Battery Hybrid Energy Storage System Research Articles

Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions

In recent years, growing consumer demand for sustainable energy is driving down costs and paving the way for more clean energy in the future. Since these energies are sporadic, and the load pattern does not correlate to their generation pattern, a battery storage system is required. Operating dispersed alternative energy sources, connected to the grid in this situation makes energy control an unavoidable task. The difficulty is brought on by things like intermittent sources, daytime costs, solar panel and battery size restrictions, and limitations in battery charging and discharging rates. Moreover, integrating energy storage devices into the power system network is one of the recommendations made in this work to increase the performance and dependability of these systems. Compared to the existing works reported in the literature, this study offers enhanced control techniques for hybrid Photovoltaic and Battery Energy Storage System under fluctuating atmospheric scenario. Here, an innovative approach called Drone Squadron Optimisation, which tracks the Global Maximum Power Point, is used get maximum power. Further, suggested approach is tested with various partial shading instances and the uniform irradiance condition to validate it. This research also investigates photovoltaic models and the status of the battery storage device for improved energy management in the system. Finally, the proposed algorithm assists in quickly identifying the potential benefits of a grid-connected, battery-powered rooftop solar system.

Strategy of Flywheel–Battery Hybrid Energy Storage Based on Optimized Variational Mode Decomposition for Wind Power Suppression

The fluctuation and intermittency of wind power generation seriously affect the stability and security of power grids. Aiming at smoothing wind power fluctuations, this paper proposes a flywheel–battery hybrid energy storage system (HESS) based on optimal variational mode decomposition (VMD). Firstly, the grid-connected power and charging–discharging power of the HESS are determined based on the sliding average algorithm. Secondly, the VMD algorithm, optimized using long short-term memory (LSTM), is used to decompose the hybrid energy storage power (HESP) into a series of sub-modes with frequencies from low to high. Then, the state of charge of the battery energy storage system and the speed of the flywheel energy storage system are monitored in real time, and the primary power of the HESS is modified according to the rules formulated by fuzzy control. Finally, through a simulation example, it is concluded that the method meets the requirements of smoothing wind power fluctuations and gives full play to the characteristics of energy storage battery and flywheel energy storage to ensure the stable operation of the energy storage system. The method presented in this paper can provide a reference for HESP configuration and control operation strategy formulation.

Distributed Cooperative Control of BESSs in AC and DC Hybrid Microgrid and Its Energy Internet Paradigm

An AC and DC hybrid microgrid, which inherits advantages of AC and DC microgrids and discards some disadvantages, is considered to be the most promising power network structure and gradually applied in the community. Usually, the AC subgrid and the DC subgrid are interconnected by Bidirectional Interlink Power Converters (BILPCs). Besides, in view of the different droop characteristics of AC subgrid and the DC subgrid, it is necessary to design a suitable distributed secondary controller for an AC and DC hybrid microgrid. Accordingly, this paper proposes a flexible and scalable distributed control framework for an AC and DC hybrid battery energy storage system (ADHB) with BILPCs in an Energy Internet (EI) paradigm. An ADHB governed by multi agent systems via a cloud server can reach the State-of-Charge balance, proportional power sharing, frequency and voltage restoration. The proposed control framework provides the group play-and-plug by adding or removing an inter-MASs interaction link. For a single BILPC in an ADHB, active/reactive power, frequency and voltage are adjusted by an AC BESS. For the parallel BILPCs in EI, a decentralized secondary control scheme is proposed. Communication delay issues and stability are analysed. Then, the relevant simulation results verify the correctness of the proposed scheme.

Co-optimization of speed planning and cost-optimal energy management for fuel cell trucks under vehicle-following scenarios

Fuel cell hybrid electric heavy-duty vehicles play a key role to realize green and low-carbon travel. To cope with actual traffic environment, an advanced energy management strategy (EMS) is crucial to ensure vehicle’s efficiency and economy. In this paper, a predictive co-optimization control method is designed to achieve speed planning and energy management for the host vehicle with a fuel cell/Li-ion battery hybrid energy storage system under vehicle-following scenarios. Firstly, the host vehicle obtains the real-time speed of leading vehicle by communication technology, and speed prediction for the leading vehicle is implemented by fuzzy C-means clustering enhanced Markov Chain (FCM-MC) considering driving habits. Secondly, based on speed prediction results, the speed planning which aims to ensure safe inter-vehicle distance and minimize the demanded vehicular power is implemented to derive the speed curve of host vehicle. Finally, according to speed planning results, predictive energy management is applied to achieve power allocation between fuel cell (FC) and battery. The simulation results denote that the proposed speed prediction method can decrease forecast error effectively. The speed planning ensures the safe inter-vehicle distance. With speed prediction accuracy improved, the proposed hierarchical energy management strategy can reduce fuel cell degradation cost by 1.31%-3.48% and total operation cost by 0.75%-1.94%.

Research on frequency modulation capacity configuration and control strategy of multiple energy storage auxiliary thermal power unit

The rapid development of new energy sources has had an enormous impact on the existing power grid structure to support the “dual carbon” goal and the construction of a new type of power system, make thermal power units better cope with the impact on the original grid structure under the background of the rapid development of new energy sources, promote the consumption of new energy sources such as solar and wind energy, and further expand the channels for upgrading and flexibility transformation of thermal power energy storage, improve the stability, safety and economy of thermal power unit operation. Therefore, based on the research status at home and abroad, a hybrid energy storage system is added to solve the above problems. The lithium battery-flywheel control strategy and the regional dynamic primary frequency modulation model of thermal power units are proposed, and study the capacity configuration scheme of flywheel‑lithium battery hybrid energy storage system under a certain energy storage capacity, the frequency modulation performance is evaluated by the system frequency fluctuation degree, fluctuation peak range and other indicators. Study under a certain energy storage capacity thermal power unit coupling hybrid energy storage system to participate in a frequency modulation of the optimal capacity configuration scheme, and perform simulation verification using MATLAB/Simulink. When the thermal power unit is coupled with a 10.8612 MW/2.7151 MWh flywheel energy storage system and a 4.1378 MW/16.5491 MWh lithium battery energy storage system, while adaptive variable coefficient droop control is adopted, the system frequency range is 0.00328 p.u.Hz, and the fluctuation degree of the output power of the thermal power units is 0.00498 p.u.MW, compared to the individual frequency regulation of thermal power units, it reduces 52.07 % and. The results show that when the thermal power unit is disturbed by external load, hybrid energy storage assisted thermal power unit frequency modulation reduces the mechanical loss of thermal power unit to a certain extent and extends the service life of the unit, effectively improve the operation stability and economy of thermal power units, further reduce the phenomenon of abandoning wind and light, and better promote the utilization of new energy.

Socio-political evaluation of renewable energy resources under uncertain environment

Countries are developing green transition policies to reduce their dependency on conventional resources and to eliminate environmental concerns while meeting increasing energy demand. Renewable energy, thus, has a crucial effect on accomplishing these policies. To ensure a rapid spread of renewable energy and develop resilient renewable energy policies concerning the evaluation of renewable energy resources, socio-political factors should be considered. However, evaluating renewable energy technologies regarding the socio-political aspect is clearly more difficult and uncertain than a study focused only on quantifiable objectives, but it is critical since real projects are affected by such aspects. Multi-criteria decision-making (MCDM) techniques are best for addressing such issues with conflicting objectives. In this study, an integrated AHP-TOPSIS method with Pythagorean fuzzy sets (PFSs) was used to create the socio-political index for evaluating renewable energy hybrid technologies and Battery Energy Storage Systems (BESSs) in Turkey. The results showed that while solar energy has the highest socio-political index, Run of River with BESSs alternative ranks as the lowest.

A Grid-Connected Optimal Hybrid PV-BES System Sizing for Malaysian Commercial Buildings

In this article, the optimal sizing of hybrid solar photovoltaic and battery energy storage systems is evaluated with respect to rooftop space and feed-in tariff rates. The battery scheduling is performed using a proposed rule-based energy management strategy. The rules are formulated based on the demand limit, PV export power limit, and state of charge of the battery. Furthermore, optimization modeling with initial choices of parameters and constraints in terms of solar photovoltaic and battery energy storage capabilities is developed to minimize the total net present cost. The hourly values of solar irradiance, air temperature, electrical loads, and electricity rates are considered the inputs of the optimization process. The optimization results are achieved using particle swarm optimization and validated through an uncertainty analysis. It is observed that an optimal photovoltaic and battery energy storage system can reduce the cost of electricity by 12.33%, including the sale of 5944.029 kWh of electricity to the grid. Furthermore, energy consumption, peak demand, and greenhouse gas emissions are reduced by 13.71%, 5.85%, and 62.59%, respectively. A comprehensive analysis between the variable and fixed data for the load, energy from PV, batteries, and the grid, and costs demonstrates that the optimal sizing of photovoltaic and battery energy storage systems with the best mix of energy from PV, batteries, and the grid provides the optimal solution for the proposed configuration.

Operation Simulation and Economic Analysis of Household Hybrid PV and BESS Systems in the Improved TOU Mode

With the popularization of electric vehicles and electric boilers, household electricity consumption will increase significantly. Household hybrid photovoltaic (PV) systems and battery energy storage systems (BESSs) can supply increasing household electricity consumption without expanding the existing distribution network. This paper validates the technical feasibility of connecting a large number of household power users that contain BESSs and PVs in a distribution line by a simulation in Matlab. In addition to technical feasibility, this article improves the time-of-use (TOU) form to achieve economic feasibility (covering equipment costs). In the past, the TOU was set from the perspective of the load demand of the grid, but the actual user participation would affect this effect. In this paper, based on a social science survey, a new three-level rate TOU is introduced, which has little impact on residents’ lifestyle, to effectively increase the response frequency effectively. Combined with the improved TOU and the state of PVs, the BESS control mode is set for simulation. To compare the three-tier rate TOU with the normal TOU tariff and select the best household BESS size, a MATLAB simulation is used to simulate the common household BESS capacity. The results indicate that the combination of the three-tier rate TOU with a 4 kWh household BESS can afford the investment of household PVs and BESSs. The high cost issue that previously primarily limited the true use of BESSs is expected to be resolved.

Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm

The need for energy and environmental sustainability drives the adoption of renewable energy systems to reduce greenhouse gas emissions. Efficient planning of energy sources is crucial for a reliable distribution network. This article solves the optimal allocation of hybrid energy sources (i.e., Renewable Distribution Generators (RDGs) and Battery Energy Storage System (BESS)) problem, aiming to minimize the annual energy loss and investment costs simultaneously. The proposed formulation includes the uncertainties such as forced outages of RDG’s, intermittence in RDG power generation, Expected Energy Not Served (EENS) by DG units, and time-varying demand altogether in the existing formulation. To evaluate the effectiveness of the proposed formulation, a Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamic Resource Allocation (MOEA/D-DRA) is used. Simulation studies are conducted on IEEE 33-node and TNEB 84-node Radial Distribution Systems (RDSs), comparing results with the Rider Optimization Algorithm (ROA) and Hybrid Nelder Mead-Particle Swarm Optimization (HNMPSO) respectively. The proposed formulation for a Multi-objective Optimization of Hybrid Energy Sources allocation problem solved by the MOEA/D-DRA algorithm provides improved benefits like minimum annual energy loss, investment cost, CO2 emission, EENS by the DG units, and enhanced system voltage stability and voltage profile.

Economic Feasibility of Hybrid Solar-Powered Charging Station with Battery Energy Storage System in Thailand

Developing a public charging infrastructure is essential for the promotion of electric cars (EVs), especially in developing countries. The use of renewable energy sources (RESs), especially solar and the replacement of fossil fuels in EV charging stations has the potential to improve economic efficiency while significantly lowering greenhouse gas emissions and improving urban air quality. Therefore, the purpose of this paper is to investigate the economic feasibility of a hybrid solar photovoltaic (PV) and battery energy storage system (BESS) for environmentally friendly EV charging stations in a university campus under different EV charger utilization rates, electricity costs, and charging types. The results showed that installing a level 2 solar PV charging station at the current subsidized rate provides the most economic benefits, while installing BESS for peak shaving is the least profitable due to the high cost. The sensitivity analysis also revealed that if the cost of the BESS decreases, the IRR of the project will increase. This study aims to promote the development of technologically and environmentally feasible EV charging stations powered by RESs.

Design and Evaluation Framework for Modular Hybrid Battery Energy Storage Systems in Full-Electric Marine Applications

In the context of the maritime transportation sector electrification, battery hybridization has been identified as a promising manner of meeting the critical requirements on energy and power density, as well as lifetime and safety. Today, multiple promising battery hybridization topologies have been identified, while there is not a level playing field enabling comparison between different topologies. This study bridges this gap directly by proposing a generic hybrid battery energy storage system (HBESS) design and evaluation framework in full-electric marine applications that accounts for the key design requirements in the system topology conceptualization phase. In doing so, generalized key component models, such as battery cell models, aging models, power converter models, and thermal models, are established. Additionally, given the selected key requirements in this study, the case study comparing one baseline monotype design and two HBESS topologies has shown the clear advantage of battery hybridization. Furthermore, we find that, depending on the topology selection and the specific load scenario being considered, power converter devices can also worsen the key performance indexes.

Power distribution optimization of a fully active hybrid energy storage system configuration for vehicular applications

As an effective solution to limitations of vehicle-mounted single-battery energy storage system, the super-capacitor (SC)/battery hybrid energy storage system (HESS) is a research topic that is receiving more and more attention and emphasis from scientific research institutions in various countries. Despite its current widespread recognition in vehicle field, low energy utilization and low work efficiency under the variable working conditions of vehicle particularly limit its practical application and popularity. The power distribution optimization is critical to obtain a HESS with superior performance such as good reliability and high efficiency. This work presents a variable voltage SC/battery HESS configuration based on series-parallel switching technology of SCs, which can realize multiple working modes of the HESS to meet the needs of complex and variable working conditions of vehicle, and increase the power output range of the HESS. Taking the proposed HESS as application object, an energy efficiency model of the HESS is established, as well as an optimization model with energy efficiency maximization as the optimization goal. Power distribution optimization methods based on Genetic Algorithm (GA) and Gray Wolf Algorithm (GWA) respectively are proposed, and compared to fixed rules-based and fuzzy-based control strategies. The optimization algorithms-based methods can almost obtain the highest energy efficiency (from 91% to 87%) within the entire power demand range (from 100 W to 500 W), have obvious advantages in comparison of several other methods. The efficiency in the whole New European Driving Cycle (NEDC) driving condition exceeds 85%, and in the most periods of this driving condition exceeds 90%. The results clearly demonstrate validity and reliability of the power distribution optimization methods proposed in this paper. This work aims to solve the problem concerning the optimal power distribution based on energy efficiency maximization of HESS, and provide solution for improving the power output capacity and energy utilization of HESS. We firmly believe that this work has considerable theoretical significance and engineering application value for the promotion of HESS.

An Examination of Power Converter Architectures for Utility-Scale Hybrid Solar Photovoltaic and Battery Energy Storage Systems: The Features of Several Power Conversion Architectures

Recently, the falling costs of photovoltaic (PV) and battery storage (BS) technologies have raised interest in the creation of hybrid PV+BS power plants. Together with increasing energy storage capacity by storing clipped energy, hybrid plants broaden a power plant’s grid services by featuring fast dispatch flexibility and voltage-ampere reactive support. Although many proposed PV plants are being developed with colocated batteries, the dominant architecture of ­utility-scale PV+BS power plants is uncertain. Moreover, power architectures are expected to evolve over time based on future trends. The primary goal of this article is to critically examine and compare several dc–dc and dc–ac power converter architectures that are suitable candidates for hybrid PV+BS power plants. In particular, the article presents characteristics of several power conversion architectures from the point of view of power semiconductor requirements, efficiency, reactive component requirements, modularity, control complexity, and so forth. Detailed analytical models are utilized, along with a benchmark design example to present a comparative evaluation of the alternatives for performing engineering tradeoff studies.

Development of a Method for Sizing a Hybrid Battery Energy Storage System for Application in AC Microgrid

This article addresses the development of the energy compensation method used for the design of hybrid energy storage systems—HBESS. The combination of two battery technologies offers better cost and performance when considering microgrid systems to provide uninterrupted power to sensitive loads (substation auxiliary system) and also provides greater energy security. In the event of a failure, the load needs to continue operating, and batteries such as lithium ions have a fast response, but are expensive for large-scale systems. However, some technologies offer low-cost and good availability of energy for long hours of discharge, such as lead–acid batteries. Consequently, different battery technologies can be used to meet all the needs of the sensitive loads. A specific method for sizing a HBESS was developed for islanded microgrids to support sensitive loads. This method was developed to meet the demand for substations outside the Brazilian standard of power systems that lack an uninterrupted and reliable energy source. The method is validated by designing a microgrid to support the auxiliary systems of a transmission substation in northeastern Brazil. The results showed a system with a capacity of 1215 kWh of lead-carbon and 242 kWh of lithium ions is necessary to maintain an islanded microgrid for at least 10 h. Furthermore, the microgrid comprises a PV plant with an AC output power of 700 kW in connected operation and 100 kW when islanded from the grid.

The Possibility of Using Superconducting Magnetic Energy Storage/Battery Hybrid Energy Storage Systems Instead of Generators as Backup Power Sources for Electric Aircraft

The annual growth rate of aircraft passengers is estimated to be 6.5%, and the CO2 emissions from current large-scale aviation transportation technology will continue to rise dramatically. Both NASA and ACARE have set goals to enhance efficiency and reduce the fuel burn, pollution, and noise levels of commercial aircraft. However, such radical improvements require radical solutions. With the current traditional aircraft designs based on gas turbines or piston engines, these goals are infeasible. Small-scale aircraft have successfully proven emission reductions using energy storage systems, such as Alice aircraft. This paper involves an investigation of the possibility of using superconducting magnetic energy storage (SMES)/battery hybrid energy storage systems (HESSs) instead of generators as backup power sources to improve system efficiency and reduce emissions. Two different power system architectures of electric aircraft (EA) were compared in terms of reliability and stability in a one-generator failure scenario. As weight is crucial in EA designs, the weights of the two systems were compared, including the generators and energy storage systems. The two EA systems were built in Simulink/MATLAB to compare their reliability and stability. With the currently available technologies, based on the energy density of 250 Wh/kg for lithium-ion batteries and a power density of 8.8 kW/kg for generators, the use of the generators as backup sources proved more efficient than the use of HESS. The break-even point was observed at 750 Wh/kg for battery energy density. Any value more than the 750 Wh/kg energy density makes HESS lighter and more efficient than generators.

Energy management of PV wind based microgrid with hybrid energy storage systems

Power demand all around the world is increasing day by day and conventional energy sources are getting depleted. In order to meet the power demand and to reduce the carbon emission caused by the conventional energy sources, alternate renewable energy sources are important. wind and solar are two reliable energy sources among the various renewable energy sources. In this proposed paper wind and photovoltaic (PV) energy-based direct current (DC) microgrid is proposed with super capacitor and battery hybrid energy storage systems. Constant DC link voltage is the replication of energy balance in DC microgrid. The main goal of the proposed microgrid energy management algorithm is to maintain the constant DC link voltage irrespective of the intermittent nature of the renewable energy sources, load variations and under fault conditions. Energy management system is designed such that battery energy storage system handles the average power requirements and super capacitor handles the transient power requirements caused by the load, renewable energy variation and also caused due to fault conditions. The proposed system improves battery life along with effective DC link voltage regulation. The proposed control algorithm of energy management is compared with conventional energy management system in MATLAB/Simulink and presented for various studies.

Battery Hybrid Energy Storage Systems for Full-Electric Marine Applications

The high cost of Lithium-ion battery systems is one of the biggest challenges hindering the wide adoption of electric vessels. For some marine applications, battery systems based on the current monotype topologies are significantly oversized due to variable operational profiles and long lifespan requirements. This paper deals with the battery hybrid energy storage system (HESS) for an electric harbor tug to optimize the size of the battery system. The impact of battery hybridization was investigated on three key performance indicators inclusive of cost, system efficiency, and battery weight. The design life of the battery system is considered to be 10 years, and NMC and LTO cell technologies are used as high-energy (HE) and high-power (HP) battery cells. The HESS design is based on a parallel full-active architecture with a rule-based energy management strategy. The results of this research indicate that battery hybridization can reduce the system cost by around 28% and 14% in comparison with a monotype battery with LTO and NMC cells, respectively. Although no noticeable difference in system efficiency is observed between the monotype system and HESS, battery hybridization reduces the total weight of the battery cells by more than 30% compared to monotype topology. This study implies that the hybridization of battery systems could be a promising solution to reduce the cost and weight of large battery packs in electric vessels.

Open-source project feasibility tools for supporting development of the green ammonia value chain

Ammonia plays a vital role in feeding the world through fertilizer production, as well as having other industrial uses. However, current ammonia production processes rely heavily on fossil fuels, mostly natural gas, to generate hydrogen as a feedstock. There is an urgent need to re-design and decarbonise the production process to reduce greenhouse emissions and avoid dependence on volatile gas markets and a depleting resource base. Renewable energy driven electrolysis to generate hydrogen provides a viable pathway for producing carbon-free or green ammonia. However, a key challenge associated with producing green ammonia is managing low cost but highly variable wind and solar renewable energy generation for hydrogen electrolysis while maintaining reliable operation of the less flexible ammonia synthesis unit. To date, green ammonia production has only been demonstrated at pilot scale, and optimising plant configurations and scaling up production facilities is an urgent task. Existing feasibility studies have demonstrated the ability to model and cost green ammonia production pathways that can overcome the technical and economic challenges. However, these existing approaches are context specific, demonstrating the ability to model and cost green ammonia production for defined locations, with set configurations. In this paper we present a modelling framework that consolidates the array of configurations previously studied into a single framework that can be tailored to the location of interest. Our open-source green ammonia modelling and costing tool dynamically simulates the integration of renewable energy with a wide range of balancing power and storage options to meet the flexible demands of the green ammonia production process at hourly time resolution over a year or more. Unlike existing models, the open-source implementation of our tool allows it to be used by a potentially wide range of stakeholders to explore their own projects and help guide the upscaling of green ammonia as a pathway for decarbonisation. Using Gladstone in Australia as a case study, a 1 million tonne per annum (MMTPA) green ammonia plant is modelled and costed using price assumptions for major equipment in 2030 provided by the Australian Energy Market Operator (AEMO). Using a hybrid (solar PV and wind) renewable energy source and Battery Energy Storage System as balancing technology, we estimate a levelized cost of ammonia (LCOA) between 0.69 and 0.92 USD kgNH3-1. While greater than historical ammonia production costs from natural gas, falling renewables costs and emission reduction imperatives suggest a major future role for green ammonia.

Liquid air energy storage for ancillary services in an integrated hybrid renewable system

High shares of intermittent renewable sources cause volatile frequency movements that could jeopardize the continuous operation of the grid. Liquid Air Energy Storage (LAES) is an emerging technology that not only helps with decarbonisation of energy sectors, but also has potentials for reliable ancillary services. In this paper, a hybrid LAES, wind turbine (WT), and battery energy storage system (BESS) is used to investigate their contributions in fast frequency control. The inertial control, droop control and combined inertial and droop terms are applied on each source of the hybrid renewable system and a comprehensive analysis is conducted to study their impacts on the frequency nadir improvement. The analysis shows that LAES with combined inertial and droop control terms along with inertial control of WT and BESS provide reliable frequency control. To further improve the frequency nadir, a Fuzzy control is proposed and applied on the LAES. The proposed control system provides a more adaptive performance against disturbances. Also, experimental tests are conducted to validate the proposed control method using a real-time hardware-in-the-loop test rig. The simulation and experimental results show that LAES in a hybrid renewable system can significantly contribute to the frequency control when variable gain control schemes are implemented.

A Multi-Objective Co-Design Optimization Framework for Grid-Connected Hybrid Battery Energy Storage Systems: Optimal Sizing and Selection of Technology

This paper develops a multi-objective co-design optimization framework for the optimal sizing and selection of battery and power electronics in hybrid battery energy storage systems (HBESSs) connected to the grid. The co-design optimization approach is crucial for such a complex system with coupled subcomponents. To this end, a nondominated sorting genetic algorithm (NSGA-II) is used for optimal sizing and selection of technologies in the design of the HBESS, considering design parameters such as cost, efficiency, and lifetime. The interoperable framework is applied considering three first-life battery cells and one second-life battery cell for forming two independent battery packs as a hybrid battery unit and considers two power conversion architectures for interfacing the hybrid battery unit to the grid with different power stages and levels of modularity. Finally, the globally best HBESS system obtained as the output of the framework is made up of LTO first-life and LFP second-life cells and enables a total cost of ownership (TCO) reduction of 29.6% compared to the baseline.