Battery Hybrid Energy Storage System Research Articles

Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm

The study addresses the integration of hybrid hydrogen (H2) and battery (BT) energy storage systems into a renewable energy microgrid comprising solar photovoltaic (PV) and wind turbine (WT) systems. The research problem focuses on improving the effectiveness and computational efficiency of energy management systems (EMS) while ensuring high system reliability. Despite the existing optimization methods for hybrid microgrids, challenges remain in optimizing energy storage and capacity planning in grid-connected microgrids. To solve this, we propose the use of the Levy Flight Algorithm (LFA) to optimize the capacities of PV, WT, H2 tanks, electrolyzers (EL), fuel cells (FC), and BT, which presents a complex nonlinear optimization challenge. The novelty of this study lies in integrating the LFA with a rule-based EMS, enhancing system reliability and efficiency. The proposed approach significantly reduces the annualized system cost (ASC) and the levelized cost of energy (LCOE). The result demonstrate that the LFA outperforms methods like the Salp Swarm Algorithm (SSA), Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Genetic Algorithm (GA), yielding cost savings of $3,309, $5,297, $4,484, and $5,129 respectively. The LFA achieves the lowest LCOE at $0.275/kWh, compared to $0.278/kWh with SSA, $0.289/kWh with GA, $0.280/kWh with PSO and $0.283/kWh with GWO. This research contributes to the broader scientific community by providing a more efficient approach to optimizing renewable energy microgrids with hybrid storage systems, thus promoting eco-friendly and cost-effective energy solutions. The proposed system design offers a pathway to future energy systems with high renewable integration, especially as technology advances and costs continue to decrease.

Towards standalone commercial buildings in the Mediterranean climate using a hybrid metal hydride and battery energy storage system

Given the critical role of hybrid energy storage systems in the building sector for enhancing renewable energy reliability and integration, this study examines the techno-economic feasibility of adopting a dual-level energy storage system for a PV-driven commercial building in the Mediterranean climate. The proposed system encompasses both hydrogen metal hydride and battery storage units. Aimed at off-grid electrification, the optimal component sizing of the hybrid system is identified by establishing a statistical optimization framework using the response surface methodology. Dynamic simulations of the hybrid system are performed through a TRNSYS model coupled with a numerical code that simulates the metal hydride system. Regarding optimal net-zero solutions, it is shown that the share of the direct PV electricity supply to end-use fluctuates within a limited range for all scenarios, namely between 57.7 and 60.5 %, while the share of each storage system varies distinctively in each solution. The results indicate a striking difference between scenarios in terms of economic aspects; differences of $ 19,791 and $ 32,621 are observed between the minimum and maximum values of the initial investment and life cycle cost, respectively. The levelized cost of electricity varies between 0.354 and 0.403 $/kWh, in which the case having the lowest payback period (10.8 years) demonstrates the lowest levelized cost of electricity too. Furthermore, an inverse relationship between the levelized cost of hydrogen and production rate is observed; the lowest levelized cost and the highest annual production are achieved in the scenario with the lowest BESS capacity and the highest electrolyzer power and hydrogen storage volume, which are equal to 5.77 $/kg and 304.7 kg H2/yr, respectively.

A hierarchical energy management strategy for DC microgrid hybrid energy storage systems based on fractional-order sliding mode controller

A hierarchical energy management strategy (EMS) for a fuel cell (FC)-supercapacitor (SC)‑lithium battery hybrid energy storage system (HESS), based on a fractional-order sliding mode controller (FOSMC), is proposed to address the nonlinear behavior of low-voltage direct current (DC) microgrid HESS. To fully exploit the energy of the SC, the system management layer divides the EMS into maximum power operation mode and state machine control algorithm operation mode. For the first time in equipment control layer, a FOSMC, more suitable for handling nonlinear characteristics, is employed, and its stability is evaluated using the Lyapunov method. Finally, a 48 V HESS experimental platform is constructed for validation, demonstrating that the proposed EMS enhances the stability, response speed, and robustness of the HESS. Compared to conventional sliding mode controller (SMC) and integral sliding mode controller (ISMC), the adoption of a FOSMC reduces the steady-state error of the bus voltage by at least 9.1 % and increases the response speed by at least 11.1 %, while exhibiting good robustness to external disturbances and uncertainties in controller parameters. This fills the current research gap in parameter robustness validation.

Planning a Hybrid Battery Energy Storage System for Supplying Electric Vehicle Charging Station Microgrids

This paper presents a capacity planning framework for a microgrid based on renewable energy sources and supported by a hybrid battery energy storage system which is composed of three different battery types, including lithium-ion (Li-ion), lead acid (LA), and second-life Li-ion batteries for supplying electric vehicle (EV) charging stations. The objective of this framework is to determine the optimal size for the wind generation systems, PV generation systems, and hybrid battery energy storage systems (HBESS) with the least cost. The framework is formulated as a mixed integer linear programming (MILP) problem, which incorporates constraints for battery ageing and the amount of unmet load for each year. The system uncertainties are managed by conducting the studies for various scenarios, generated and reduced by generative adversarial networks (GAN) and the k-means clustering algorithm for wind speed, global horizontal irradiation, and EV charging load. The studies are conducted for three levels of unmet load, and the outputs are compared for these reliability levels. The results indicate that the cost of hybrid energy storage is lower than individual battery technologies (21% compared to Li-ion, 4.6% compared to LA, and 6% compared to second-life Li-ion batteries). Additionally, by using HBESS, the capacity fade of LA batteries is decreased (for the unmet load levels of 0, 1%, 5%, 4.2%, 6.1%, and 9.7%, respectively), and the replacement of the system is deferred proportional to the degradation reduction.

Test of a YBCO thin film based over current limiter employed in battery unit of SMES-battery HESS during charging process

This paper proposes a novel over current protection strategy based on YBa2Cu3O7-x (YBCO) thin film current limiter, to improve the over current stability of the battery unit in superconducting magnetic energy storage (SMES)-battery hybrid energy storage system (HESS) during charging process. The conventional over current protection strategy for battery unit is based on cutting off the operation of the battery unit to remove the fault. Especially, during the charging process, once the battery unit circuit is cut off, the stability and reliability of the HESS will be also reduced. Hence, considering the features of the YBCO thin film in both superconducting state and quench state, it can be deployed as the over current limiter, to keep the stability of the battery unit against the over current fault during the charging process. In this paper, we designed and fabricated the YBCO thin film over current limiter, meanwhile, the preliminary verification experiment was carried out in our laboratory. It can be found from the experimental results that the over current in battery unit can be limited effectively by its quench resistance without cutting off the whole circuit. Besides, the charge voltage fluctuation of the battery unit can be also compensated by using the proposed protection strategy. Thus, the stability and reliability of the battery unit against the over current fault in charging process can be further improved.

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.