Utility-scale Energy Storage Systems Research Articles

Utility-scale energy storage system for load management under high penetration of electric vehicles: A marginal capacity value-based sizing approach

To determine a trade-off between the battery energy storage system (BESS) size and corresponding benefits in managing the load of distribution systems under high penetration of electric vehicles (EVs), a marginal capacity value-based sizing approach is proposed in this study. First, the yearly load profiles of EVs are estimated considering different factors, such as EV parameters, driver behavior, day types, and customers at each secondary distribution transformer. Then, a utilization index is proposed to quantify the benefits of increasing the BESS size. To this end, an iterative method is proposed to determine the BESS size with a given utilization target. To expedite the convergence speed, a binary and interpolation search-inspired algorithm is proposed, which can determine the BESS size within a limited number of iterations. The performance of the proposed BESS sizing approach is compared with three other approaches, i.e., optimization-based sizing approach, metaheuristic sizing approach, and enumeration-based sizing approach. The obtained results are tested and validated using the data of a real distribution system. Finally, a sensitivity analysis of different user defined factors such as granularity level in BESS size and utilization target levels is carried out. Simulation results have shown that the proposed method can significantly reduce the BESS size while having minute impact on the peak shaving.

Managing the techno-economic impacts of partial string failure in multistring energy storage systems

The role of energy storage systems (ESSs) is becoming increasingly important for today’s electric power systems. Unavailability of an ESS assigned to critical grid services may cause unwanted disruption of those services and hence, may have a significant techno-economic impact. Like any physical equipment, an ESS is vulnerable to various types of faults. Failure of one or more strings in a multistring ESS does not have to be the cause of shutting down the entire ESS. It can still operate with a partial number of strings and continue providing critical services to the grid, if there are no reliability or safety issues and is acceptable under applicable standards. However, it is important to make sure that the control strategies are adaptable to the changes in ESS capacity caused by failed strings. Also, depending on the previous operation and type of failure, the reallocation of duty cycle burden among available strings could be non-uniform. These complexities suggest that mitigation of the impact of partial failure in multistring ESSs is not trivial and needs careful consideration. This is the topic of this paper. The proposed work investigates the impact of partial failure of a large multistring ESS on the assigned service and develops strategies to adjust the ESS control duty cycles for reducing such impacts. In doing so, the paper proposes a novel two-stage framework that plans for the multistring failure using robust optimization theory and then adjusts in real-time using a rule-based algorithm, based on the real-time information on the power availability of the string. Illustrations provided in this work are based on frequency regulation use-case, which is a common application for many utility-scale ESSs. A 750 kilowatt (kW)/1500 kilowatt-hour (kWh) 3-string ESS is used for the demonstration in this work and the efficacy of the proposed method is demonstrated and compared against methods that do not incorporate string failure in their strategy. In particular, we show that revenue loss of 93% can be incurred when partial string failure is not included in operation and planning. These losses in revenue are reduced by 60% with the proposed method.

Utility-Scale Energy Storage Systems: A Comprehensive Review of Their Applications, Challenges, and Future Directions

Conventional utility grids with power stations generate electricity only when needed, and the power is to be consumed instantly. This paradigm has drawbacks, including delayed demand response, massive energy waste, and weak system controllability and resilience. Energy storage systems (ESSs) are effective tools to solve these problems, and they play an essential role in the development of the smart and green grid. This article discusses ESSs applied in utility grids.

Energy and environmental footprints of flywheels for utility-scale energy storage applications

Flywheel energy storage systems are feasible for short-duration applications, which are crucial for the reliability of an electrical grid with large renewable energy penetration. Flywheel energy storage system use is increasing, which has encouraged research in design improvement, performance optimization, and cost analysis. However, the system's environmental impacts for utility applications have not been widely studied. Evaluating the life cycle environmental performance of a flywheel energy storage system helps to identify the hotspots to make informed decisions in improving its sustainability; to make reasonable comparisons with other energy storage technologies, such as pumped hydro, compressed air, electro-chemical batteries, and thermal; and to formulate environmental policy in the energy sector. In this study, an engineering principles-based model was developed to size the components and to determine the net energy ratio and life cycle greenhouse gas emissions of two configurations of flywheel energy storage: steel rotor flywheel and composite rotor flywheel. The net energy ratio is a ratio of total energy output to the total non-renewable energy input over the life cycle of a system. Steel rotor and composite rotor flywheel energy storage systems were assessed for a capacity of 20 MW for short-duration utility applications. A consistent system boundary was considered for both systems with the life cycle stages of material production, operation, transportation, and end-of-life. Electricity from solar and wind was considered separately in the operation phase. The net energy ratios of the steel rotor and composite rotor flywheel energy storage systems are 2.5–3.5 and 2.7–3.8, respectively. The corresponding life cycle greenhouse gas emissions are 75.2–121.4 kg-CO2eq/MWh and 48.9–95.0 kg-CO2eq/MWh, depending on the electricity source. The net energy ratio and greenhouse gas emissions are highly influenced by the operation phase, which includes charging and standby modes. Uncertainty analysis shows that the life cycle greenhouse gas emissions are most sensitive to the solar, wind, and grid electricity mix emission factors. The results of this study will help to understand the carbon footprints of the various utility-scale energy storage systems.

Stabilising transient disturbances with utility‐scale inverter‐based resources

This paper presents a trajectory tracking control strategy that modulates the active power injected by geographically distributed inverter-based resources to support transient stability. Each resource is independently controlled, and its response drives the local bus voltage angle toward a trajectory that tracks the angle of the center of inertia. The center-of-inertia angle is estimated in real time from wide-area measurements. The main objectives are to stabilize transient disturbances and increase the amount of power that can be safely transferred over key transmission paths without loss of synchronism. Here we envision the actuators as utility-scale energy storage systems; however, equivalent examples could be developed for partially-curtailed photovoltaic generation and/or Type 4 wind turbine generators. The strategy stems from a time-varying linearization of the equations of motion for a synchronous machine. The control action produces synchronizing torque in a special reference frame that accounts for the motion of the center of inertia. This drives the system states toward the desired trajectory and promotes rotor angle stability. For testing we employ a reduced-order dynamic model of the North American Western Interconnection. The results show that this approach improves system reliability and can increase capacity utilization on stability-limited transmission corridors.

Optimal sizing of a utility-scale energy storage system in transmission networks to improve frequency response

The frequency response of a large power system is affected by the penetration of renewable energy sources (RESs), where a utility-scale energy storage system (ESS) can alleviate the problem. This paper presents a strategy for sizing an ESS to improve frequency response of transmission networks. The location of the ESS in the transmission network is determined through a sensitivity analysis targeting minimum line loading around a bus. The ESS sizing strategy considers the minimization of frequency deviation as well as rate of change of frequency (ROCOF) after generator or load tripping events. The tuning of PQ controller parameters of the ESS (active power part) is also performed for frequency response improvement. The proposed approach is tested in a modified IEEE-39 bus power system considering a variety of scenarios where RESs are integrated as four different schemes for peak and off-peak load conditions. DIgSILENT PowerFactory is used for developing, testing, and analyzing the system models. A fitness-scaled chaotic artificial bee colony (FSCABC) optimization algorithm (a hybrid meta-heuristic approach) is used for optimization through a Python script automating simulation events in PowerFactory. The results obtained from the FSCABC approach are verified through the application of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS sizing technique including ESS controller tuning can successfully improve the frequency response of a transmission network.

Parameter Identification for Cells, Modules, Racks, and Battery for Utility-Scale Energy Storage Systems

The equivalent circuit model for utility-scale battery energy storage systems (BESS) is beneficial for multiple applications including performance evaluation, safety assessments, and the development of accurate models for simulation studies. This paper evaluates and compares the performance of utility-scale equivalent circuit models developed at multiple sub-component levels, i.e. at the rack, module, and cell levels. This type of modeling is used to demonstrate that the equivalent circuit model for a reference cell, module, or rack of a BESS can be scaled to represent the entire battery system provided that the battery management system (BMS) is active and functional. Contrary to the rapid pulse discharge cycles employed in conventional cell parameter estimation approaches, the study proposes a new charge/discharge cycle for identifying the equivalent circuit parameters for utility-scale battery systems using equipment readily available at installation sites without the need for laboratory setups. Furthermore, a sensitivity analysis for classifying and quantifying the effect of each equivalent circuit parameter on the performance of the proposed battery system model was executed. The measurements and simulations are conducted for a 1MW/2MWh BESS testing facility located at the Louisville Gas and Electric and Kentucky Utilities (LG&E and KU) E.W. Brown generating plant. The results indicate that for the example utility-scale battery setup with an active BMS, the equivalent circuit model of either the cell, module, or rack can be scaled to represent the battery system with less than 1% average voltage error.

The economic feasibility of solar and storage system in Illinois

To help understand the economic feasibility of installing solar and energy storage in Illinois, we conducted a case study to examine the viability of multiple options of (1) installing utility-scale storage at the Waukegan plant site and surrounding area, and (2) investing in behind-the-meter storage combined with solar and energy efficiency on the residential and commercial buildings. To analyze the economics of the utility-scale storage system, we quantified the net present cost of installing the system, the reliability and transmission benefits, and the increase in capacity revenue. For the customer-owned systems, we estimated the cost of investing in the solar-storage hybrid systems, the electricity bill savings, and the payback periods of three different building types. We found that the financial benefits of solar plus storage, accompanied by load reduction by energy efficiency would exceed the costs in most cases. Assuming a 16 MW four-hour duration lithium-ion battery, the initial capital cost of installing a utility-scale energy storage system would be $14.3 million. Over the 25-year project lifetime, financial benefits total $19.1 million including $6.9 million of avoided transmission costs and $12.1 million of capacity revenue. In addition, investing in solar could significantly lower consumer electricity bills. Most homes and businesses in the area could cut their electricity bills by more than half by investing in solar energy. When energy efficiency and solar energy are combined, a household in the area could save 66 percent annually on its electricity bill. Stronger climate policies and expanded use of time-varying electricity rates could further improve the economics of solar plus storage systems.

Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm

The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) distributed generation, for two scenarios: (1) with a uniform ESS size and (2) with non-uniform ESS sizes. System models for the proposed implementations are developed, analyzed, and tested using DIgSILENT PowerFactory. The artificial bee colony optimization approach is employed to optimize the objective function parameters through a Python script automating simulation events in PowerFactory. The optimization results, obtained from the artificial bee colony approach, are also compared with the use of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS placement approach can successfully achieve the objectives of voltage profile improvement, line loading minimization, and power loss reduction, and thereby significantly improve distribution network performance.

Optimal Asset Expansion in Distribution Networks Considering Battery Nonlinear Characteristics Expansion optimale des actifs dans les réseaux de distribution en tenant compte des caractéristiques non linéaires des batteries

Asset expansion planning in distribution systems is vital and should be extended to consider utility-scale energy storage systems such as batteries. Unlike other assets, usage parameters such as number of storage cycles and depth of discharge (DOD) have a dramatic nonlinear effect on the lifetime of battery energy storage systems (BESSs). Hence, it is imperative to include the relationship between lifetime, number of storage cycles, and DOD of BESS in the optimal asset planning formulation. This paper presents a new formulation and solution for the optimization problem of asset expansion planning in power distribution systems. The research considers adding new BESS units to existing distribution grids. The nonlinear life-cycling-usage relationship of BESS has been modeled for the first time in the context of asset expansion planning in power systems. The formulation aims at minimizing the annualized cost of the expansion plan while satisfying forecasted demand and other distribution system requirements. The methodology is used to optimally plan for the expansion of 6-bus and 33-bus distribution networks. The results show the effect of considering the life-cycling-usage relationship of BESS on optimal asset expansion plans including the optimal size and capacity of the assets. In addition, the impact of the ratio of off-peak load to peak load on total asset cost is analyzed and reported. It is shown that an annual cost saving of 51.79% is possible via the proposed approach. Findings of this paper will capture the attention of planning and asset management departments of electric distribution utilities.

Pumped thermal energy storage and bottoming system part A: Concept and model

This work introduces a new concept for a utility scale combined energy storage and generation system. The proposed design utilizes a pumped thermal energy storage (PTES) system, which also utilizes waste heat leaving a natural gas peaker plant. This system creates a low cost utility-scale energy storage system by leveraging this dual functionality. This Part A of a two-part paper presents a review of previous work in PTES as well as the details of the proposed integrated bottoming and energy storage system. A time-domain system model was developed in Mathworks R2016a Simscape and Simulink software to analyze this system. Validation of both the fluid state model and the thermal energy storage model are provided. The experimental results showed the average error in cumulative fluid energy between simulation and measurement was ±0.3% per hour. Comparison to a Finite Element Analysis (FEA) model showed <1% error for bottoming mode heat transfer. Part B of this two-part paper gives a detailed characterization of the integrated bottoming with energy storage system.

Life Cycle Cost Analysis for utility-scale Energy Storage systems

This paper examines the existing literature in life cycle cost analysis of large scale electricity storage systems, providing an overview of their technical benefits and drawbacks as well as the cost associated with their expected lifespan. The energy storage systems that are being evaluated are Lead-Acid batteries, Nickel-Cadmium batteries, Sodium-Sulfur batteries, Compressed Air energy storage, and Pumped Hydro plants. These systems are suitable for grid support, and are considered of great importance for the grid of the future. Life cycle cost analysis is an eective way of inter- preting and comparing those systems. Both the technical and cost characteristics that are presented in the paper are key findings critical for understanding the applicability and challenges associated with each system. These metrics should be used to properly evaluate the most cost eective option among the systems in a holistic approach, as the power industry moves towards a greener future.

A temporal assessment of vehicle use patterns and their impact on the provision of vehicle-to-grid services

With the emerging nationwide availability of battery electric vehicles (BEVs) at prices attainable for many consumers, electric utilities, system operators and researchers have been investigating the impact of this new source of energy demand. The presence of BEVs on the electric grid might offer benefits equivalent to dedicated utility-scale energy storage systems by leveraging vehicles’ grid-connected energy storage through vehicle-to-grid (V2G) enabled infrastructure. It is, however, unclear whether BEVs will be available to provide needed grid services when those services are in highest demand. In this work, a set of GPS vehicle travel data from the Puget Sound Regional Council (PSRC) is analyzed to assess temporal patterns in vehicle use. These results show that vehicle use does not vary significantly across months, but differs noticeably between weekdays and weekends, such that averaging the data together could lead to erroneous V2G modeling results. Combination of these trends with wind generation and electricity demand data from the Electric Reliability Council of Texas (ERCOT) indicates that BEV availability does not align well with electricity demand and wind generation during the summer months, limiting the quantity of ancillary services that could be provided with V2G. Vehicle availability aligns best between the hours of 9 pm and 8 am during cooler months of the year, when electricity demand is bimodal and brackets the hours of highest vehicle use.

Improved Accounting of Emissions from Utility Energy Storage System Operation

Several proposed utility-scale energy storage systems in the U.S. will use the spare output capacity of existing electric power systems to create the equivalent of new load-following plants that can rapidly respond to fluctuations in electricity demand and increase the flexibility of baseload generators. New energy storage systems using additional generation from existing plants can directly compete with new traditional sources of load-following and peaking electricity, yet this application of energy storage is not required to meet many of the Clean Air Act standards required of new electricity generators (e.g., coal- or gas-fired power plants). This study evaluates the total emissions that will likely result from the operation of a new energy storage facility when coupled with an average existing U.S. coal-fired power plant and estimates that the emission rates of SO2 and NOx will be considerably higher than the rate of a new plant meeting Clean Air Act standards, even accounting for the efficiency benefits of energy storage. This study suggests that improved emissions "accounting" might be necessary to provide accurate environmental comparisons between energy storage and more traditional sources of electricity generation.

Life cycle energy requirements and greenhouse gas emissions from large scale energy storage systems

Abstract Using life cycle assessment, metrics for calculation of the input energy requirements and greenhouse gas emissions from utility scale energy storage systems have been developed and applied to three storage technologies: pumped hydro storage (PHS), compressed air energy storage (CAES) and advanced battery energy storage (BES) using vanadium and sodium polysulphide electrolytes. In general, the use of energy storage with electricity generation increases the input energy required to produce electricity, as well as the total greenhouse gas emissions. Despite this increase, the life cycle GHG emission rate from storage systems when coupled with nuclear or renewable sources is substantially lower than from fossil fuel derived electricity sources. GHG emissions from PHS when coupled with nuclear and renewable energy systems are lower than those from BES or CAES. When coupled with fossil generation, CAES has significantly lower net GHG emissions than PHS or BES.