, and main functions of the platform development are introduced in sequence. This platform significantly improves the safety of energy storage stations by implementing active safety monitoring and early warning, which is of great significance for the large-scale application and promotion of lithium battery energy storage stations.

A real-time thermal behaviour monitoring and analysis of a 500 kWh grid-connected battery energy storage system

Statistical analysis yields critical data for risk evaluation and management of a stationary battery energy storage system (BESS). Lithium-ion (Li-ion) batteries have attained huge attention for both stationary and non-stationary applications due to their lucrative features such as lightweight, high energy density efficiency, and long lifespan. However, detailed analysis and trends subjected to thermal behaviour of the device especially in grid-connected BESS application is still neglected. Therefore, this paper presents a statistical analysis for thermal behaviour of a grid connected BESS. The significance of Li-ion battery employing battery thermal management is presented, which can guarantee a reliable and safe operation as well as examining the effect of voltage, current and state of charge (SOC) on BESS operation. The large group of datasets recorded daily with five-minute intervals are difficult to be analysed numerically in a timely manner. Thus, the analysis can be made by visualizing the numerical data that was retrieved through representational state transfer (REST API) for easier interpretation and trend analysis. The visualization is made using Microsoft Power BI and presented in this paper.

Counterflow canopy-to-canopy and U-turn liquid cooling solutions for battery modules in stationary Battery Energy Storage Systems

This work documents the liquid cooling solutions of Li-ion battery for stationary Battery Energy Storage Systems. Unlike the batteries used in Electric Vehicles which allow to use liquid cold plates, here the cooling must be implemented at the scale of modules filled with three rows of 14 cells each. Before moving to the scale of the modules, two different numerical cell models are developed and compared. One determines the temperature fields while the heat generated during the cell discharge is calculated simultaneously with the voltage changes. The other model uses the heat generated as input data, leading to similar temperature distributions throughout the cells and to much shorter computational times. At the module level, the two different configurations studied are U-turn cooling, inspired from cooling systems found in certain Electric Vehicles, and counterflow canopy-to-canopy cooling, a solution allowing a better control of the thermal exchanges. It is shown that while the two options are based on the same volume of fluid and lead to similar pressure losses, the counterflow canopy-to-canopy presents the advantage of a better control of the volumetric temperature distribution throughout the entire module.

Optimal day-ahead large-scale battery dispatch model for multi-regulation participation considering full timescale uncertainties

Grid scale battery integration plays an important role in renewable energy integration and the formation of smart grid. To mitigate the problems of insufficient frequency response and peak regulation capacities faced by modern power grids with high wind energy uptake, a day-ahead optimization dispatch strategy considering operational risks is proposed in this study. In the day-ahead dispatch model, generation units and a large-scale battery energy storage station (LS-BESS) are coordinated to participate in multi-type frequency control ancillary services (FCASs). For optimal performance, scheduling in different timescales and the complementarity between power and energy types of requirements are coordinated, with various service uncertainties considered. Then the conditional value-at-risk theory is utilized to achieve the optimal mix of multiple resources for day-ahead regulation reserves, to realize the minimum operation cost. To tackle the uncertainty of wind power over a large timescale, a robust optimization (RO) approach based on the budget uncertainty set is employed, which considers robustness and economy. This can help avoid over-conservation of the standard RO and enhance the applicability of the decisions made. Simulation studies and comparison analysis of multiple schemes verify the effectiveness of the proposed optimal day-ahead dispatch strategy, which also demonstrate that a LS-BESS participating in multiple FCASs for day-ahead dispatch can help realize secure, reliable, and economic power grid.

Energy Efficiency Evaluation for Battery Energy Storage Stations Based on AHP-TOPSIS

The development of energy storage is a necessary support for the realization of the green energy future. At present, battery energy storage stations (BESSs) consume large amounts of energy, the energy loss relationships between various devices in a station are complex, and there is a lack of energy loss analysis and statistical methods for BESSs. It poses challenges to the further development of BESSs in the power grid. To deal with this issue, this paper establishes the energy loss indicators and proposes the energy loss evaluation methods for BESSs. The simulation results verify that the proposed method can accurately reflect the overall energy loss level of the BESSs and the proposed method of energy loss estimation and analysis can support the development of energy saving and loss reduction.

A novel fault diagnosis method for battery energy storage station based on differential current

Nowadays, an increasing number of battery energy storage station (BESS) is constructed to support the power grid with high penetration of renewable energy sources. However, many accidents occurred in BESSs threaten the development of the BESS, so it is important to develop a protection method for the BESS. In this work, a novel fault diagnosis method based on differential current is proposed, which can identify the short circuit fault rapidly and effectively. Firstly, in order to simulate the short circuit fault characteristic of a BESS, a linear varying parameter battery equivalent circuit model (ECM) which can demonstrate the short circuit current are established based on the manta ray foraging optimization (MRFO) algorithm. Secondly, the fault diagnosis method based on differential current is proposed and analyzed through the calculation of short circuit current (SCC) in BESS. Finally, different working state data of battery are used to verify the fault diagnosis method. The results show that the proposed method can effectively diagnose the short circuit fault. In summary, the proposed fault diagnosis method based on differential current is efficient in protecting the BESS.

Trends, Technology Developments and Future Prospects of Stationary Battery Energy Storage Systems for Power Grid

Trends, Technology Developments and Future Prospects of Stationary Battery Energy Storage Systems for Power Grid

Operation optimization of battery swapping stations with photovoltaics and battery energy storage stations supplied by transformer spare capacity

AbstractDriven by the demand for carbon emission reduction and environmental protection, battery swapping stations (BSS) with battery energy storage stations (BESS) and distributed generation (DG) have become one of the key technologies to achieve the goal of emission peaking and carbon neutrality. Therefore, this paper proposes a strategy to optimize the operation of BSS with photovoltaics (PV) and BESS supplied by transformer spare capacity. Firstly, it introduces the operation mechanism of BSS and uses the spare capacity of building special transformers and the roof PV to supply power to BSS to avoid the investment of transformers. Secondly, this paper establishes the load model of BSS and proposes the charging rules of battery swapping. Thirdly, a segmented pricing mechanism for the rental price of special transformers is formulated to guide BSS operators to preferentially rent spare capacity during low load rate periods. Aiming at the maximum daily profit of BSS, an optimization model is established to optimize the number of batteries to be charged and the charging status of BESS in each period; on this basis, the demand response model is further proposed. Simulation results show that the proposed strategy can improve the daily profit of BSS through shifting load. And the configuration of BESS can improve the battery swapping capacity and peak‐shaving ability. Moreover, the exponential segmented pricing mechanism can greatly reduce the number of high load periods and reduce the burden on the power supply.

Public policy and strategic business recommendations to accelerate adoption of stationary battery energy storage systems (BESS) in India

PurposeInterest in battery energy storage systems (BESS) is high, and technologies such as Li-ion (and other advanced chemistry) batteries in specific use cases are already economically viable. In this paper, the authors build further on the authors' previously published paper1 to estimate the potential positive impact that accelerated adoption of Li-ion batteries for stationary storage per the authors' identified already economically viable use cases, can have both on India's macro-economy and current account deficit as well as in helping meaningfully accelerate circular economy and Sustainable Development Goals (SDG) benefits of green economy transition.Design/methodology/approachThe authors identified key challenges for development of BESS ecosystem and applied quantitative and qualitative assessment methodology for rapid adoption of BESS in India. The authors' study was validated through interviews with stakeholders and the authors summarize applicable findings for emerging countries such as India to encourage faster, wider adoption of energy storage.FindingsThe authors' study provides key policy recommendations to achieve a better balance in policy focus—not only for electronic vehicles (EVs) and utility-scale storage, but also for stationary behind-the-meter storage through key policy measures including placing a CESS on diesel generators (DGs), differential tariffs, encouraging advanced battery imports as a way to reduce crude oil imports, green financing and investments in de-carbonized energy breakthrough technologies (e.g. gravity-based energy storage systems). The authors recommend key technology priorities and strategic business rationale for private sector efforts by developing competitive advantages for non-battery hardware and software and expanding into emerging markets, with potential US$15–20+bn enterprise value.Originality/valueWhile the dominant discourse focuses on EVs and utility scale applications of storage, the authors' paper shows the larger near term opportunity for impact is in stationary storage that too in end-user adoption use cases.

A generic and scalable dynamic model for stationary battery energy storage systems

A generic and scalable dynamic model for stationary battery energy storage systems

Power curves of megawatt-scale battery storage technologies for frequency regulation and energy trading

Large-scale stationary battery energy storage systems (BESS) continue to increase in number and size. Most systems have been put into operation for grid services because of their technical capabilities. With increasing and more dynamic energy prices, their use in short-term energy trading such as day-ahead and intraday trading has also been gaining importance. In current technical and economic simulations and trading models, batteries are often used as an energy reservoir that can charge and discharge a constant power specified by the energy over a certain time. However, this simplification can lead to wrong results and makes economic assessments difficult. In order to successfully use BESS in energy trading, their real operating ranges and limits must be investigated, since batteries respectively BESS cannot deliver the same power over the entire state of charge (SOC) range. With a performance test of our hybrid BESS M5BAT, we show the characteristic performance curves for different battery technologies and consequently suitable operating ranges in a large-scale system configuration. The results show the wide range of challenges such as battery aging and balancing states that occur in the real-world implementation of BESS. The lithium-ion batteries of the system under test have a remaining usable energy between 75 % and 90 %, depending on the type of lithium-ion battery, while the usable energy of the lead acid batteries is only 60 %. The lithium-ion batteries were able to deliver a constant power output in the SOC range between 10 % and 80 %, which is a necessary requirement in short-term energy trading. The lead-acid batteries could only be discharged at full power in the range of 100 %–50 % SOC and charged at full power between 0 % and 50 %. In the performance test, balancing was a limiting factor for lithium-ion batteries, while aging was the limiting factor for lead-acid batteries. Based on our findings, estimates for other existing BESS can be made to determine feasible operating ranges of these batteries for short-term energy trading. This also provides a guideline for individual tests that should be carried out on other BESS for verification.