Battery Energy Storage Technology Research Articles

Hydrogen Technology and Decarbonization [From the Editor

In power grids worldwide, penetrations of renewable energy sources, e.g., wind and solar, are increasing at a dazzling speed. High penetrations introduce many new operational challenges since solar and wind are intermittent. Battery energy storage becomes a necessity. In the two most recent issues, <i>IEEE Electrification Magazine</i> has focused on battery energy storage technology at scale (December 2021) and grid-forming inverter technology for battery energy systems and renewable energy sources (March 2022). On the other hand, as stated by the former U.S. Department of Energy secretary, Ernest Moniz, net-zero emissions call for a supercharged decade of energy innovation in electricity generation, transportation, the heating of buildings, and so forth. All kinds of low-carbon tools and technologies are to be explored, not just solar, wind, and batteries.

A stochastic techno-economic comparison of generation-integrated long duration flywheel, lithium-ion battery, and lead-acid battery energy storage technologies for isolated microgrid applications

Different energy storage technologies can be potentially integrated into microgrids to support variable renewable energy generators. Long-duration flywheel energy storage is considered a new contender in the energy storage market. This energy storage technology has been previously evaluated in a techno-economic study, but it did not consider uncertainties in the model input data. In this work, stochastic techno-economic comparison is performed using microgrid modeling and Monte-Carlo methods to compare long-duration flywheels, lithium-ion batteries, and lead-acid batteries for isolated microgrid and industrial facility. Results generally show a relatively high probability for long-duration flywheels to yield a lower leveized cost of storage (LCOS) and levelized cost of electricity (LCOE) compared to lithium-ion batteries in 2020. Higher probability can be attained when the overnight component cost of long-duration flywheels is reduced or when overnight diesel prices are high. However, the chances of long-duration flywheels yielding lower LCOS and LCOE rapidly decreases as time progresses. Long-duration flywheel manufacturers and promoters must find ways to accelerate price reduction by 2.5× from baseline to secure a better chance of yielding a lower LCOS in 2050.

Multi-service based economic valuation of grid-connected battery energy storage systems

Grid-scale Battery Energy Storage (BES) technologies are advocated as key enablers for low-carbon pathways. High capital costs and limited revenue from capacity utilization for a specific service leave most of the storage assets under high investment risks. Economic viability of BES can be justified from their participation in multiple services. Most of the existing works on value stacking and economic viability assessment are limited to considering energy arbitrage, peak shaving, and frequency regulation. Non-consideration of other potential grid services like load following and ramp products results in inadequate economic feasibility assessment of storage projects. In this context, the paper attempts to analyze economic feasibility from stacked revenues of an optimally sized BES. Various combinations of six grid services - energy arbitrage, regulation, reserve, load following, peak shaving, and ramp products; are modeled to assess optimal portfolio of services for BES value stacking and economic viability. BES and conventional units are co-optimized for various services in hourly resolution and inter-day rolling horizon for a year using security-constrained scheduling framework. Economic analysis of BES is carried out using cash flows for various service combinations. Case studies conducted on IEEE RTS 24 and Great Britain test systems highlight that BES, with stacked services, can gain 80%–120% of the sum of individual revenues. BES investments are found to be economically viable with value stacking from 04 to 05 services.

COMPARATIVE ANALYSIS OF BATTERY STORAGE TECHNOLOGIES FOR RESIDENTIAL PHOTOVOLTAIC SOLAR ENERGY INSTALLATIONS

The study concerns a comparative analysis of battery storage technologies used for photovoltaic solar energy installations used in residential applications. Battery storage is needed because of the intermittent nature of photovoltaic solar energy generation and also because of the need to store up excess energy generated in periods of high demand or for sales to the National Grid System. The study consists of three parts; namely: (a) to undertake a comprehensive review of current battery storage technologies. (b) To investigate the performance of the main battery storage technologies that is commercially available (efficiency, energy density, power density, self-discharge per day and power rating); (c). Undertake comparison of battery energy storage technologies. From the findings, it shows that the Lithium Ion Battery technology is the most reliable and most widely used technology for residential applications. It has the best performance characteristics (efficiency, energy density, power density, moderate self-discharge and power rating) however, lithium ion batteries are still relatively expensive among others. Due to these features the Lithium Ion Battery technology stands a total chance of dominating the Battery technology market for residential and automotive applications. Also shows from the findings, the performing reliability of the Lithium ion battery by using the battery application requirements and the dangers in operating at a not required specification. More recommendations were made in areas of challenges faced by the battery storage technologies in order to make improvement.

A novel adaptive intelligent MPC scheme for frequency stabilization of a microgrid considering SoC control of EVs

In the recent years, the vehicle-to-grid (V2G) technology has been successfully implemented to stabilize the frequency deviations in a microgrid (MG) whereby charging/discharging of battery of electric vehicles (EVs) is utilized depending upon their state-of-charge (SoC). Compared to the conventional battery energy storage technology, lower degradation tendency and lesser cost of an EV battery are obvious reasons for its utilization as an alternate. This paper proposes a novel adaptive intelligent model predictive control (AIMPC) scheme for frequency stabilization of an MG considering the SoC control of the battery of the EVs. The MPC scheme operates by predicting the future behavior of a plant whereby an explicit discrete-time state-space model of the plant is utilized. Since optimal performance of the MPC depends upon the tuning parameter (τw) present in its cost function, an intelligent optimization algorithm is implemented to dynamically optimize the parameter τw and simultaneously the proposed control scheme is made adaptive. Effect of the SoC control on the frequency deviation response (FDR) of the MG is demonstrated. Further, competence of the proposed control scheme is established over the adaptive fuzzy MPC and PID controller considering diverse loading conditions in the MG. Simulation results clearly establish that the FDRs of the MG are improved with the implementation of the proposed control scheme. Lastly, sensitivity of the proposed scheme is corroborated considering parametric uncertainties in the MG.

Optimization Techniques for Improving the Performance of Solar Photovoltaic System in Conjunction with Health Informatics and the Hospital Energy Management System

Energy savings, clean energy, savings in utility and energy governance tools are buzzwords in the healthcare industry. Healthcare sectors become largest consumer of energy in the modern world. Based on data of American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), a moderate hospital consume 2.5 times higher energy than commercial buildings. As a result, increased worries about energy costs and environmental issues, as well as the anticipation of rising energy prices in the future and the need to enhance the dependability of healthcare facilities, have led to a focus on in-house power generation systems and the importance of energy management in hospitals and their health care facilities. Solar power systems that are clean and ecologically friendly have grown in popularity as distributed power generation (DPG) systems in recent years. In this work, a Grid-tied Solar PV system incorporated with Battery energy storage technology is considered in conjunction with health informatics and the hospital Energy Management System reduces energy consumption cost and improves the reliability of the power supply to run all clinical equipment available in the hospital’s Intensive Care Unit (ICU) and other premises. In this context, the Energy management controller utilised in the hospital Energy Management System will effectively use the electricity supplied by the Solar PV system while minimising grid demand and stabilising the voltage in the DC bus, which must be inverted into AC using an inverter to feed clinical loads. Furthermore the maximum power point tracking method is adopted, which enhances the quality of DC voltage generated by solar PV panels and feed to the DC bus. Sliding mode controller (SMC) is adopted in the inverter side and the quality of the inverted voltage is optimized using artificial bee colony (ABC) method. The proposed solar PV system in conjunction with health informatics and the hospital Energy Management System is developed and simulated in the MATLAB Simulink. The response of the suggested SMC and ABC techniques are compared and their outcomes are shown to confirm the performance of hospital energy management system.

A decision support tool for multi-attribute evaluation of demand-side commercial battery storage products

With the diversification of commercial energy storage technologies, choosing a suitable technology is becoming a complex decision-making process. The complexity is rooted in the many decision criteria such as technology, brand reputation, energy capacity, volume, weight, aging, and warranty among many others. As such, for non-expert users, particularly small households or enterprises, the act of energy storage adoption is becoming growingly cumbersome. To address this problem, this paper introduces a decision support tool for the evaluation of commercial (small-scale) energy storage products. It then identifies the most suitable option(s) based on the users' preferences.For the reasons elaborated in the paper, nine multi-criteria decision-making (MCDM) methodologies have been employed. Altogether, 19 attributes are identified for the evaluation of (battery) energy storage technologies. The decision support tool is developed in the Matlab environment and includes a graphical user interface for easier interaction of non-expert users. For the demonstration, three scenario cases have been studied for users with different preferences. The ranking results clearly show the marked impact of users preferences on the recommended energy storage technologies. This implies that a tool like this can help small users in the selection of their right technology and avoid resource loss due to inappropriate technology selection, which can be neither economical nor sustainable.

Optimal power system design and energy management for more electric aircrafts

Recent developments in fuel cell (FC) and battery energy storage technologies bring a promising perspective for improving the economy and endurance of electric aircraft. However, aircraft power system configuration and power distribution strategies should be reasonably designed to enable this benefit. This paper is the first attempt to investigate the optimal energy storage system sizing and power distribution strategies for electric aircraft with hybrid FC and battery propulsion systems. First, a novel integrated energy management and parameter sizing (IEMPS) framework is established to co-design aircraft hardware and control algorithms. Under the IEMPS framework, a new real-time power distribution algorithm with a flexible ratio is established to facilitate integrated parameter optimization, which can adapt to different power system configurations. Based on the comprehensive analysis of hydrogen economy, FC aging cost, and aircraft stability, a multi-objective parameter optimization model is established to decide the size of aircraft energy storage systems and hyper-parameters in the power controller. The X-57 Maxwell, an experimental electric aircraft designed by NASA, is employed to verify the developed methods. This work provides a novel power system configuration, sizing, and power management method for future commercial aircraft design, and it can further promote the aviation electrification process.

Improved Deep Q-Network for User-Side Battery Energy Storage Charging and Discharging Strategy in Industrial Parks.

Battery energy storage technology is an important part of the industrial parks to ensure the stable power supply, and its rough charging and discharging mode is difficult to meet the application requirements of energy saving, emission reduction, cost reduction, and efficiency increase. As a classic method of deep reinforcement learning, the deep Q-network is widely used to solve the problem of user-side battery energy storage charging and discharging. In some scenarios, its performance has reached the level of human expert. However, the updating of storage priority in experience memory often lags behind updating of Q-network parameters. In response to the need for lean management of battery charging and discharging, this paper proposes an improved deep Q-network to update the priority of sequence samples and the training performance of deep neural network, which reduces the cost of charging and discharging action and energy consumption in the park. The proposed method considers factors such as real-time electricity price, battery status, and time. The energy consumption state, charging and discharging behavior, reward function, and neural network structure are designed to meet the flexible scheduling of charging and discharging strategies, and can finally realize the optimization of battery energy storage benefits. The proposed method can solve the problem of priority update lag, and improve the utilization efficiency and learning performance of the experience pool samples. The paper selects electricity price data from the United States and some regions of China for simulation experiments. Experimental results show that compared with the traditional algorithm, the proposed approach can achieve better performance in both electricity price systems, thereby greatly reducing the cost of battery energy storage and providing a stronger guarantee for the safe and stable operation of battery energy storage systems in industrial parks.

Peak shaving benefit assessment considering the joint operation of nuclear and battery energy storage power stations: Hainan case study

The rapid development of battery energy storage technology provides a potential way to solve the grid stability problem caused by the large-scale construction of nuclear power. Based on the case of Hainan, this study analyses the economic feasibility for the joint operation of battery energy storage and nuclear power for peak shaving, and provides an effective solution framework for construction scale and battery type determination. Under the proposed framework, a novel cost model for the large-scale battery energy storage power station is proposed. Then, economic analysis is conducted to get the most economical battery type and construction scale by considering the comprehensive economic benefit of the joint operation under the limit of the load factor. On this basis, sensitivity analysis of economic indicators to control parameters and economic parameters is performed to further demonstrate the economic feasibility of the joint operation. Comparative analysis shows that 270 MW lithium iron phosphate battery energy storage power station has the best and stable comprehensive performance in terms of the IRR, PBP and LCOE, which are 16.27%, 6.27 year and 0.464¥/kWh, respectively. In comparison with the pumped storage, the battery energy storage has lower initial investment, faster capital recovery and smaller floor area under the joint operation mode. Moreover, sensitivity analysis illustrates that the large-scale application of battery energy storage still depends on the trade-off between the cost performance of battery and the real-time electricity price.

PV and battery energy storage integration in distribution networks using equilibrium algorithm

Taking advantage of the favorable operating efficiencies, photovoltaic (PV) with Battery Energy Storage (BES) technology becomes a viable option for improving the reliability of distribution networks; however, achieving substantial economic benefits involves an optimization of allocation in terms of location and capacity for the incorporation of PV units and BES into distribution networks. This article suggests a methodology based on the Equilibrium Optimization (EO) algorithm for optimal integration of PV with BES in radial distribution networks. Multifarious objectives are comprised to minimize the cost of energy not supplied (CENS), the investment cost of PV and BES installations, their operational costs, the power losses through the distribution lines, the produced CO2 emissions relative to the grid and PV systems. Added to that, the power losses through the voltage source converter (VSC) interface between integrated PV and BES with the grid are assessed. The proposed methodology is applied on two radial distribution systems of 30-bus and 69-bus. The optimal integration of PV systems with BES have been obtained by considering various case studies by imposing several limits on the number of PV-BES and the state of charge (SoC) for BES. Subsequently, comparative performance analysis is performed using genetic algorithm (GA), EO algorithm, particle swarm optimization (PSO), differential evolution (DE), and grey wolf optimization (GWO).

Techno-economic analysis of solar photo-voltaic/diesel generator hybrid system using different energy storage technologies for isolated islands of India

This paper exclusively investigates techno-economic performance of solar photo-voltaic (SPV)/diesel generator (DG) hybrid system using four different battery energy storage (BES) technologies namely lead acid battery, lithium ion battery, vanadium redox battery, and zinc bromine flow (ZBF) for the isolated Andaman & Nicobar and Lakshadweep islands of India. The analysis has been performed using Hybrid Optimization Model for Electric Renewables (HOMER) software at Baratang and Minicoy islands of Andaman & Nicobar and Lakshadweep, respectively, in which SPV/DG/ZBF hybrid system (20 kW SPV, 7 kW DG, 100 kWh ZBF batteries and 20 kW converter) found to be most techno-economic viable optimized solution for both locations. The net present cost, levelized cost of energy, and operating cost of this configuration are found to be $23927.21, $0.167/kWh and $338.20, respectively, for Baratang island; and $22366.64, $0.155/kWh and $217.49, respectively, for Minicoy island. Using this system as baseline configuration, analysis was extended to different BES technologies to evaluate the performance parameters like system cost, return of investment, simple payback period, energy produced, pollutant emissions, renewable penetration etc. The effectiveness of the ZBF technology is justified with the obtained results which show highest value of return of investment and renewable penetration with lowest simple payback period and pollutant emission. Finally, sensitivity analysis of the system was performed using a unique three-dimensional approach.

Techno-economic analysis of lithium-ion and lead-acid batteries in stationary energy storage application

Grid-connected renewable energy systems are considered a viable solution for satisfying the swiftly growing demand. Nevertheless, the intermittent nature of renewable energy sources (RESs) hinders their performance and can not be efficiently utilized, rather imposes power quality and instability problem on the grid system. To alleviate this challenge, it is common practice to integrate RESs with efficient battery energy storage technologies. Lead-acid batteries were playing the leading role utilized as stationary energy storage systems. However, currently, there are other battery technologies like lithium-ion (Li-ion), which are used in stationary storage applications though there is uncertainty in its cost-effectiveness. In this paper, a state-of-the-art simulation model and techno-economic analysis of Li-ion and lead-acid batteries integrated with Photovoltaic Grid-Connected System (PVGCS) were performed with consideration of real commercial load profiles and resource data. The Hybrid Optimization Model for Electric Renewables (HOMER) was used for the study of the techno-economic analysis. Besides, the performance of these batteries is greatly affected by the rate of charge and discharge cycling effects which gradually degrades the capacity of the battery. This effect was also investigated with Matlab using a simplified equivalent circuit model by considering a typical stationary application datasheet. The techno-economic simulation output provided that the system with Li-ion battery resulted in a Levelized Cost of Energy (LCOE) of 0.32 €/kWh compared to the system with lead-acid battery with LCOE of 0.34 €/kWh. Besides, the Net Present Cost (NPC) of the system with Li-ion batteries is found to be €14399 compared to the system with the lead-acid battery resulted in an NPC of €15106. According to the result found, Li-ion batteries are techno-economically more viable than lead-acid batteries under the considered specifications and application profile.

Comparison study of lead-acid and lithium-ıon batteries for solar photovoltaic applications

The battery energy storage systems are very essential for maintaining constant power supply when using solar photovoltaic systems for power generation. The viability and ability of battery energy storage systems are assessed based on battery usage in Solar Photovoltaic utility grid-connected systems. The power supply quality and reliability are improved by utilizing battery energy storage technologies in conjunction with solar photovoltaic systems. This paper presents a comparative analysis of Lead-Acid Storage battery and Lithium-ion battery banks connected to a utility grid. The battery mathematical model simulation study gives their performance characteristics of these batteries under grid-connected loads. Cost-benefit analysis of battery usage for determining the best battery suitable for solar photovoltaic system applications is also presented in this paper.

A fuzzy decision-making model for optimal design of solar, wind, diesel-based RO desalination integrating flow-battery and pumped-hydro storage: Case study in Baltim, Egypt

This paper aims to propose a conceptual design model for sustainable hybrid renewable stand-alone energy system (HRSES) to meet the electricity demand of a large-scale reverse osmosis desalination plant in Baltim, Egypt. The model investigates the feasibility of different HRSES alternatives and develop a fuzzy-based multicriteria decision-making model for meticulously selecting the optimal energy solution. Both zinc-bromine flow battery and turbine-pumped hydro energy storage technologies are integrated independently with wind, solar, and diesel power sources. Firstly, the proposed model uses HOMER software to execute an energy-economic-ecological optimization analysis for studying the practicability and components sizing of nine HRSES alternatives. Second, an integration between Fuzzy-AHP and Fuzzy-VIKOR decision-making methods is executed to choose the best design considering ten performance criteria. In the second stage, the fuzzy environment is engaged to expedite decision-makers to express their ratings in linguistic terms and to achieve more sensible and accurate results. Among ten feasible alternatives, the results reveal that the optimal system consists of 5 × 20-kW wind turbines, 328-kW photovoltaic array, 100-kW diesel generator, 112 batteries and 235-kW converter. This system has the best economic performance among all alternatives with least NPC, COE, and payback-period of $1,048,046, 0.101$/kWh and 1.1 yr, respectively. Besides, it has a treasured share of renewable of 95.55%; hence, it produces a realistic CO2 of 25,426.46 kg/year. Lastly, the sensitivity analysis illuminates that the future load growth and low-interest rate hurt upcoming investments while the projected reduction in the cost of energy storages has an encouraging influence on financing decisions.

Integration of Battery Energy Storage Systems into Natural Gas Combined Cycle Power Plants in Fuzzy Environment

The increasing share of renewable energy sources in the grid has created the need for operational flexibility for natural gas combined cycle power plants (NGCCPPs) that offer high thermal efficiency and ease of operation. However, battery energy storage technologies (BESSs), which eliminate the time and ratio imbalance between energy supply and demand, will be effective solutions that can increase plant flexibility when integrated with NGCCPPs. This integration is a decision problem with high uncertainty and complexity evaluated by grid stakeholders. For this reason, firstly, the operational goals of the power plants have been prioritized in terms of BESSs. At this phase, the combination of Pythagorean Fuzzy AHP and Pythagorean Fuzzy TOPSIS methods was used. Afterwards, to pose a sustainable projection under the mentioned operational goals, which is the main purpose of the study has been started to the phase of ranking BESSs (lead-acid, lithium-ion, vanadium redox flow battery, sodium-nickel chloride, sodium-sulfur) under different conditions. By this means, evaluating the BESSs for different application purposes, rationalizing the high uncertainty in both the energy sector and electricity markets at the same time with the proposed hierarchical model will provide an important projection to the literature. The results of the proposed methodology show that lithium-ion batteries can be an effective replacement technology alternative for NGCCPPs, given their economic benefits and technological capabilities. Another result is that the scalability of BESSs can be used for different operational goals in the power plants. This also can allow the establishment of a hybrid BESS facility.

Techno-Economic Assessment of Grid-Level Battery Energy Storage Supporting Distributed Photovoltaic Power

Centralised, front-of-the-meter battery energy storage systems are an option to support and add flexibility to distribution networks with increasing distributed photovoltaic systems, which generate renewable energy locally and help decarbonise the power sector. However, the provision of specific services at distribution level remains under development for real applications in industry. To this end, this paper presents an exhaustive techno-economic analysis of the role of front-of-the-meter battery energy storage systems in primary distribution networks with presence of distributed PV covering: (i) the siting decision for storage systems using multi-objective genetic algorithm optimisation; (ii) the response when smart capabilities for PV inverters (e.g., volt-var control) are present; and (iii) the quantification of revenue streams and compensation schemes that would bring positive profitability when providing distribution-specific services based on the supply of real and reactive power. The performance of grid-level battery energy storage technology is evaluated in the IEEE 34-bus system particularised to the distribution code of Northern Ireland, UK. The techno-economic assessment covers one year of simulations at 1-minute resolution performed with the simulation tool EPRI OpenDSS and its Python communication interface. The results show that, besides the technical benefits of centralised battery storage systems, the economic compensation based on traditional transmission-level services is not sufficient for the profitability of these projects. Several ideas are explored to improve the profitability of these systems considering the local value and decarbonisation they add. The findings presented can direct system operators and regulators towards developing schemes to incentivise centralised battery energy storage projects in distribution networks in the context of distribution-level services.

Economic analysis for centralized battery energy storage system with reused battery from EV in Australia

With battery energy storage technology development, the centralized battery energy storage system (CBESS) has a broad prospect in developing electricity. In the meantime, the retired lithium-ion batteries from electric vehicles (EV) offer a new option for battery energy storage systems (BESS). This paper studies the centralized reused battery energy storage system (CRBESS) in South Australia by replacing the new lithium-ion batteries with lithium-ion second-life batteries (SLB) and evaluating the economic benefits with economic indicators as net present value (NPV), discounted payback period (DPBP), Internal rate of return (IRR) to depict a comprehensive understanding of the development potential of the CRBESS with the lithium-ion SLB as the energy storage system. This paper proposes a calculation method of frequency control ancillary services (FCAS) revenue referring to market share rate (MSR) when building the economic model. Moreover, the residual value of lithium-ion batteries is considered. This paper uses the economic model to calculate the profitability and development potential of CRBESS. From an economic perspective, the superiority and feasibility of CRBESS compared with CBESS were analyzed.

An Evaluation of Energy Storage Cost and Performance Characteristics

The energy storage industry has expanded globally as costs continue to fall and opportunities in consumer, transportation, and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS)—lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium-metal halide batteries, and zinc-hybrid cathode batteries—four non-BESS storage systems—pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors—and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

Size-dependent mechanical-diffusion responses of multilayered composite nanoplates

ABSTRACT Multi-cell storage devices (e.g. lithium-ion batteries (LIBs)) stand as one of the most important components which are widely used in battery energy storage technology for renewable energy power system, hybrid electric vehicles and portable electronic devices due to its high energy density and low manufacturing cost. In recent years, there has been an explosion of developing new and multifunctional nanomaterials with particular interest to electrode nanomaterials (nano-MnO2, nano-LiMn2O4, etc.). In such case, size-dependent mechanical-diffusion responses analysis of multilayered composite nanostructure under non-uniform concentration in-service environment will become significantly important. To address the problem, a multilayered composite nanoplates account for diffusion impedance and elastic wave impedance at the interface is considered in this research. Governing equations involving with size-dependent characteristic lengths and material constant ratio of each two adjacent layers are formulated, and then, a semi-analytical approach via the Laplace transformation is applied. Then, the obtained solutions are applied to bilayered composite nanoplates, and the influences of size effects and material constants ratio on structural responses are emphatically discussed to provide guidelines on and new insights into the optimal design and management of mechanical responses and vibration control of nano-sized multi-cell storage devices under non-uniform concentration environment, especially for the nano-coating.