Grid-scale Battery Energy Storage System Research Articles

Early prediction of battery degradation in grid-scale battery energy storage system using extreme gradient boosting algorithm

The growth of battery energy storage systems (BESS) is caused by the variability and intermittent nature of high demand and renewable power generation at the network scale. In the context of BESS, Lithium-ion (Li-ion) battery occupies a crucial position, although it is faced with challenges related to performance battery degradation over time due to electrochemical processes. This battery degradation is a crucial factor to account for, based on its potential to diminish the efficiency and safety of electrical system equipment, thereby contributing to increased system planning costs. This implies that the health of battery needs to be diagnosed, particularly by determining remaining useful life (RUL), to avoid unexpected operational costs and ensure system safety. Therefore, this study aimed to use machine learning models, specifically extreme gradient boosting (XGBoost) algorithm, to estimate RUL, with a focus on the temperature variable, an aspect that had been previously underemphasized. Utilizing XGBoost model, along with fine-tuning its hyperparameters, proved to be a more accurate and efficient method for predicting RUL. The evaluation of the model yielded promising outcomes, with a root mean square error (RMSE) of 90.1 and a mean absolute percentage error (MAPE) of 7.5 %. Additionally, the results showed that the model could improve RUL predictions for batteries within BESS. This study significantly contributed to optimizing planning and operations for BESS, as well as developing more efficient and effective maintenance strategies.

The Role of Energy Density for Grid-Scale Batteries

For grid-scale battery energy storage systems it is often presumed that cell level energy density is not too important. Yet, countless publications highlight low energy density as the key limitation of technologies such as redox flow batteries or aqueous alkali-ion batteries that are inherently developed for stationary applications.Here, we resolve this apparent conflict by quantifying the areal energy density, expressed in kWh m-2, of over forty MWh-scale battery energy storage systems deployed around the world.[1] Via satellite imagery we compare lithium-ion, sodium-sulfur, and flow battery projects and show that the amount of energy that is stored per land area is often comparable between these technologies, even though the energy density on cell level varies by an order of magnitude. We highlight excellent safety and vertical scalability as key untapped advantages of aqueous batteries and provide examples of where they can excel, besides simply competing with state-of-the-art lithium-ion batteries. We show, for example, that MWh-scale aqueous flow batteries can safely be deployed underground and within buildings, feats that due to safety constraints are not possible with current lithium-ion batteries at this scale.Seeing satellite images of battery installations near solar farms is a humbling experience that every researcher working in the field should come across and we provide the locations of all the examined battery installations in a Google Earth file. Grasping the fantastical scale at which renewables are, and must continue to be, deployed certainly provides some perspective regarding energy density of individual battery cells. [1] Reber, D., Jarvis, S.R., Marshak, M.P., The role of energy density for grid-scale batteries, ChemRxiv, 2022, doi: 10.26434/chemrxiv-2022-5ddhs

A Model-Aware Comprehensive Tool for Battery Energy Storage System Sizing

This paper presents a parametric procedure to size a hybrid system consisting of renewable generation (wind turbines and photovoltaic panels) and Battery Energy Storage Systems (BESS). To cope with the increasing installation of grid-scale BESS, an innovative, fast and flexible procedure for evaluating an efficient size for this asset has been developed. The tool exploits a high-fidelity empirical model to assess stand-alone BESS or hybrid power plants under different service stacking configurations. The economic performance has been evaluated considering the revenue stacking that occurs when participating in up to four distinct energy markets and the degradation of the BESS performances due to both cycle- and calendar-aging. The parametric nature of the tool enables the investigation of a wide range of system parameters, including novel BESS control logic, market prices, and energy production. The presented outcomes detail the techno-economic performances of a hybrid system over a 20-year scenario, proposing a sensitivity analysis of both technical and economic parameters. The case study results highlight the necessity of steering BESS investment towards the coupling of RES and accurate planning of the service stacking. Indeed, the implementation of a storage system in an energy district improves the internal rate of return of the project by up to 10% in the best-case scenario. Moreover, accurate service stacking has shown a boost in revenues by up to 44% with the same degradation.

Large-scale energy storage system: safety and risk assessment

The International Renewable Energy Agency predicts that with current national policies, targets and energy plans, global renewable energy shares are expected to reach 36% and 3400 GWh of stationary energy storage by 2050. However, IRENA Energy Transformation Scenario forecasts that these targets should be at 61% and 9000 GWh to achieve net zero carbon emissions by 2050 and limit the global temperature rise within the twenty-first century to under 2 °C. Despite widely known hazards and safety design of grid-scale battery energy storage systems, there is a lack of established risk management schemes and models as compared to the chemical, aviation, nuclear and the petroleum industry. Incidents of battery storage facility fires and explosions are reported every year since 2018, resulting in human injuries, and millions of US dollars in loss of asset and operation. Traditional risk assessment practices such as ETA, FTA, FMEA, HAZOP and STPA are becoming inadequate for accident prevention and mitigation of complex energy power systems. This work describes an improved risk assessment approach for analyzing safety designs in the battery energy storage system incorporated in large-scale solar to improve accident prevention and mitigation, via incorporating probabilistic event tree and systems theoretic analysis. The causal factors and mitigation measures are presented. The risk assessment framework presented is expected to benefit the Energy Commission and Sustainable Energy Development Authority, and Department of Standards in determining safety engineering guidelines and protocols for future large-scale renewable energy projects. Stakeholders and Utility companies will benefit from improved safety and reliability by avoiding high-cost asset damages and downtimes due to accident events.

Impact of the splitting of the German–Austrian electricity bidding zone on investment in a grid-scale battery energy storage system deployed for price arbitrage with gray and green power in Austrian and German day-ahead power markets

The splitting of the German–Austrian electricity bidding zone in October 2018 established limits for cross-border exchanges of power between Germany and Austria, which led to the decoupling of German and Austrian wholesale power prices. We analyze the impact of the split on the investment in lithium-ion grid-scale battery energy storage systems (BESS) used for intertemporal arbitrage in German and Austrian day-ahead power markets with hourly contracts operated by the Energy Exchange of Austria. The paper was written in response to the increasing share of green power in the national energy mix of the two countries, followed by a similar development in the volume of green power traded. Arbitrage with green power was analyzed and compared to arbitrage with power from conventional sources using a robust mixed-integer linear programming (MILP) model extended with a battery degradation process. The model was solved for different levels of depth of discharge (DOD) to identify the optimum between cycle life and calendar aging with respect to prevailing market conditions. Using predicted costs of battery, a break-even point was reached with 60% DOD identified as the optimal pattern for the dispatch of the BESS. A separate scenario was considered for the analysis of the impact of moving from the perfect knowledge of future prices to a situation where day-ahead prices are forecasted using the seasonal autoregressive integrated moving average (SARIMA) model.

Optimal Sizing of Grid-Scaled Battery with Consideration of Battery Installation and System Power-Generation Costs

Variable renewable energy (VRE) generation changes the shape of residual demand curves, contributing to the high operating costs of conventional generators. Moreover, the variable characteristics of VRE cause a mismatch between electricity demand and power generation, resulting in a greater expected energy not supplied (EENS) value. EENS involves an expected outage cost, which is one of the important components of power-generation costs. A utility-scale battery energy storage system (BESS) is popularly used to provide ancillary services to mitigate the VRE impact. The general BESS ancillary-service applications are as a spinning reserve, for regulation, and for ramping. A method to determine optimal sizing and the optimal daily-operation schedule of a grid-scale BESS (to compensate for the negative impacts of VRE in terms of operating costs, power-generation-reliability constraints, avoided expected-outage costs, and the installation cost of the BESS) is proposed in this paper. Moreover, the optimal BESS application at a specific time during the day can be selected. The method is based on a multiple-BESS-applications unit-commitment problem (MB-UC), which is solved by mixed-integer programming (MIP). The results show a different period for a BESS to operate at its best value in each application, and more benefits are found when operating the BESS in multiple applications.

Challenges and Mitigation Measures in Power Systems with High Share of Renewables—The Australian Experience

Australia is one of the leading countries in energy transition, and its largest power system is intended to securely operate with up to 75% of variable renewable generation by 2025. High-inertia synchronous condensers, battery energy storage systems, and grid-forming converters are some of the technologies supporting this transformation while facilitating the secure operation of the grid. Synchronous condensers have enabled 2500 MW of solar and wind generation in the state of South Australia, reaching minimum operational demands of ≈100 MW. Grid-scale battery energy storage systems have demonstrated not only market benefits by cutting costs to consumers but also essential grid services during contingencies. Fast frequency response, synthetic inertia, and high fault currents are some of the grid-supporting capabilities provided by new developments that strengthen the grid while facilitating the integration of new renewable energy hubs. This manuscript provides a comprehensive overview, based on the Australian experience, of how power systems are overcoming expected challenges while continuing to integrate secure, low cost, and clean energy.

Early Prediction of Remaining Useful Life for Grid-Scale Battery Energy Storage System

AbstractThe grid-scale battery energy storage system (BESS) plays an important role in improving power system operation performance and promoting renewable energy integration. However, operation sa...

Optimal Cell Utilization for Improved Power Rating and Reliability in a Grid-Scale Three-Phase Battery Energy Storage System Using Hybrid Modular Multilevel Converter Topology Without Redundant Cells

Redundant cells within a battery energy storage system (BESS) are an important aspect to be considered in a BESS planning, design, and operation in order to achieve high reliability. The conventional topology does not have the ability to take advantage of its idle cells, at least one-third of its cells are constantly idling in a typical three-phase BESS. This article presents a new topology for a three-phase grid-scale BESS, where it offers three ways to deal with its idle cells. First, the idle cells were eliminated from the BESS plant while still achieving the desired output power with reduced cost. Second, the idle cells were utilized where no redundant cell is required. Finally, they were utilized to meet the output power required during peak demand. Consequently, the overall construction cost of BESS plant, losses, size, and control complexity are reduced while the reliability is improved. The simulation results indicate that at least 140 out of 333 modules (3996 cells) are in an idle state during the BESS operation, with the three-phase output voltage achieved in both topologies. Using 333 modules, the three-phase output power has increased by 58.8% in the proposed topology (306 kW) compared with the conventional topology (180 kW).

Cycle-Life-Aware Optimal Sizing of Grid-Side Battery Energy Storage

Grid-side electrochemical battery energy storage systems (BESS) have been increasingly deployed as a fast and flexible solution to promoting renewable energy resources penetration. However, high investment cost and revenue risk greatly restrict its grid-scale applications. As one of the key factors that affect investment cost, the cycle life of battery heavily depends on its charging/discharging actions during the operation, particularly in the presence of uncertain renewable generation. In this context, it is necessary to consider the operation-dependent cycle life of batteries in optimal BESS sizing, which imposes great challenges to the modeling and solving of the planning problems. In this paper, we propose a novel two-level optimal sizing model for grid-scale BESS, considering its operation under uncertainties induced by volatile wind generation. In the lower level, a long-term chronological operation simulation of BESS is processed with an accurate cycle life model of batteries; in the upper level, marginal economic utility analysis and BESS size reforming are conducted to approach the optimal size of BESS. An iterative algorithm is designed to solve the model effectively. The proposed method is verified on a modified IEEE RTS-24 system and a real provincial power grid of China.

State-of-Charge Balancing Control for ON/OFF-Line Internal Cells Using Hybrid Modular Multi-Level Converter and Parallel Modular Dual L-Bridge in a Grid-Scale Battery Energy Storage System

Cell state-of-charge (SoC) balancing within a battery energy-storage system (BESS) is the key to optimizing capacity utilization of a BESS. Many cell SoC balancing strategies have been proposed; however, control complexity and slow SoC convergence remain as key issues. This paper presents two strategies to achieve SoC balancing among cells: main balancing strategy (MBS) using a cascaded hybrid modular multi-level converter (CHMMC) and a supplementary balancing strategy (SBS) using a cascaded parallel modular dual L-bridge (CPMDLB). The control and monitoring of individual cells with a reduction in the component count and the losses of BESS are achieved by integrating each individual cell into an L-bridge instead of an H-bridge. The simulation results demonstrate a satisfactory performance of the proposed SoC balancing strategy. In this result, SoC balancing convergence point for the cells/modules is achieved at 1000 min when cell-prioritized MBS-CHMMC works without SBS-CPMDLB and at 216.7 min when CPMBS-CHMMC works together with SBS-CPMDLB and when the duration required reduces by 78.33 %. Similarly, a substantial improvement in SoC balancing convergence point for the cells/modules is achieved when module-prioritized MBS-CHMMC works together with SBS-CPMDLB; the duration needed to reach the SoC balancing convergence point for the cells/modules is achieved after 333.3 and 183.3 min.

Efficiency analysis for a grid-connected battery energy storage system

Efficiency is one of the key characteristics of grid-scale battery energy storage system (BESS) and it determines how much useful energy lost during operation. The University of Manchester has been commissioned with 240 kVA, 180 kWh lithium-ion BESS. This paper investigates round-trip efficiencies, comparing energy extracted from and returned to the grid, of the BESS for different operation modes. This is done by developing simulation switch-level model of power components of the BESS. The simulation is validated against hardware test results and used to identify optimum operation modes, which vary depending on SOC and charging and discharging power rates of the BESS.

The benefits of grid-scale storage on Oahu

The Hawaiian Electric Company intends to procure grid-scale Battery Energy Storage System (“BESS”) capacity. The purpose of this study is to determine whether providing contingency reserve or time-of-day shifting is of more benefit to the Oahu grid, and to better understand the relationship between BESS size and level of benefit. This is an independent study by Sandia, and is not being used to support the regulatory case for BESS capacity by Hawaiian Electric. The study team created a production cost model of the Oahu grid using data primarily from the Hawaiian Electric Company. The proposed BESS supplied contingency reserve in one set of runs and time-of-day shifting in another. Supplying contingency reserve led to larger savings than time-of-day energy shifting. Assuming a renewable reserve and a quick-start reserve, and $15/MMBtu for Low-Sulphur Fuel Oil, the 50-MW/25-MWh, 100-MW/50-MWh, and 150-MW/75-MWh systems supplying contingency reserve provided, respectively, savings of 9.6, 15.6, and 18.3 million USD over system year 2018. Over the range of fuel prices tested, these cost savings were found to be directly proportional to the cost of fuel. As the focus is the operational benefit of BESS capacity, the capacity value of the BESS was not included in benefit calculations.

Very short term load forecasting of a distribution system with high PV penetration

A battery energy storage system (BESS) is an available solution for utilities to deal with intermittency issues resulting from renewable energy resources. A BESS needs to have a control algorithm to provide a very good estimation of the load on the grid at each time step. A short-term load forecast (STLF) is necessary for efficient and optimized control of BESSs that are connected to the grid. In this work, two parallel-series techniques for load forecasting are proposed to optimize the performance of a grid-scale BESS (1 MW, 1.1 kWh) in 15-min steps within a moving 24-h window. In both techniques, a complex-valued neural network (CVNN) is used for parallel forecasting. The parallel component is based on the search for similar days of historical data that have a weekly index comparable to the forecast day. For series forecasting, historical data of each day is used within a moving forecast window by CVNN along with the spline method. For both techniques, parallel forecasting is mixed with series forecasting by an adjustment coefficient. Both techniques are tested on a set of real data for a grid with high PV penetration, and the obtained results are compared.

Stochastic coordinated operation of wind and battery energy storage system considering battery degradation

Grid-scale battery energy storage systems (BESSs) are promising to solve multiple problems for future power systems. Due to the limited lifespan and high cost of BESS, there is a cost-benefit trade-off between battery effort and operational performance. Thus, we develop a battery degradation model to accurately represent the battery degradation and related cost during battery operation and cycling. A linearization method is proposed to transform the developed battery degradation model into the mixed integer linear programming (MILP) optimization problems. The battery degradation model is incorporated with a hybrid deterministic/stochastic look-ahead rolling optimization model of wind-BESS bidding and operation in the real-time electricity market. Simulation results show that the developed battery degradation model is able to effectively help to extend the battery cycle life and make more profits for wind-BESS. Moreover, the proposed rolling look-ahead operational optimization strategy can utilize the updated wind power forecast, thereby also increase the wind-BESS profit.

Cycle and Calendar Aging Study of Lithium-Ion Batteries in the Context of Grid-Scale Energy Storage Systems

The Hawai‘i Natural Energy Institute (HNEI) is leading a team engaged in the research, development, deployment, and analysis of grid-scale battery energy storage systems (BESS) that are designed for system control and power quality support at the generation, transmission, and distribution levels. The program aims to identify high value BESS applications at various system levels, develop control algorithms that maximize the benefit to the grid/customer and the lifetime of the BESS, and evaluate and optimize those algorithms under real world operating conditions. The focus is to deploy, operate, and validate the performance of four grid-scale BESS for various ancillary service applications on grid systems across the state. Large scale battery energy storage systems will become an important part of the electric grid in the near future and it will be essential to ensure their reliability. The objective of this project is to understand the degradation of the individual batteries to anticipate failures. Laboratory testing of advanced Li-ion battery cells is performed to support life-time analysis of technologies targeted for large-scale grid energy storage applications. HNEI’s battery testing efforts have focused on grid scale deployment lithium ion titanate battery technology which is successfully being used for a variety of purposes including frequency and power regulation of large scale wind and solar energy generation. There is currently a lack of understanding of long term performance of battery technology in general, and specifically lithium ion titanate, used under large scale, grid conditions.  This work aims to fill that gap in knowledge through laboratory scale battery testing and the development predictive lifetime models of performance of grid battery technology. Accelerated testing of identical lithium ion titanate battery technology was performed in the laboratory and those results will be used to develop predictive performance models. This model will combine existing modules [1-4] that account for single cell asymmetric degradation, single cell heat generation, string imbalance, and cell paralleling. As real world data is collected from the grid batteries, the predictive models will be compared and assessed for accuracy and ability to predict performance. This work will present preliminary results of the cycle and calendar aging long-term studies. [1] M. Dubarry, N. Vuillaume and B. Y. Liaw, J. Power Sources 186(2), (2009) 500-507. [2] M. Dubarry, C. Truchot and B.Y. Liaw, J. Power Sources 219 (2012) 204-216. [3] https://www.soest.hawaii.edu/HNEI/alawa/[4] M. Dubarry, C. Truchot, A. Devie and B. Y. Liaw, J. Electrochem. Soc 162(6), (2015) A877-A884.

Path Dependence in Lithium-Ion Batteries Degradation - a Comparison of Cycle and Calendar Aging

The Hawai‘i Natural Energy Institute (HNEI) is leading research efforts to understand the degradation of lithium-ion batteries under two distinct projects. The first research project is focused on grid-scale battery energy storage systems (BESS) while the second project is targeting electric vehicles (EVs) and their synergy with the grid. Both applications require a combination of long cycle-life (1000 cycles or more) and long shelf-life (10 to 20 years in operation) to meet the expectations of the customers. To determine whether these durability goals are realistic or not, we performed accelerated testing of different lithium-ion battery technologies in the laboratory. For each technology, we conducted a series of cycle and calendar aging experiments. The results of these studies will be used to develop predictive performance models. The concept of accelerated aging is only valid if the degradation the cell underwent is the same than of the one it experienced in real life. In this presentation, we want to share our preliminary observations regarding the differences between cycle aging and calendar aging across the different chemistries and across the industries (EVs, BESS). Our primary objective is to showcase the different degradation pathways, whether calendar-driven or cycle-driven, which can lead to identical capacity losses. This concept is better known as path dependence and this talk will highlight its implications for the design of long-life battery systems, the laboratory testing it requires and the validity of accelerated testing strategies. [1] M. Dubarry, N. Vuillaume and B. Y. Liaw, J. Power Sources 186(2), (2009) 500-507. [2] M. Dubarry, C. Truchot and B.Y. Liaw, J. Power Sources 219 (2012) 204-216. [3] https://www.soest.hawaii.edu/HNEI/alawa/[4] M. Dubarry, C. Truchot, A. Devie and B. Y. Liaw, J. Electrochem. Soc 162(6), (2015) A877-A884.

Balancing control for grid-scale battery energy storage system

Lithium (Li)-ion cells are becoming increasingly attractive for use in grid-scale battery energy storage systems (BESSs). A key problem with BESSs is the potential for poor utilisation of mismatched cells and reliability issues resulting from the use of large series strings of cells. This paper investigates the close integration of a full-bridge modular multi-level converter and a large number of lithium-ion cells interfacing with an AC electrical grid. The cells are organised in a hierarchical structure consisting of modules, sub-banks, banks and phases. The control strategy includes five levels of balancing: balancing of cells within a module, balancing of modules within a sub-bank, sub-banks within banks, banks within phases and balancing between phases. The system is validated in simulation for a 380 kWh BESS using 2835 lithium-ion cells. Charge balancing is demonstrated for mismatched cells by varying the parameters such as ampere-hour capacity, internal resistance and initial state of charge. A ‘peak sharing’ concept is implemented so that alternative modules assume a portion of the load when certain modules are not capable of meeting the demand. This work is intended to address the challenges of eventual scaling towards a 100 MWh + BESS, which may be composed of 100 000 individual cells.