Hybrid Electrical Energy Storage System Research Articles

Мodelling of Passive Coupling of Battery Units of Hybrid Energy Storage System

Due to the development of electric transport and the growth of “green” energy, electric energy storage systems (ESS) are increasingly being used in the world. The growth of the battery market in the last decade has been 20-30%. One of the ways to increase the efficiency of an electric power storage device is its hybridization, i.e. the use of heterogeneous battery units. The paper examines the features of passive coupling of lead-acid and lithium-ion batteries in a hybrid storage device. A model is presented for calculating the electrical characteristics of these units during operation. The possibility of choosing a hybrid drive structure that provides a comparable operating voltage range of the units (operation without voltage converters) is demonstrated. The modes of operation of a hybrid energy storage system are modeled both for simple parallel connection and for switching blocks according to a threshold algorithm. It is demonstrated that in order to equalize the discharge rate of the main and additional units, it is necessary to coordinate the capacity of the ESS, the degree of hybridization, the type of load and the electrical parameters of the batteries, which is impossible without modeling the system. When the threshold switching of the blocks takes place, additional control parameters, making it possible to change the discharge rate of the additional block and increase the economic efficiency of the hybrid ESS. Estimates of the economic efficiency of hybrid ESSs have been made for different values of the threshold switching voltage of the lithium-ion unit, as well as for three characteristic loads: an electric forklift truck, a 30-apartment apartment building and a 300-apartment residential complex. The results demonstrate the features and technical and economic potential of passive hybridization, can be used for the design of hybrid ESSs for small power systems with solar and wind power plants, in the calculation and design of generator – storage – consumer systems.

Performance improvement of a standalone PV system using supercapacitors: modeling and energy management

Standalone photovoltaic (PV) systems are the most common and practical application in remote areas and communities far from the power grid. However, in the case of supplying a pulsating load with only a battery as a storage unit, their performance degraded. Therefore, hybrid electrical energy storage (HEES) systems represent a viable solution. This paper investigates the impact of utilizing a supercapacitor (SC) to work cooperatively with a battery storage unit to enhance the overall system behavior. Two scenarios of battery storage systems with/without SC are considered. A comprehensive modeling and sizing approach is established and presented in detail. Then, an energy management system (EMS) is proposed to enhance the HEES system’s performance. A proportional-integral (PI)-based controller is designed and examined to control the power electronic converters and hence improve energy management. The HEES system operation is simulated and evaluated using MATLAB/Simulink to feed a pulsating load, where the drawn pulsated load current is composed of two components: one component is supplied by battery, and the other component is fed from SC. Finally, the performance of the two hybrid configurations is evaluated in terms of battery voltage and current fluctuations, transient response, and load voltage and current ripples. The obtained results demonstrate the effectiveness of introducing SCs into HEES system.

Energy Management in Hybrid Electric and Hybrid Energy Storage System Vehicles: A Fuzzy Logic Controller Review

Energy Management in Hybrid Electric and Hybrid Energy Storage System Vehicles: A Fuzzy Logic Controller Review

Physical analysis of self-discharge mechanism for supercapacitor electrode for hybrid electric energy storage system

Self-discharge is a spontaneous process that has considerable adverse effects on the performance of supercapacitors. In order to quantitatively investigate the contribution of self-discharge mechanism, this paper proposed a theoretical self-discharge model for carbon electrode of supercapacitors based on electric double layer theory. Three physical contributions, i.e., side reactions, ion diffusion, and ohmic leakage, were investigated. In addition, self-discharge measurement of carbon electrode was performed to validate such theoretical model. The results indicated that the potential drop due to side reactions was negligible throughout the self-discharge process in all cases. In addition, ion diffusion dominated for low initial potential and short holding time, accounting for 50%–80% of self-discharge. On the other hand, ohmic leakage dominated for high initial potential and long holding time. Furthermore, the potential drop due to ion diffusion increased monotonously with time while the potential drop due to ohmic leakage remained constant throughout the self-discharge. Moreover, the potential drop due to ohmic leakage increased with the increase in holding time, which compensated for the decreasing potential drop due to ion diffusion. This could explain the fact that the total electrode potential decay during the self-discharge was independent of holding time. Finally, dimensional analysis was performed to predict self-discharge. Time constants of side reactions, ion diffusion, and ohmic leakage were derived. Overlapping dimensionless electrode potential versus dimensionless time indicated that such dimensional analysis was generally applicable to predict self-discharge of carbon-based supercapacitors at a given initial potential and time.

Impact of hybrid electrical energy storage system on realistic deregulated power system having large-scale renewable generation

Frequency stabilization in the deregulated power system (DPS) becomes more significant because of increased complexities and uncertainties due to higher penetration of renewable energy sources (RESs) among other operational challenges of the system. Variable generation due to RESs and frequent load deviations impact the supply and demand balance which causes huge frequency deviations in the system. The issues associated with the grid due to RES can be effectively tackled by maintaining power balance using different types of energy storage and advanced control mechanism. This article evaluates the suitability of hybrid electrical energy storage (HEES) and a novel (1 + TDF)-PI cascade controller to tackle the frequency regulation issues of the two-area DPS. The DPS has a power generation capacity of 2000 MW in each area integrated with RESssuch as geothermal power plant (GPP) and realistic dish-sterling solar thermal system (RDSTS). To resemble the practical operational situation of the DPS, several contract transaction scenarios and nonlinearities have been considered and examined. The HEES is a combination of a Super-Capacitor (SC) and redox flow battery (RFB). The SC is very fast responding and it can counter immediate variations in the power whereas, the RFB system can counter large variations of the power as needed in the system. The supremacy of the proposed controller has been confirmed by equating its performance with other well-known controllers. Compared to the state-of-the-art approaches, with the proposed controller smaller setting time has been achieved i.e. 10.72 s and 10.579 s for area-1 and area-2 frequency and 1.25 s for tie-lie power under the BBT scenario. Moreover, the system performances and capabilities to handle system nonlinearities have been prominently enriched due to precise control and a quick response provided through the proposed HEES.

Enhancing the Structural and Surface Properties of Ni-Rich LiNi0.91Co0.06Mn0.03O2 Ncm Cathode Material By Mg Doping and Li3PO4 Coating

The increasing demand of energy has surge the prices of fossil fuels. In addition, the CO2 emissions has increased exponentially which prompts the global warming [1]. Therefore, to cope-up these concerns clean alternative energy sources has been investigated, in which lithium-ion batteries (LIBs) has been focused due to their excellent rate capability, high discharge capacity and low cost [2]. The main components of LIBs are anode, cathode, electrolyte and separator. Cathode electrode plays an important role in determining the cost and energy density of the LIBs [3]. The Ni-rich NCM cathode materials are promising candidates for the electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs) and energy storage systems (ESS). Unfortunately, Ni-rich NCM suffers from continuous structural degradation which leads to the rapid capacity fading and rise in impedance during charge-discharge process [4]. In addition, the consumption of Li-ions for the solid electrolyte interphase severely damages the electrochemical performance of the LIBs [5]. Recently, an innovative approach has been introduced to resolve these issues. The one-step process stabilizes the crystal lattice and protects the active material from hostile attack of electrolyte. In this study, MgHPO4 has been utilized to modify the structural and surface properties of LiNi0.91Co0.06Mn0.03O2 NCM cathode material. The samples were characterized by SEM, XRD, XPS and Nano-SIMS. The electrochemical properties were measured by assembling the coin cells.The shifting of (003) diffraction peak to the low angle confirms the Mg doping. The peaks of Li3PO4 has been indexed which confirms that the NCM cathode material is coated with lithium phosphate. The presence of Mg and P is validated from the XPS results. SEM images confirms that the particles have sustain their original spherical morphology which confirms that the Mg doping has not increased the internal stresses. The 1 mol. % NCM samples shows the superior electrochemical properties due to optimized amount of dopant and coating.The Mg2+ provides the pillar effect in the Li-slabs which prevents the structural collapse during Li-ion de/intercalation. Li3PO4 coating inhibits the side reactions of active material with the electrolyte while keeping enabling the smooth Li-ion diffusion.

A Linear Recursive State of Power Estimation for Fusion Model Component Analysis with Constant Sampling Time

The state of power of lithium-ion batteries, as the main product of choice for electric and hybrid electric vehicle energy storage systems, is one of the precise feedback control parameters for the battery management system. The proposed research establishes a method for the analysis of charging and discharging constitutive factors under the sampling time, realizes the online identification of parameters by building an adaptive forgetting factor recursive least-squares method based on the Thevenin model, and uses the online parameters to achieve an effective characterization of the power state under voltage and current limitations. The results demonstrate that the accuracy error of online parameter identification is less than 0.03 V. Combining the analysis of charging and discharging constitutive factors under-sampling time with the fusion model of voltage and current limitation makes the power state estimation more reliable and accurate. The results demonstrate that the power state estimation error in the discharging state is less than 8%.

Thermodynamic Analysis of a Hybrid Electrical Energy Storage System Integrating High‐Temperature Thermal Energy Storage and Compressed Air Energy Storage for Mitigating Renewable Energy Curtailment

Compressed air energy storage (CAES) system can smooth out the fluctuated power from renewable energy and allow it to meet electricity demands reliably. It further enables the mitigation of renewable energy curtailment. A hybrid energy storage system integrating high‐temperature thermal energy storage (HTTES) and CAES is proposed. In the energy charging process, the high‐ and low‐quality power from renewable energy are stored separately in the air storage reservoir (ASR) and HTTES system. In the energy discharging process, the compressed air is heated to high temperature in the HTTES system and finally expands in air turbines for electricity generation. Thermodynamic analysis reveals that a round trip efficiency of 64.36% with an energy storage density of 5.38 kWh m−3 can be achieved. It is found that the proposed hybrid system has the beneficial effect of improving the system performance. The largest exergy destruction takes place in the HTTES system. The round trip efficiency is mostly sensitive to the output temperature of HTTES, the isentropic efficiency of compressors and turbines, and the maximum and minimum operating pressures of ASR.

A data-mining based optimal demand response program for smart home with energy storages and electric vehicles

In recent years, modern appliances with high electricity demand have played a significant role in residential energy consumption. Despite the positive impact of these appliances on the quality of life, they suffer from major drawbacks, such as serious environmental concerns and high electricity bills. This paper introduces a consolidated framework of load management to alleviate those drawbacks. Initially, benefiting from a demonstrative analysis of home energy consumption data, controllable and responsive appliances in smart home are identified. Then, the energy consumption pattern is reduced and shifted using flexible load models and better utilization of existing energy storage systems. This can be achieved through data mining approaches, i.e., density-based spatial clustering of application with noise (DBSCAN) method. In this technique, no sensor for detection or measurement instruments will be required, whose deployment incur cost to the system or increase security risk for consumers. In the following, one scheduling of using controllable appliances, which is formulated by convex optimization, is considered for the demand response (DR) program, provided that this plan doesn't affect customers’ priority and convenience. In the last stage, the deployment of energy storage systems, such as plug-in hybrid electric vehicles (PHEVs) and battery energy storage systems (BESS), is introduced to lower the energy cost and improve the performance of the proposed DR model. Simulation results of this demand response are compared with conventional k-clustering methods to confirm the economic superiority of the DBSCAN clustering technique using the data of a residential unit during three different scenarios.

An Improved SOC Control Strategy for Electric Vehicle Hybrid Energy Storage Systems

In this paper, we propose an optimized power distribution method for hybrid electric energy storage systems for electric vehicles (EVs). The hybrid energy storage system (HESS) uses two isolated soft-switching symmetrical half-bridge bidirectional converters connected to the battery and supercapacitor (SC) as a composite structure of the protection structure. The bidirectional converter can precisely control the charge and discharge of the SC and battery. Spiral wound SCs with mesoporous carbon electrodes are used as the energy storage units of EVs. Under the 1050 operating conditions of the EV driving cycle, the SC acts as a “peak load transfer” with a charge and discharge current of 2isc~3ibat. An improved energy allocation strategy under state of charge (SOC) control is proposed, that enables SC to charge and discharge with a peak current of approximately 4ibat. Compared with the pure battery mode, the acceleration performance of the EV is improved by approximately 50%, and the energy loss is reduced by approximately 69%. This strategy accommodates different types of load curves, and helps improve the energy utilization rate and reduce the battery aging effect.

Preface

After successfully held for two consecutive year, 2020 3rd International Conference on Green Buildings and Environmental Management (GBEM 2020) continued to be held on June 12 this year. Despite the impact of COVID-19 and worldwide travel restriction, GBEM 2020 continued to be carried out under the enthusiastic participation of scholars without postponing the original schedule by conducting the form of virtual conference to avoid personnel gatherings. GBEM 2020 aims to provide a flexible platform for the experts and scholars in the field of Green Buildings and Environmental Management to present and disseminate the state-of-the-art research, share the latest trends, and promote the cooperation between each other.The committee of GBEM 2020 was composed of over seventy experts. With such profound academic influence, GBEM 2020 attracted over 100 persons to join the online meeting. The conference model was divided into two parts, including keynote presentations and online discussion. In the first part, each keynote speakers were allocated 30 minutes to present their talks via Zoom. After the keynote talks, all participants joined in a WeChat communication group to discuss more about the talks and presentations. We are honored to have invited five distinguished experts as our keynote speakers. Dr. Jinfeng Zhou, Secretary General of China Biodiversity Conservation and Green Development Foundation, was the first one to perform a thought-provoking speech on why Green Engineering Needs to Fundamentally Solve the Problem of Green Thinking Deficiency. Secondly, Prof. Hongxing Yang from Hong Kong Polytechnic University held his speech on Design optimization of hybrid renewable energy and electrical energy storage systems for power supply to buildings. Thirdly, Prof. Hamidi Abdul Aziz from Universiti Sains Malaysia talked about Sustainable solid waste disposal for developing countries: A journey to sanitary landfilling. Then we had Prof. Mohan Kolhe, representing University of Agder, Norway, whose speech is about Implementation of Demand Response Program in Residential Households (EU FP7 Project ‘Scalable Energy Management Infrastructure for Aggregation of Household’SEMIAH). Last but not least, Prof. Ismael Guerrero Arias from Loyola University of Spain discussed his research on Potential of unsubsidized solar energy and energy storage. Their insightful speeches had triggered heated discussion in the second session of the conference. The WeChat discussion lasted for about 30 minutes. Every participant praised this conference for disseminating useful and insightful knowledge.We are glad to share with you that we still received lots of submissions from the conference during this special period. Hence, we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following three categories but are not limited to: Green Building, Structures and Civil Engineering, Environment Management, and other related fields. All the papers have been through rigorous review and process to meet the requirements of International publication standard.We would like to express our sincere gratitude to the committee members, the distinguished keynote speakers, as well as all the participants. We also want to thank the publisher for publishing the proceedings. May the readers could enjoy the gain some valuable knowledge from it. We are expecting more and more experts and scholars from all over the world to join this international event next year.Committee member, Committee are available in the pdf.

The Use of Hybrid Energy Storage Devices for Balancing the Electricity Load Profile of Enterprises

In this article, the authors consider the possibility of using a hybrid energy storage system to even out the load profile of the enterprise. Solving the problem of rational use of energy storage taking into account the initial variable load schedule will significantly reduce not only the cost of electricity consumption by the enterprise, but also the costs of its production. Detailed characteristics of batteries with various types of electrolytes and supercapacitors are given. A model of the active scheme of a hybrid electric energy storage system consisting of a lithium-ion battery and a supercapacitor unit with the corresponding characteristics is presented. The model was carried out by using the SimPowerSystems software in MatLab. During the simulation, the temperature and the aging effects and of the batteries were not taken into account. The selfdischarge parameter of the battery was also not presented. As a result of the simulation, discharge characteristics of supercapacitors and batteries were obtained based upon which the expediency of their combined use for leveling load profiles of various types was substantiated. The paper presents the results of the simulation of operating modes of a hybrid energy storage device, combining the advantages of two types of energy storage devices, as well as a diagram of delivered power to the network, corresponding to the specified parameters. The paper provides a mathematical description of the increasing power by hybrid storage system resulting from the combined use of supercapacitors and batteries. The paper presents the dependence of the power increase ratio on the frequency and the pulse current duty ratio, which proves that the maximum possible output power of the hybrid storage system can be several times greater than the power of a single battery having the same parameters.

Identification of parameters for the hybrid electrical energy storage system in autonomous power system

The article describes the approach to the selection of parameters of a hybrid electrical energy storage system (EESS) based on supercapacitors (SC) and lithium ion battery (LIB) for an autonomous power station with a diesel generator set (DGS). The calculations of transients in an autonomous power supply system with an abruptly variable load and participation of a hybrid EESS. The procedure of determining the share of participation in the energy exchange of storage subsystems based on LIB and SC is presented.

Thermal and economic analysis of hybrid energy storage system based on lithium-ion battery and supercapacitor for electric vehicle application

A hybrid electrical energy storage system (EESS) consisting of supercapacitor (SC) in combination with lithium-ion (Li-ion) battery has been studied through theoretical simulation and experiments to address thermal runaway in an electric vehicle. In theoretical simulation, the working temperature of Li-ion battery and SC has been varied from 0 to 75 °C in steps of 25 °C and the effect of the variation is observed on the output current, voltage and power of Li-ion battery and SC for a calculated load using the standard driving cycle. Further, electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) have been performed to investigate the effect of temperature on SC. EIS measurements of SC indicate a low equivalent series resistance of 0.095 Ω at 25 °C. CV measurements indicate a high value of capacitance of 56.65 F/g at 25 °C for a scan rate of 5 mV s−1. Through theoretical simulation of EESS, a temperature increase ( $$ \Delta T $$ ) of 0.41 °C is calculated considering an initial peak of 10-s duration for the case of EESS without SC, whereas the use of SC reduces $$ \Delta T $$ to 0.025 °C. Further, optimal size calculation for hybrid EESS is done to achieve the least cost, wherein Li-ion battery capacity has been varied from 0 to 200 Ah and the SC capacity has been varied from 0 to 5 F in MATLAB simulation. The optimal combination is obtained as 30 Ah capacity of Li-ion battery and 3 F capacity of SC by connecting load across hybrid EESS for a duration of 3600 s.

Optimal operation of hybrid electrical and thermal energy storage systems under uncertain loading condition

This paper presents a hybrid model of an energy storage system including thermal and electrical energy storage systems in the building with thermal and electrical loads. Building receives its energy from electrical grid and purpose is to reduce the daily energy cost by optimal operation of hybrid energy storage system. Load forecast error is included as uncertainty and both thermal and electrical loads are modeled by Gaussian probability distribution function. The proposed problem for optimal cooperation of hybrid thermal-electrical storage systems is mathematically expressed as mixed integer binary linear programming. The scenario-based stochastic modelling is also included to deal with uncertainty in loading. The expressed stochastic optimization programming minimizes the daily energy cost in building and determines the optimal charging-discharging pattern for both thermal and electrical storage systems at the same time. The results demonstrate that electrical energy storage system reduces the cost about 15%, the thermal energy storage system decreases the cost about 17%, and coordinated thermal-electrical energy storage system reduces the cost about 34%. As a result, the best operation is achieved by the coordinated thermal-electrical energy storage system.

Stochastic multi-objective energy management in residential microgrids with combined cooling, heating, and power units considering battery energy storage systems and plug-in hybrid electric vehicles

Abstract Governmental incentives to use clean energy, concerns about high and rising prices of fossil fuels, and environmental issues are the most important motivations for adding distributed energy resources to conventional power systems. In these circumstances, new technologies such as combined cooling, heating, and power systems, energy storage systems including battery and thermal storages, and plug-in hybrid electric vehicles not only can improve system efficiency but also can reduce operation and investment cost as well as emissions. In this paper, a residential microgrid consisting of combined cooling, heating and power, plug-in hybrid electric vehicles, photovoltaic unit, and battery energy storage systems is modeled to obtain the optimal scheduling state of these units by taking into account the uncertainty of distributed energy resources. To achieve this goal, a scenario-based method is used to model uncertainties of electrical market price, electrical and thermal demand, and solar irradiance using Normal, Weibull, and Beta probability distribution functions, respectively. The scenario tree is used to generate scenarios and representative scenarios are selected with scenario reduction techniques. The proposed problem is formulated as a mixed-integer nonlinear programming to minimize objectives of operation cost and total emissions. This multi-objective problem is solved by the Augmented ɛ-constraint method and the best solution on the Pareto front set is determined by a fuzzy approach. In order to maintain system reliability during on-peak periods, the time-of-use demand response program is considered to promote a change in energy consumption patterns. Finally, plug-in hybrid electric vehicles are considered as electrical energy storage instead of batteries in optimal energy and emissions management. Proposed energy management is applied on a residential microgrid and the effectiveness of the model is verified. It is found that uncertainties increase the cost by 12.2%; however, energy storage systems reduce cost and emissions by 4.7% and 23%, respectively.

Load serving entity interactions on residential energy management strategy: A two-level approach

A massive motivation has been made on in-home energy management (iHEM) strategies aimed to cooperate with each other in integrated residential areas. Such an approach could make sense in satisfying the objectives of load serving entity (LSE), too. To make such concepts, residential energy management (REM) approach, in interaction with LSE, is proposed pursuing two objectives. The main goal of these objectives is to modify microgrid day-ahead load profile by considering the minimized total daily energy costs of homes. In this regard, in the first level, the objective pursues a minimum energy cost for each home. In the second level, the minimum load profile deviation for microgrid is tracked. Moreover, the obtained homes minimum costs which are achieved in the first level are assigned as running constraints of the second level optimization. In the present study, in addition to existing fixed-loads, iHEM systems are responsible for adjusting shiftable appliances commitment, charging/discharging intervals of plug-in hybrid electric vehicles (PHEVs) and energy storage systems (ESSs), and roof-top photovoltaic (PV) panels. Efficient linearization methods are considered to avert non-linear nature of the established model to a linear one. To investigate the efficiency of the proposed approach, the obtained simulation results are explored carefully.

Optimal Operation of Electric Railways With Renewable Energy and Electric Storage Systems

This paper proposes a methodology for optimal operation of railway electric energy systems considering renewable energy sources (PV panels and wind turbines), regenerative braking capabilities and hybrid electric energy storage systems (ultracapacitors and batteries). The uncertainties associated to renewable energies are taken into account through a scenario tree approach. All these elements are integrated into a multi-period AC optimal power flow problem. This problem is then cast as a large-scale nonlinear optimization problem. The aim is to study the potential for energy and economic savings of the railway operation as well as energy storage systems behavior. A real case study is analyzed for a Spanish high-speed railway line. Results are reported for several cases comparing four different operation modes.

Coordinated PHEV, PV, and ESS for Microgrid Frequency Regulation Using Centralized Model Predictive Control Considering Variation of PHEV Number

The integration of plug-in hybrid electric vehicles (PHEVs), photovoltaic (PV) generators, and energy storage systems (ESSs) into microgrids is highly anticipated. A coordinated control of PHEVs, PVs, and ESS will support frequency control in a microgrid. However, the size of the ESS depends on the surplus power of PV. The lower the surplus power is, the smaller the size of ESS. Furthermore, the number of available PHEVs vary with the cumulative number of the participating PHEVs. This variation of the number of PHEVs may reduce the PHEVs’ control effect in the microgrid. This paper proposes a coordinated control of PHEVs, PVs, and ESSs for frequency control in the microgrid using a centralized model predictive control (CMPC) considering the variation of PHEV numbers. The objectives of the coordinated control are: 1) to suppress the system frequency fluctuation and 2) to minimize the surplus power of PV and, therefore, reduce the size of ESS. Simulation studies indicate that the coordinated control of PHEVs, PVs, and ESSs by the proposed CMPC is superior to that of the proportional integral derivative control and the distributed MPC in terms of minimizing the frequency fluctuation, the PV surplus power, and the ESS size.

Frequency Power Sharing for Battery/Supercapacitors Hybrid Energy Storage System in Electric Vehicles

Battery/Supercapacitors combination offers superior performances for a hybrid electric energy storage system in Electric Vehicles. This paper, presents a frequency power sharing strategy to get the best use of complementarity between battery and supercapacitors. Storage devices are sized based on reduced scale specifications for the studied EV. Power and current waveform simulation results are shown for each storage device due to the use of a frequency power sharing policy. Various power split configurations are analyzed to study their effect on battery current waveforms. Optimal frequency sharing policy for the battery/SCs hybrid reducing RMS battery current is obtained. The best use of battery/SCs association provides significant improvements of Electric Vehicle performances in terms of battery lifetime and amortized cost.