Battery Energy Storage Research Articles

Will Iron Forge the Future of Metal-Air Batteries in Grid Scale Energy Storage?

The community is exploring sustainable alternatives for grid-scale energy storage. Besides lithium-ion batteries (LIBs), such technologies with a focus on sustainability aspects offer only a limited solution for grid-scale energy storage. Rechargeable metal-air batteries (MABs) based on affordable abundant multivalent metal anodes in aqueous medium provide promising theoretical metrics, such as volumetric capacity, but do not completely fulfill their potential when scaled from lab to commercial products. Both the metal anode and the air cathode need to be addressed: corrosion, hydrogen evolution reaction (HER) during charging, and passivation all diminish the anode's effective volumetric energy density and shelf life, while the air cathode's challenges include sluggish kinetics, low efficiency, and poor stability. Nevertheless, this Perspective highlights iron-air MABs as an appealing sustainable alternative for grid-scale energy storage, since iron is abundant and affordable, recyclable, has multielectron reversible redox activity, historically rich experience in production and processing, and is safe to handle. Given that further research will be directed to exploring the composition and design of electrolytes and electrodes, it may lead to advances in scaling and commercialization, as well as reducing the environmental impact of secondary batteries utilized for grid-scale energy storage in the next decades.

Optimizing Battery Energy Storage for Fast Charging Stations on Highways

Optimizing Battery Energy Storage for Fast Charging Stations on Highways

New biconvex optimization for planning of battery energy storage systems

New biconvex optimization for planning of battery energy storage systems

A Function‐Oriented Binder with Exceptional Interface Ion Transport and Impurity Tolerance for Hard Carbon Anode

AbstractHard carbon is the sole anode material employed in commercial sodium‐ion batteries. However, its intrinsic defects and impurities will lead to battery failure, diminishing further development of sodium batteries in energy storage. Here, an acrylonitrile copolymer and poly(ethylene oxide) (LA/PEO) composite binder is developed to address these challenges in biomass‐derived hard carbon. Typical commercial biomass‐derived hard carbon with this binder (HC‐LA/PEO) achieved an initial coulombic efficiency (ICE) of 91.1% and a reversible capacity of 341.12 mAh g−1, superior to most of binders currently used. When transition metal ion impurities exist in hard carbon, the HC‐LA/PEO shows better tolerance and even shows a higher reversible capacity than its high purity counterpart. After function‐oriented design, due to hydrogen bonding and polar interaction, the HC‐LA/PEO demonstrated superior initial efficiency and reversible capacity while enhancing mechanical strength and reducing electrode brittleness. In addition, this composite binder induced a more uniform and stable SEI layer on hard carbon, improving interfacial stability and ion transport efficiency. The LA/PEO binder acts as an intelligent gatekeeper mitigating the adverse effects from intrinsic defects and impurities, consequently, gives full play to the biomass‐derived hard carbon in sodium batteries.

Interaction Mechanism and Oscillation Characteristics of Grid-Connected Concentrating Solar Power–Battery Energy Storage System–Wind Hybrid Energy System

Solar thermal concentrating solar power (CSP) plants have attracted growing interest in the field of renewable energy generation due to their capability for large-scale electricity generation, high photoelectric conversion efficiency, and enhanced reliability and flexibility. Meanwhile, driven by the rapid advancement of power electronics technology, extensive wind farms (WFs) and large-scale battery energy storage systems (BESSs) are being increasingly integrated into the power grid. From these points of view, grid-connected CSP–BESS–wind hybrid energy systems are expected to emerge in the future. Currently, most studies focus solely on the stability of renewable energy generation systems connected to the grid via power converters. In fact, within CSP–BESS–wind hybrid energy systems, interactions between the CSP, collection grid, and the converter controllers can also arise, potentially triggering system oscillations. To fill this gap, this paper investigated the interaction mechanism and oscillation characteristics of a grid-connected CSP–BESS–wind hybrid energy system. Firstly, by considering the dynamics of CSP, BESSs, and wind turbines, a comprehensive model of a grid-connected CSP–BESS–wind hybrid energy system was developed. With this model, the Nyquist stability criterion was utilized to analyze the potential interaction mechanism within the hybrid system. Subsequently, the oscillation characteristics were examined in detail, providing insights to inform the design of the damping controller. Finally, the analytical results were validated through MATLAB/Simulink simulations.

Flow Channel Optimization and Performance Analysis of Forced Air-Cooling Thermal Management for Lithium-ion Battery Energy Storage Modules

<div>The maximum temperature and the maximum temperature difference of lithium battery energy storage systems are of great importance to their lifespan and safety. The energy storage module targeted in this research utilizes a forced air-cooling thermal management system. In this article, the maximum battery temperature, temperature difference, and cooling fan power are used as evaluation indicators. The thermal–fluid coupling simulation technology is utilized to restore the real structure of the module, ensuring the reliability of the simulation results. The P-Q curve is introduced for the boundary conditions of the heat dissipation fan to investigate the influence of the flow channel structure on the airflow volume and distribution. First, the thermal–fluid coupling simulation results of the original structure were compared with the measured parameters. Subsequently, the study on the airflow and temperature distribution of the original flow channel structure reveals that a significant pressure drop occurs when the airflow passes through the energy storage module, and the high-temperature areas are concentrated in the middle and rear sections of the flow channel. Based on the above analysis, fluid simulation is employed to study and propose three improvement schemes. Scheme A involves adding an arc-shaped air duct at the right-angle bend of the air inlet; scheme B consists of increasing the opening area of the air inlet; and scheme C entails reducing the cross-sectional area of some flow channels. Eventually, the thermal–fluid coupling simulation is adopted to verify the individual schemes and the combined schemes. After comparing the results, the following improvement effects are obtained: a 4.591% reduction in the maximum temperature, a 31.144% reduction in the temperature range, and a 16.583% reduction in the static pressure power of the fan.</div>

Unrestraining The Biot Number for Systems with Internal Heat Generation

Abstract Thermal runaway from hot spots in systems such as solar energy storage pose safety concerns. Tools for rapid analysis of these systems would be exceedingly useful in their development and maintenance. The “Lumped Capacitance” (LC) assumption is one such tool and is limited to Biot numbers less than about 0.1. However, for systems like energy storage batteries with internal heat generation, there is no such tool. A numerical solution was, therefore, used to compute the spatiotemporal temperature of cooling spheres with varying thermal conductivity, characteristic length scale, and internal heat generation rate to determine the effects internal heat generation has on LC accuracy. Increasing the heating time or decreasing the thermal conductivity hinders LC accuracy, while increasing the internal heat generation rate or characteristic length scale improves it. This means that larger volumes improve the accuracy of LC, completely inverting its previous relationship. The Buckingham-Pi theorem was then used to create a new nondimensional group, the Yonkist number, in order to provide an analogous Biot number for systems with heat generation. Ultimately, it was found that LC can be utilized for systems with unlimited Biot numbers, as long as the internal heat generation rate is sufficiently large or the heating time sufficiently small to make the Yonkist number less than the Biot number. The use of the new Yonkist number removes the upper boundary from the range of Biot numbers to which the LC assumption can be applied and allows expedient heat transfer analyses for thermal runaway problems.

PIDE: Photovoltaic integration dynamics and efficiency for autonomous control on power distribution grids

PIDE: Photovoltaic integration dynamics and efficiency for autonomous control on power distribution grids

Assessment and Optimization of Residential Microgrid Reliability Using Genetic and Ant Colony Algorithms

The variability of renewable energy sources, storage limitations, and fluctuations in residential demand affect the reliability of sustainable energy systems, resulting in energy deficits and the risk of service interruptions. Given this situation, the objective of this study is to diagnose and optimize the reliability of a residential microgrid based on photovoltaic and wind power generation and battery energy storage systems (BESSs). To this end, genetic algorithms (GAs) and ant colony optimization (ACO) are used to evaluate the performance of the system using metrics such as loss of load probability (LOLP), loss of supply probability (LPSP), and availability. The test system consists of a 3.25 kW photovoltaic (PV) system, a 1 kW wind turbine, and a 3 kWh battery. The evaluation is performed using Python-based simulations with real consumption, solar irradiation, and wind speed data to assess reliability under different optimization strategies. The initial diagnosis shows limitations in the reliability of the system with an availability of 77% and high values of LOLP (22.7%) and LPSP (26.6%). Optimization using metaheuristic algorithms significantly improves these indicators, reducing LOLP to 11% and LPSP to 16.4%, and increasing availability to 89%. Furthermore, optimization achieves a better balance between generation and consumption, especially in periods of low demand, and the ACO manages to distribute wind and photovoltaic generation more efficiently. In conclusion, the use of metaheuristics is an effective strategy for improving the reliability and efficiency of autonomous microgrids, optimizing the energy balance and operating costs.

Optimization of Sizing of Battery Energy Storage System for Residential Households by Load Forecasting with Artificial Intelligence (AI): Case of EV Charging Installation

This paper presents the optimization sizing of a battery energy storage system for residential use from load forecasting using AI. The solar rooftop panel installation and charging systems for electric vehicles are connected to the low-voltage electrical system of the Metropolitan Electricity Authority (MEA). The daily electricity demand for future load forecasting used the long short-term memory (LSTM) technique in order to analyze the appropriate size of the battery energy storage system (BESS) for residences. The solar rooftop installation capacity is 5.5 kWp, which produces an average of 28.78 kWh/day. The minimum actual daily load in a month is 67.04 kWh, comprising the base load and the load from charging electric vehicles, which can determine the size of the battery energy storage system as 21.03 kWh. For this research, load forecasting will be presented to find the appropriate size of BESS by considering the minimum daily load over the month, which is equal to 102.67 kWh, which can determine the size of the BESS to be 17.84 kWh. When comparing the size of BESS from actual load values with the load from the forecast, it can significantly reduce the size and cost of BESS.

Integrating Battery Energy Storage Systems for Sustainable EV Charging Infrastructure

The transition to a low-carbon energy matrix has driven the electrification of vehicles (EVs), yet charging infrastructure—particularly fast direct current (DC) chargers—can negatively impact distribution networks. This study investigates the integration of Battery Energy Storage Systems (BESSs) with the power grid, focusing on the E-Lounge project in Brazil as a strategy to mitigate these impacts. The results demonstrated a 21-fold increase in charging sessions and an energy consumption growth from 0.6 MWh to 10.36 MWh between June 2023 and March 2024. Compared to previous findings, which indicated the need for more robust systems, the integration of a 100 kW/138 kWh BESS with DC fast chargers (60 kW) and AC chargers (22 kW) proved effective in reducing peak demand, optimizing energy management, and enhancing grid stability. These findings confirm the critical role of BESSs in establishing a sustainable EV charging infrastructure, demonstrating improvements in power quality and the mitigation of grid impacts. The results presented in this study stem from a project approved under the Research and Development program of the Brazilian Electricity Regulatory Agency (ANEEL) through strategic call No. 022/2018. This initiative aimed to develop a modular EV charging infrastructure for fleet vehicles in Brazil, ensuring minimal impact on the distribution network.

Net-zero energy communities at Local Climate Zones: integrating photovoltaics and energy sharing for a social housing neighborhood

Abstract Integrating renewable energy systems into urban neighborhoods is essential for achieving sustainable development and decarbonization. This study investigates the integration of building-integrated photovoltaics and energy-sharing mechanisms to achieve net-zero energy communities in low-income urban neighborhoods. Using a social housing neighborhood in Ioannina, Greece, within Local Climate Zone 6, as a case study, we evaluated energy performance through hourly simulations. Annual PV generation (1096.2 MWh) exceeded the total load (931.5 MWh), achieving net-positive energy status. Incorporating a 1000 kWh battery energy storage system improved the hourly load match from 39.1 to 81% and reduced grid imports and exports by 52% and 37%, respectively. The findings underscore the potential of energy-sharing systems to enhance urban energy resilience and self-sufficiency. In addition, the study emphasizes the importance of leveraging Local Climate Zone characteristics to design energy systems tailored to urban contexts. Policy incentives and further research are recommended to promote cost-effective energy-sharing models in similar contexts.

Design and Performance Analysis of a Hybrid Grid-connected PV System: A Case Study of Wakanda Estate's 1.5MWh Solar Installation

Due to technological advancements, there are efforts globally to lessen the generation of carbon dioxide, one of the gases responsible for the greenhouse effect. Renewable energy has seen tremendous growth in recent years. In order to protect the environment from pollution and provide electricity from an endless source for future generations, renewable energy sources, particularly solar energy via photovoltaic systems have come to stay. This paper simplified the process, control mechanism and cost benefit of connecting solar farm (Wakanda estate as case study) for hybrid applications, directly connected to the grid with an inverter during high power demand or as standalone off grid system using batteries for energy storage when supply to the grid is not needed. Due to the intermittent nature of solar irradiance, an MPPT (Maximum Power Point Tracking) is applied to the topology. The MPPT algorithm must strike a compromise between maximizing power extraction and power quality issues, especially harmonic distortion brought on by switching elements, when interacting with the grid to dynamically modify the operating voltage to harness the most power possible under a variety of environmental conditions. The control mechanism commonly adopts a cascaded structure where the MPPT determines appropriate voltage references while an inner current control loop manages grid synchronization. Filters play a dual role in the management of harmonics in solar PV system. Despite its usefulness in removing chopped signals, filter dynamics (usually LCL configurations) must be taken into consideration since they can present resonance issues that have the potential to also destabilize the system if not well managed, particularly when irradiance changes quickly. In order to preserve stability during grid disruptions and guarantee that power quality criteria are fulfilled by adaptive filtering, advanced MPPT implementations and include anti-islanding protection, low-voltage ride-through capabilities, and dynamic impedance matching. The process was investigated by modeling and simulating photovoltaic arrays in MATLAB-Simulink using solar cell block from SimElectronics where influence of variable elements such as solar radiation was checked against performance of photovoltaic cells.

Design and implementation of a photovoltaic system for health facilities in rural areas of Uganda

The persistent issue of unreliable electricity in rural Ugandan healthcare facilities significantly hinders the provision of essential medical services, affecting everything from diagnostic testing to emergency care. This study addresses the urgent need for dependable, renewable energy solutions by designing and implementing a photovoltaic (PV) system specifically tailored to meet the energy requirements of rural health centres. The primary aim of this research was to develop a cost-effective, portable solar power system that can provide continuous power for critical medical equipment, including portable ultrasound scanners, medical centrifuges, vaccine refrigerators, and other essential diagnostic and monitoring devices. The PV system comprises two 50 W monocrystalline solar panels, a buck-boost converter for voltage regulation, a 12 V, 25 Ah maintenance-free battery for energy storage, and a single-phase inverter capable of producing 1 kW of power with an integrated inverter driver system to handle three-phase load requirements. Experimental testing was conducted over a three-month period, during which the system operated from 8:55 AM to 5:00 PM, five days a week. Data on voltage, current, power, and efficiency were recorded, showing an average system efficiency of 92.46%, even under varying sunlight conditions. The high efficiency and portability of the PV system underscore its suitability for off-grid healthcare facilities, enabling reliable operation of life-saving equipment and improving the quality and continuity of care. Compared with existing systems in similar regions, this study’s approach offers a portable, robust, and low-maintenance solution that directly addresses the challenges faced by rural healthcare facilities. The key contribution of this research is its practical, adaptable PV system model, which can be scaled and modified for use in other resource-limited settings. By providing a renewable and consistent energy source, this study advances the field of sustainable healthcare infrastructure and highlights the potential of PV technology to improve healthcare accessibility in underserved areas.

Model predictive control for micro-hydro, solar photovoltaic-based standalone microgrid with power quality improvement

ABSTRACT This study presents the control of a micro-hydro-driven self-excited induction generator (SEIG) and solar photovoltaic (PV)-based standalone microgrid. PV is connected to the microgrid through a cascaded connection of a boost converter (BC) and a voltage source inverter (VSI). The stator terminals of the SEIG are connected to the same VSI through inductive filters. Constant switching frequency-based model predictive current control (CSF-MPCC) is adopted for the control of the VSI. In addition to active power injection, the VSI improves the power quality of the microgrid along with regulating the amplitude of the point of common coupling (PCC) voltage. To improve the power quality, the reference load harmonic currents are extracted through third-order filters (TOFs) due to their efficient estimation and good dynamic performance, even during unbalanced loading conditions. Further, to maintain the frequency of the standalone microgrid, the system’s load demands should be kept constant. Consequently, the surplus or deficit power after feeding consumer loads is used to charge or discharge the battery energy storage system (BESS) connected to the DC-link of VSI through a bidirectional converter (BDDC). The performance of the developed CSF-MPCC is demonstrated and validated through MATLAB simulation and real-time hardware results under various scenarios.

Synergetic simplified super-twisting algorithm control for stability enhancement of PV/BESS-based DC microgrid

To address the challenges of global warming and the greenhouse effect, extensive research has been dedicated to microgrids (MGs) powered by renewable energy sources (RESs). This paper presents an innovative control mechanism, the synergetic simplified super-twisting algorithm (SSSTA), designed specifically for a DC-MG incorporating a battery energy storage system (BESS), a solar photovoltaic (PV) unit, and DC loads. The PV system connects to a shared DC bus via a unidirectional DC–DC boost converter, optimized for maximum power point tracking from the PV generator. At the same time, the BESS is linked using a bidirectional DC–DC buck-boost converter to the same bus, aimed at maintaining supply–demand balance within the DC-MG through charging and discharging. The SSSTA is designed to regulate each power control unit in the MG. It ensures the desired voltage level at the common DC bus while tailoring energy allocation to meet load requirements. The study shows that SSSTA improves the performance and stability of DC-MG systems incorporating solar PV and batteries. By implementing SSSTA, the stability of the MG system is sustained even under varying load conditions, thereby minimizing the impact of disturbances such as fluctuations in load demand and solar irradiation. As a result, implementing this control strategy enhances the reliability and efficiency of MGs integrated with RESs, promoting broader adoption. Furthermore, to offer a clearer understanding of the proposed control approach, the results of the proportional-integral control are also presented. Simulation experiments in MATLAB confirm the effectiveness of the designed control mechanism.

Reliability enhancement with coordinated operation of wind power and battery energy storage using machine learning based unit commitment decision

Reliability enhancement with coordinated operation of wind power and battery energy storage using machine learning based unit commitment decision

Addressing solar power curtailment by integrating flexible direct air capture

Addressing solar power curtailment by integrating flexible direct air capture

Flexible-fidelity modeling for faster-than-real-time emulation of modular multilevel converter with battery energy storage

Flexible-fidelity modeling for faster-than-real-time emulation of modular multilevel converter with battery energy storage

Sustainable recycling of Na3V2(PO4)3 cathodes: A pathway to high-safety Na-Ni dual-ion batteries for scalable energy storage

Sustainable recycling of Na3V2(PO4)3 cathodes: A pathway to high-safety Na-Ni dual-ion batteries for scalable energy storage