Large-scale Battery Energy Storage System Research Articles

Design of hundred mw level shared BESSs and “Clean Energy + Energy Storage” joint operation mode

Abstract This paper presents the background of the construction of the Fujian Xiapu shared energy storage power station project. It also establishes the structure of the dispatching energy management system (EMS) for a large-scale Battery Energy Storage System (BESS) based on the energy storage station’s topology. The design and implementation method of the monitoring module for the energy storage power station is introduced, along with the proposition of the joint operation mode of “clean energy + energy storage”. Additionally, the technical requirements and feasibility of this mode are discussed. The shared energy storage operation mode can effectively enhance the energy conversion efficiency of the battery system while significantly reducing costs.

Noise control tactics to balance the demand for sustainable energy storage, community tranquility, and environmental regulatory compliance

As the construction of large-scale Battery Energy Storage System (BESS) facilities increases in California, their impact on urban sprawl is also becoming more pronounced. Projects involving BESS arrangements increasingly find themselves within or near residential land uses in California, providing greater challenges for noise control and abatement to comply with state and local operational noise thresholds. This paper presents case studies of what Dudek has found to be the most efficient noise control tactics related to lowering the noise emission of BESS facilities, particularly through the implementation of onsite noise walls, direct noise attenuation applied to BESS equipment (i.e., noise attenuation for battery thermal management systems involving the operation of ventilation fans and refrigeration system components), and modified BESS equipment arrangements. These strategies are essential for ensuring that BESS projects are not only compliant with environmental standards but also socially acceptable within residential communities. By presenting practical and efficient noise mitigation techniques, this paper aims to guide planners and developers in the sustainable development of BESS facilities, balancing the demand for energy storage with the preservation of community tranquility and compliance with regulatory noise limits.

INTEGRATION OF GRID SCALE BATTERY ENERGY STORAGE SYSTEMS AND APPLICATION SCENARIOS

Integration of renewable energy sources (RESs) into the grid has profoundly gained a lot of attention in the energy domain, coupled with an ever-changing generation profile and dependency on weather conditions, RESs are commonly known to pose security of supply challenges and in case they are not monitored they can cause techno-economic losses and even lead to catastrophic failure of the electrical grids. However, their availability and negligible generation cost make them environmentally friendly when compared to conventional energy sources. For seamless connection of renewables to the grid network, battery energy storage system (BESS) has been suggested in literature, the technology has come to the fore recently, and has found application cases in the utility grid with enhanced functions to participate in both reserve and wholesale electricity markets such as day-ahead and intra-day markets. This technical brief presents various energy storage systems (ESSs) potentially used in large-scale grid networks, which are investigated, and their individual properties are compared, where necessary application areas with examples enabled by constituting material properties are outlined, in the same context their general advantages and disadvantages are given in reference to the specific application cases. In addition, the application of large-scale BESS is explained together with the integration solutions such as use of Virtual Power Plant (VPP) and microgrid.

Improved rule-based power distribution algorithm for hybrid battery storage systems and real-world validation

Large-scale battery energy storage systems (BESS) can serve many applications and are already widely used for grid services. The rapidly growing BESS market and the recent interest in their deployment accentuate the need for safe, reliable, and highly available energy management systems (EMS) for automated control. However, the EMS and their integrated power distribution algorithms (PDA) can still be optimized to adapt various characteristics of the BESS. This study investigates a new version of a PDA with a particular focus on battery aging and system efficiency. The rule-based PDA has been validated on a 6 MW/7.5 MWh BESS system with five battery technologies providing frequency containment reserve to the German power grid. The results underline the PDA's capability to exploit the individual strengths of each battery technology. The PDA sets objectives for the state of charge, energy throughput, and power of the batteries to extend battery life. The distribution of energy throughputs among batteries can be selected in advance through the new implementation of the PDA. At the same time, the inverters are significantly less often activated and used in the optimal efficiency range, increasing the overall system efficiency to approximately 82 %. The optimized switching behavior leads to less frequent power switching between individual battery units and longer phases with more constant power. In addition, the operational efficiency of BESS can be improved by the choice of battery technology and the overall system layout on the hardware side. The improvements on the software side are only possible by increasing the overall power requests through multi-use operation by about 6 % compared to our benchmark test. The results can be used by BESS operators to increase operational profits due to longer battery life and fewer efficiency losses.

Lithium-Ion Batteries on Board: A Review on Their Integration for Enabling the Energy Transition in Shipping Industry

The emission reductions mandated by International Maritime Regulations present an opportunity to implement full electric and hybrid vessels using large-scale battery energy storage systems (BESSs). lithium-ionion batteries (LIB), due to their high power and specific energy, which allows for scalability and adaptability to large transportation systems, are currently the most widely used electrochemical storage system. Hence, BESSs are the focus of this review proposing a comprehensive discussion on the commercial LIB chemistries that are currently available for marine applications and their potential role in ship services. This work outlines key elements that are necessary for designing a BESS for ships, including an overview of the regulatory framework for large-scale onboard LIB installations. The basic technical information about system integration has been summarized from various research projects, white papers, and test cases mentioned in available studies. The aim is to provide state-of-the-art information about the installation of BESSs on ships, in accordance with the latest applicable rules for ships. The goal of this study is to facilitate and promote the widespread use of batteries in the marine industry.

Large-Scale BESS for Damping Frequency Oscillations of Power Systems with High Wind Power Penetration

With the high penetration of renewable energy into power grids, frequency stability and oscillation have become big concerns due to the reduced system inertia. The application of the Battery Energy Storage System (BESS) is considered one of the options to deal with frequency stability and oscillation. This paper presents a strategy to size, locate, and operate the BESS within the power grid and, therefore, investigate how sizing capacity is related to renewable energy penetration levels. This paper proposes an identification method to determine the best location of the BESS using the Prony method based on system oscillation analysis, which is easy to implement based on measurements while actual physical system models are not required. The proposed methods for BESS size and location are applied using MATLAB/Simulink simulation software (version: R2023a) on the Kundur 2-area 11-bus test system with different renewable energy penetration levels, and the effectiveness of the applied method in enhancing frequency stability is illustrated in the study cases. The case studies showed a significant improvement in steady-state frequency deviation, frequency nadir, and Rate of Change of Frequency (ROCOF) after implementing BESS at the selected bus. The integration of BESS can help to avoid Under-frequency Load Shedding (UFLS) by proper selections of size, location, and operating strategy of the BESS within the power grid.

An adaptive charge control strategy for participation of neighbourhood battery energy storage systems in frequency stability

Neighbourhood Battery Energy Storage System (N-BESS) is a new scale of energy storage that is expected to have a potential role in modern power systems stability. In the literature, there is a lack of studies that proposed a smart engagement of N-BESS in the frequency stability. In this paper, an adaptive charge control strategy for the N-BESS has been proposed to enhance the frequency stability while maintaining a fair State-of-Charge (SOC) levels for N-BESS. Also, a collaborative framework for large-scale Battery Energy Storage System (L-BESS) with N-BESS has been introduced, in which the N-BESS play an auxiliary role in frequency stability. In this study, a number of system uncertainties, including N-BESS SOC, load consumption, wind farm generation, and contingency size and location, have been considered. The simulation has been carried out in the Simplified 14-Generator Model of the South East Australian Power System over one-year simulation using DIgSILENT/PowerFactory software and Python interface. The results have demonstrated that a higher SOC levels of N-BESS under the proposed strategy have been maintained compared to that of the conventional strategy. Moreover, when the L-BESS collaborated with the N-BESS under the proposed framework, the best frequency stability with highest SOC levels of N-BESS have been obtained; at the same time less discharged power by the L-BESS was noted compared to that when the L-BESS participated individually which indicated that a smaller L-BESS size would be required if it collaborated with N-BESS in frequency stability service.

A resilience enhanced hierarchical strategy of battery energy storage for frequency regulation

Battery energy storage system (BESS) has been regarded as an effective technology to regulate system frequency for power systems. However, the cost and the system security of battery energy storage are the bottle necks for the battery energy storage system to be applied to practical projects for frequency regulation. Comparing with the large-scale battery energy storage system, the small-scale energy storage system has better robustness and could reduce the cost and improve the system security with lower energy capacity and wider regional distribution. However, coordinating the state of charge (SOC) of a large number of small-scale battery storage system to provide effective frequency regulation service is a challenge for the operation of power systems. In this paper, a hierarchical energy management strategy, which can be applied to different scenarios with and without limited communication systems, has been proposed to coordinate a large number of small-scale energy storage systems to regulate frequency for power systems. The rated power capacity, energy capacity, and SOC of the BESS are considered in the proposed strategy to maximize the capability of frequency regulation for power systems. The proposed strategy can be applied to power systems without powerful and expensive communication systems and coordinate BESS according to SOC of the BESS and the quality of communication system. The resilience of power systems after extreme natural events can be enhanced by the frequency regulation service of BESS under proposed strategy.

IANOS: Innovative energy storage solutions for the decarbonization of geographical islands

Geographical Islands experience harsh climate conditions resulting in diminished reliability of their grid. IANOS, a project funded by the European Commission, is developing technologies to overcome these challenges and allow for the secure decarbonisation of islands. The project will deploy and use storage technologies in two islands: Terceira, in Portugal, and Ameland, in the Netherlands. These include a 100kW/3kWh flywheel; thirty-five 2kW private fuel cells; sixteen 3kW/3kWh electrochemical batteries; two large-scale Battery Energy Storage System (BESS); a biobased saline battery of 120kWh; and twenty-four heat batteries of 3.5kWhth. These technologies, managed by an intelligent Virtual Power Plant (iVPP) also developed within the project, will be used for the maximisation of demand-side self-consumption, as well as for the provision of ancillary services, targeting the maximum economic and environmental benefit for the population and the island’s grid. In this paper, the specifications of each storage technology are described, as well as the impacts on the grid stability. The role of storage technologies in the decarbonisation of geographical islands will be emphasized.

Review of machine learning method for safety management of lithium-ion battery energy storage

With the broad implementation of electrochemical energy storage technology, the noteworthy issue of ensuring safe operation and maintenance of battery energy storage power plants has become more and more prominent. The conventional battery management system solely acquires data on the voltage, current, and temperature of individual battery cells. Constrained by hardware processing capabilities, limitations in data transmission bandwidth, and latency issues, effectively monitoring the health and safety of large-scale battery energy storage systems has become a critical technological challenge. The implementation of machine learning techniques in predicting the operating conditions of lithium-ion batteries has provided opportunities for enhancing the safety management of energy storage systems. To address the safety management requirements of lithium-ion batteries, this paper firstly introduces research related to the risk mechanism of abusive use and thermal runaway of such batteries. Next, the architecture and application characteristics of the lithium-ion battery management system will be discussed. The implementation of machine learning techniques for analyzing the health and safety status of lithium-ion batteries is extensively discussed. Finally, a safety assessment of lithium-ion batteries for energy storage power stations is anticipated.

Research on the Frequency Regulation Strategy of Large-Scale Battery Energy Storage in the Power Grid System

Driven by the carbon peaking and carbon neutrality target, the large-scale grid-connected of renewable energy such as wind and solar has increased, and the volatility and randomness have posed new challenges to the stability of the power grid frequency. In this case, battery energy storage is a grid auxiliary resource with fast response and adjustable parameters, which can provide frequency support for the grid system in a short period. This paper studies the frequency regulation strategy of large-scale battery energy storage in the power grid system from the perspectives of battery energy storage, battery energy storage station, and battery energy storage system, respectively. First of all, the droop control based on logistic function and the virtual inertia control based on piecewise function are proposed for battery energy storage frequency regulation, which improves the performance of battery energy storage power output effectively. Second, the weighting factor is set according to the current battery charge to achieve the most optimal distribution of frequency regulation power for each battery pack in the battery energy storage station. In the end, a control framework for large-scale battery energy storage systems jointly with thermal power units to participate in system frequency regulation is constructed, and the proposed frequency regulation strategy is studied and analyzed in the EPRI-36 node model. The results of the study show that the proposed battery frequency regulation control strategies can quickly respond to system frequency changes at the beginning of grid system frequency fluctuations, which improves the stability of the new power system frequency including battery energy storage. In addition, this paper also provides a certain reference for the construction of the new power system dispatching that integrates “Generation-Grid-Load-Storage” in the future.

Potential analysis of current battery storage systems for providing fast grid services like synthetic inertia – Case study on a 6 MW system

Large-scale battery energy storage systems (BESS) already play a major role in ancillary service markets worldwide. Batteries are especially suitable for fast response times and thus focus on applications with relatively short reaction times. While existing markets mostly require reaction times of a couple of seconds, this will most likely change in the future. During the energy transition, many conventional power plants will fade out of the energy system. Thereby, the amount of rotating masses connected to the power grid will decrease, which means removing a component with quasi-instantaneous power supply to balance out frequency deviations the millisecond they occur. In general, batteries are capable of providing power just as fast but the real-world overall system response time of current BESS for future grid services has only little been studied so far. Thus, the response time of individual components such as the inverter and the interaction of the inverter and control components in the context of a BESS are not yet known. We address this issue by measurements of a 6 MW BESS's inverters for mode changes, inverter power gradients and measurements of the runtime of signals of the control system. The measurements have shown that in the analyzed BESS response times of 175 ms to 325 ms without the measurement feedback loop and 450 ms to 715 ms for the round trip with feedback measurements are possible with hardware that is about five years old. The results prove that even this older components can exceed the requirements from current standards. For even faster future grid services like synthetic inertia, hardware upgrades at the measurement device and the inverters may be necessary.

Establishment of Performance Metrics for Batteries in Large‐Scale Energy Storage Systems from Perspective of Technique, Economics, Environment, and Safety

The battery is the core of large‐scale battery energy storage systems (LBESS). It is important to develop high‐performance batteries that can meet the requirements of LBESS for different application scenarios. However, large gaps exist between studies and practical applications because there are no uniform metrics for evaluating the performance of batteries. Herein, based on the fundamental requirements of LBESS, this perspective establishes the performance metrics of batteries for scenarios of load leveling, frequency regulation, and reserve application, respectively. Performance metrics include the technical metrics (e.g., the energy density, cycling performance, rate performance), economic metrics (levelized cost of energy), environmental metrics (sustainability of the material, recyclability of batteries, etc.), and safety metrics. The relationship between the proposed metrics and the application of the LBESS are discussed to guide the future studies.

Enhancing static voltage stability of a power system in the presence of large-scale PV plants using a battery energy storage control scheme by the probabilistic technique

This paper aims to investigate the impact of large-scale photovoltaic plant (LS-PVP) controllers on the voltage stability (VS) of a power system. Besides, a new control strategy is proposed for the large-scale battery energy storage system (LS-BESS) to enhance a power system integrated with LS-PVPs, especially VS. To this end, a probabilistic technique, based on the stochastic nature of LS-PVPs and loads, is employed to accurately evaluate the impact of LS-PVPs on the system. Next, a new coupling between the optimization algorithm and the probabilistic technique is proposed to determine the optimal number, location, and capacity of the LS-BESSs by the probabilistic particle swarm optimization (PPSO) algorithm. The objective function is then used to simultaneously maximize the total VS and minimize the total power losses, line loading, as well as investment costs of LS-BESSs. Furthermore, technical performance indices (TPIs) are used for a more comprehensive investigation to compare the proposed solution to the synchronous generators. Finally, several disturbances occurring in the Nordic system are used to validate the effectiveness of the proposed approach, using the Monte Carlo simulation (MCS) method. According to the results, when a fault occurs, a system integrated with LS-PVPs in the stressed area does not operate better than synchronous generators. Therefore, an advanced control method is required to reduce undesirable effects of LS-PVPs. Using the proposed solution, voltage instability was prevented, LS-BESS investment costs were minimized, and negative effects of LS-PVPs on the system were reduced. Besides, costs required for expanding the transmission network as well as communication between controllers and reactive power compensation devices were reduced.

A simple and effective methodology for sizing electrical energy storage (EES) systems based on energy balance

The use of the electrical energy storage (EES) plays an important role in the transition of energy generation towards renewable energy sources (RESs). An effective sizing of EES systems is very important in order to cope with the volatility of RESs and to ensure a reliable energy supply. The present paper provides a methodology which helps to determine the minimum required EES size for conceiving a fully standalone system. Its approach is based on the evaluation of the energy balance for a given design period, and it can also be applied for sizing the EES system in grid-connected applications. The methodology was validated using measurement data obtained from two different systems corresponding to: a) a near-zero energy building with local generation sources, and b) a large-scale battery energy storage system (BESS) installed in a factory and used for peak-shaving. The obtained results confirmed the effectiveness of the proposed methodology by estimating the required size of the EES system. A good correlation was found between the estimated and the installed BESS size in the considered systems. The deviation between real and estimated BESS capacities was found to be less than 5%.

Reliability Assessment of Renewable Power Systems Considering Thermally-Induced Incidents of Large-Scale Battery Energy Storage

The battery energy storage system (BESS) has been envisaged as an effective solution for renewable energy accommodation in power systems. However, the residual capacity and maximum power of large-scale BESS are highly affected by thermally-induced incidents such as battery degradation and Thermal Runaway (TR) propagation. In the prior-art studies, the impacts of thermally-induced incidents on the BESS service performance have not been well modeled, resulting in relatively over-optimistic reliability estimation of power systems. In this paper, the reliability of large-scale grid-connected BESSs as well as its impacts on the overall reliability of power systems are investigated considering the battery degradation and TR propagation. To quantify the time-varying performance of the BESS, a multi-state model is constructed. The proposed model describes the aging process of batteries inside the BESS, incorporating the combined effects of sequential TR and the performance degradation of the surrounding batteries due to heat absorption. Based on the Monte Carlo method, scenarios that reflect the uncertainties of the intermittent wind generation and fluctuating loads are simulated. An optimal scheduling model is deployed, and a solution algorithm is proposed to calculate the scheduling results of the BESS in the real-time performance range subject to its thermal conditions. Case studies are conducted to validate the effectiveness of the proposed model and technique.

A business-oriented approach for battery energy storage placement in power systems

Battery energy storage systems (BESSs) are gaining increasing importance in the low carbon transformation of power systems. Their deployment in the power grid, however, is currently challenged by the economic viability of BESS projects. To drive the growth of the BESS industry, private, commercial, and institutional investments in large-scale BESS projects are needed. For financiers and investors, choosing an appropriate BESS installation location is a crucial task that requires important considerations. However, so far, studies targeting the BESS placement problem have mainly focused on minimizing operational losses, solving power quality issues, and improving the voltage profile of the system. Implementing such approaches only considers the operational feasibility of BESS at the installation site while ignoring its business feasibility. Therefore, in this paper, we approach the BESS placement problem from a business viewpoint by conducting a stage-level investigation of BESS projects. First, we identify the factors impacting the business feasibility of placement decisions in projects’ construction, connection, operation, and disposal stages and propose cost and time effective measures for making them business friendly. We investigate several factors such as profitability of grid services, integrability of renewable resources, affordability of connection charges, and the usability of BESS capacity. Second, we investigate the business potential of placing BESSs in different grid-levels of the power system and examine BESS connection procedures at those levels. Third, we implement the proposed approach for installing a BESS in the Danish island of Bornholm, for which, we investigate multiple locations of the Bornholm power system.

Enhancing long-term voltage stability of a power system integrated with large-scale photovoltaic plants using a battery energy storage control scheme

Due to distinct differences in dynamic characteristics of large-scale photovoltaic plants (LS-PVPs) compared to conventional generation units, utilities face some new non-traditional operational problems, more specifically in terms of voltage stability. This paper analyzes the impact of various control methods of LS-PVPs on long-term (LT) voltage stability. A new corrective voltage control (CVC) scheme is proposed for the large-scale battery energy storage system (LS-BESS) to prevent LT voltage instability in a power system integrated with LS-PVPs. For this purpose, a new coupling between optimization and dynamic simulations is proposed to treat the problem as an objective function, which uses the particle swarm optimization (PSO) algorithm. This objective function is used to minimize investment costs and voltage drops of the system by determining the optimal number, location, and capacity of LS-BESSs. Furthermore, the effects of local voltage control modes and power priority settings of LS-BESSs are investigated. Besides, effectiveness of the proposed approach is validated through several scenarios using time-domain simulations of a more realistic system, namely the Nordic system. According to the results, upon using the proposed approach, negative effects of LS-PVPs on voltage stability and costs required for expanding and reinforcing the transmission network decreased. In addition, voltage collapse was prevented, investment costs of LS-BESSs were minimized, and costs required for reactive power compensation devices and communication between controllers decreased.

Practical state estimation using Kalman filter methods for large-scale battery systems

The system states of battery energy storage systems (BESSs) such as state of charge (SOC) and state of health (SOH) are essential for the functions of the system, such as frequency support services and energy trading. However, the complexity of a large-scale battery system makes the estimations more difficult than at the cell-level. This is further compounded by real-world limitations on system monitoring data granularity, accuracy and quality. In this paper it is shown how cell-level state estimation techniques can be utilised on large-scale BESSs using experimental data from a 2MW, 1MWh BESS. The results show how a Dual Sigma point Kalman Filter (DSPKF) SOC estimation provides more accurate results compared to the commercial BESS battery management system SOC. It is shown how the DSPKF parameters can be tuned by a genetic algorithm to simplify selection and generalise the approach for different BESSs. Furthermore, it shows how this method of SOC estimation can be combined with a total least-squares (TLS) method for capacity estimation to less than 1% error. Online system state estimation is demonstrated using both designed tests and real-world operational profiles where the BESS has provided contracted frequency response services to the national electricity grid in the UK.

Operational strategy optimisation of VRB energy storage systems considering the dynamic characteristics of VRB in active distribution networks

Strategy optimisation of large-scale battery energy storage system (BESS) operation in active distribution networks (ADNs) is an actively pursued research topic concerned by electric power researchers. This study proposes a dynamic programming method (DPM)-based operational strategy optimisation of vanadium redox flow battery (VRB) ESSs for the comprehensive performance of ADNs considering the dynamic characteristics of VRB. The dynamic characteristics of VRB based on self-discharge rate, dynamic efficiencies, maximum absorption power, cycle life and apparent power are reasonably proposed to construct the operational restrictions of ESSs. VRB is safely and reasonably operated with high cycle life and ideal states by these dynamic operational restrictions. And then, DPM is used to decompose the multivariate optimisation problem into several univariate optimisation problems. Finally, different case studies showed that the developed operation strategy of VRB ESSs can greatly improve both the economy and the voltage quality of ADNs. Also, the curtailment rate of renewable energy in ADNs is greatly reduced by about 50% and VRB ESSs can get a perfect optimisation associated with a higher utilisation rate of about 0.8 and an ameliorative average efficiency of about 0.753.