Battery Hybrid Energy Storage System Research Articles

Hybrid improved Sparrow Search Algorithm and sequential quadratic programming for solving the cost minimization of a hybrid photovoltaic, diesel generator, and battery energy storage system

ABSTRACT In this paper, a hybrid photovoltaic/battery/diesel generator power generation system is designed and optimized to power a network of a remote village in China. The purpose of the system designed here is to lessen the fuel costs of the system dependent on the load demand and some constraints. Therefore, the idea comprises an optimization problem that is solved here based on a new optimization policy by an Improved design of Sparrow Search Algorithm (imSSA) and the Sequential Quadratic Programming (SQP). The results of the proposed method are analyzed in different seasons and also on weekdays and weekends to show their effect on the operational cost of the PV/Diesel BESS system. Final results indicate that in both winter and summer, the weekday costs are lesser than weekend fuel costs. Furthermore, the summer fuel cost is lesser than the winter fuel costs which is because of lesser demand in summer and the higher levels of summer radiation imply less usage of auxiliary origins. The results show that at the weekends cost more than the weekday. For instance, for the proposed mode, the winter weekends and the weekdays’ costs are US$12.1 and US$10.2, respectively, or the summer weekends and the weekdays’ costs are US$7.3 andUS$5.7, respectively.

Robust Partial Feedback Linearized Controller Design for Standalone Hybrid PV-BES System

This paper presents a mixed-sensitivity-based robust H∞ loop-shaping partial feedback linearized control scheme to enhance the transient stability of a battery energy storage-associated standalone solar photovoltaic system. The proposed control scheme has been provided independent operating points for a generalized nonlinear dynamical model of DC microgrids connected standalone hybrid solar photovoltaic and battery energy storage system. A parametric uncertainty model is developed for the generalized dynamical model, and the noise disengaging merit of the proposed control technique has been investigated. The designed controller’s performance has been demonstrated under four different scenarios, and it is compared with the conventional PI controller for partial feedback linearized control law.

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.

Decentralised control strategy for hybrid battery energy storage system with considering dynamical state‐of‐charge regulation

Hybrid battery energy storage system (HBESS) consists of high power density battery and high energy density battery will have a bright future in special isolated DC microgrid conditions such as the all-electric ships and all-electric airplanes, which have strict limitation on storage capacity and size. In this study, a new decentralised control strategy based on mixed droop is proposed to HBESSs with considering the batteries. In decentralised control strategy, conventional V–I droop controller is utilised to high energy density battery to mainly supply the steady power, I–V droop controller is utilised to high power density battery to respond to power change and supply a few steady power. In addition, dynamical state-of-charge (SoC) regulation algorithm is utilised to reassign the battery power according to their own SoC. The power coordination of the high energy density batteries and high discharge rate batteries is achieved by adjusting the values virtual impedance and reference input voltage. Case study shows that the proposed control strategy is flexible and efficient.

Research and implementation of new-type supercapacitor and battery hybrid energy storage system

When a dump truck brakes, it is difficult to effectively absorb the braking energy due to the transient mutation of braking energy. At the same time, braking energy production is too high to store easily. Focusing on these problems, this paper proposes a new type of two-stage series supercapacitor and battery (SP&B) hybrid energy storage system (ESS). Using the characteristics of supercapacitors, which can charge and discharge quickly with large currents, the system combines the supercapacitors with a battery with a high energy storage capacity. This allows sudden large currents to be absorbed and released rapidly, while large amounts of energy can be stored. This system can also reduce the charge and discharge times of the SP&B to meet the working requirements of dump truck braking while improving the service life of the system. After completion of the research and implementation of the proposed SP&B hybrid ESS, a laboratory dynamic model was set up as an experimental platform and vehicle operation experiments were performed. The obtained results show that the energy recovery efficiency of the hybrid ESS can reach 53.5%, which can realize both security and stability for dump truck braking energy recovery and utilization (BER&U) systems.

RETRACTED ARTICLE: Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems

Microgrid with hybrid renewable energy sources is a promising solution where the distribution network expansion is unfeasible or not economical. Integration of renewable energy sources provides energy security, substantial cost savings and reduction in greenhouse gas emissions, enabling nation to meet emission targets. Microgrid energy management is a challenging task for microgrid operator (MGO) for optimal energy utilization in microgrid with penetration of renewable energy sources, energy storage devices and demand response. In this paper, optimal energy dispatch strategy is established for grid connected and standalone microgrids integrated with photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), diesel generator (DG) and battery energy storage system (ESS). Techno-economic benefits are demonstrated for the hybrid power system. So far, microgrid energy management problem has been addressed with the aim of minimizing operating cost only. However, the issues of power losses and environment i.e., emission-related objectives need to be addressed for effective energy management of microgrid system. In this paper, microgrid energy management (MGEM) is formulated as mixed-integer linear programming and a new multi-objective solution is proposed for MGEM along with demand response program. Demand response is included in the optimization problem to demonstrate it’s impact on optimal energy dispatch and techno-commercial benefits. Fuzzy interface has been developed for optimal scheduling of ESS. Simulation results are obtained for the optimal capacity of PV, WT, DG, MT, FC, converter, BES, charging/discharging scheduling, state of charge of battery, power exchange with grid, annual net present cost, cost of energy, initial cost, operational cost, fuel cost and penalty of greenhouse gases emissions. The results show that CO2 emissions in standalone hybrid microgrid system is reduced by 51.60% compared to traditional system with grid only. Simulation results obtained with the proposed method is compared with various evolutionary algorithms to verify it’s effectiveness.

Model Predictive Control Method of hybrid Battery energy storage system for Smoothing Wind Power Fluctuation

In a large-scale wind power generation system, active power fluctuation caused by random wind speed will have a serious impact on the power grid. In order to limit the power fluctuation that wind farm transmits to the power grid and protect the energy storage battery, this paper has proposed a model predictive control method of hybrid energy storage by optimizing the objective function and constraint conditions. Firstly, the mathematical model of predictive control method has been established in a wind power system with hybrid energy storage. Then, with the goal of minimum energy storage output and maximum charging-discharging capacity of the super-capacitor, the predictive control process has been optimized. Meanwhile, the constraint on the output power of the battery has been dynamically changed to reduce its charging-discharging switching frequency, and the model predictive control strategy of the hybrid energy storage has been formed. Finally, compared with the model prediction control method of single energy storage, based on a wind farm data, the simulation results show that the proposed method can smooth wind power fluctuation, reduce the time that the power does not satisfy the fluctuation requirements, ensure the capability of the super-capacitor, and reduce the charging-discharging switching frequency of the energy storage battery.

Exploration and Verification Analysis of YBCO Thin Film in Improvement of Overcurrent Stability for a Battery Unit in a SMES-Battery HESS

This article puts forward a method based on high-temperature superconducting (HTS) current limiting technology, to improve the overcurrent stability for a battery unit in a superconducting magnetic energy storage (SMES)-battery hybrid energy storage systems (HESS). In contrast to supercapacitors, flywheels and other energy storage systems, SMES-battery HESS possess the technical properties of power capacity, energy, and response speed, among others. Thus, SMES-battery HESS may be utilized to handle power swing, energy transfer, voltage fluctuation, and related transient stability issues. But an overcurrent in a battery unit is harm to its cycle life of the battery. Hence, the internal protection system of the battery unit is used to remove a fault by cutting off its outputs. In this article, a YBa 2 Cu 3 O 7-X (YBCO) thin film is employed as the protection device to limit the overcurrent in a battery unit. In normal operation, the thin film is in the superconducting state, and its influence on the system can be ignored. An overcurrent will be limited evidently lower than the action threshold of the internal protection system by the quench resistance of the thin film. Therefore, the whole outputs of a battery unit will not be interrupted and restarted. Through the verification experiment carried out in our laboratory, the proposed protection method operated as expected, and the stability, as well as the reliability of the battery unit, could be improved.

Enhanced control strategies for a hybrid battery/photovoltaic system using FGS-PID in grid-connected mode

This paper suggests improved control strategies using Fuzzy Gain Scheduling of Proportional-Integral-Derivative (FGS-PID) controller for a hybrid Photovoltaic (PV) and Battery Energy Storage (BES) system under different weather conditions. The proposed scheme is implemented using a two-level control system structure, combining the benefits of the PID as well as the fuzzy logic controller (FLC) for maximum power point tracking (MPPT). Ziegler-Nichols tuning method is also employed to select the initial values of PID gains. Within the period of steady-states and transients, FGS-PID adopts the gains to ensure the stability of the control scheme. It also damps out transient fluctuations and reduces settling time. Also, BES could be employed to provide a stable and reliable power from the output of PV sources to loads. It can enhance the performance of the entire power system during the grid-connected mode. The simulation results under Matlab/Simulink show that the suggested control strategies are robustness, fast transient response and proper steady-state performance in the grid-connected mode in comparison other presented methods.

Real-Time Simulation of Smart DC Microgrid with Decentralized Control System Under Source Disturbances

Decentralized control of DC microgrid (dcµG) using hybrid renewable energy sources (RES) and battery energy storage system (BESS) which operate with and without grid-connected mode is proposed in this paper. In dcµG integrated with multiple RES and BESS, fluctuating output characteristics of the distributed generations (DGs) due to changing input conditions and the dynamic interactions of the source and load interface converters are main factors which cause stability problem of DC bus voltage. Thus, to solve this problem, the decentralized control scheme which uses bus voltage level as communication link in the control law is proposed in this paper. Accordingly, the control method realizes different operating modes based on the available generations and load demand. Maximum power and constant voltage controls schemes are applied in the DGs interfacing control to regulate the power and voltage variations due to changing input conditions. Furthermore, in the control strategy, the source and battery interfacing converters are controlled autonomously using the bus voltage level without any communication. This maintains the reliability and flexibility of the system. The proposed system model is developed with Matlab/Simulink SimPowerSystem and simulated with real-time simulation using OPAL-RT.

A Hybrid MMC-Based Photovoltaic and Battery Energy Storage System

This paper proposes a new configuration and its control strategy for a modular multilevel converter (MMC)-based photovoltaic (PV)-battery energy storage (BES) system. In the MMC-based PV-BES system, each PV submodule is interfaced from its dc side with multiple PV generators using isolated dual active bridge (DAB) dc–dc converters. One BES system is embedded into each arm of the converter and is connected to the dc port of the associated BES submodule using multiple isolated DAB converters. The embedded BES systems are used to smooth the output power of the PV generators and limit the rate of change of the power delivered to the host grid. Moreover, they enable compensation of power mismatches between the arms and legs of the system by exchanging power with the arms of the converter. This paper then proposes a hybrid power mismatch elimination strategy using a combination of power exchange with the arms of the converter and internal power flow control of the MMC. The proposed hybrid power mismatch elimination strategy employs BES systems and differential currents to compensate power mismatches and transfer power between the arms and legs of the converter, respectively. The effectiveness of the proposed power smoothing technique using the embedded BES systems and hybrid power mismatch elimination strategy is demonstrated using time-domain simulations conducted on a switched model of the PV-BES system in PSCAD/EMTDC software environment.

Sizing and operation of hybrid energy storage systems to perform ramp-rate control in PV power plants

This paper proposes a methodology for optimal sizing of a Hybrid (battery and ultracapacitors) Energy Storage system for ramp-rate control in PV plants. Frequency stability events can appear in power systems high non-dispatchable renewable energy generation due to sharp power output fluctuations. This has caused TSOs in several countries to require PV and wind plants to implement some method for limiting the pace at which the power injection to the grid is allowed to vary (ramp-rate control). Due to its quick response, properly controlled energy storage consisting of batteries and ultracapacitors can perform this task by dampening quick increases/decreases in the power injection to the grid by absorbing/injecting power at the point of common coupling.In this work, a techno-economic model is presented that can be used to calculate the Net Present Cost over the project life of different energy storage devices used for ramp-rate control by simulating their operation. A real case is studied for a PV power plant is presented. Results are reported comparing different configurations of the energy storage system.

Improved coordinated control strategy of hybrid energy storages in PV Power Smoothing

High penetration of renewable energy could causes system frequency fluctuation of power flow and this significantly affects the power system operation. Control strategy of Flywheel and lithium battery hybrid energy storage system (HESS) is designed in this paper. An improved energy allocation strategy of grid-connected PV power smoothing strategy is designed. Coordinated control strategy is added to avoid the power output direction inconsistent of two kinds of storage, and consider energy storage SOC level simultaneously. This strategy effectively reduces the number of charge and discharge cycles of energy storage system(ESS). The strategy is applied to a demonstration project. Results show that the proposed coordinated control strategy can improve the life expectancy of the battery and reduce the operating cost.

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.

A SC/battery Hybrid Energy Storage System in the Microgrid

The major challenges in power systems are driven by the energy shortage and environmental concerns, namely facilitating the penetration of renewable energy and improving the efficiency of the renewable powers. Due to the variable nature of renewables, the generated power profile may not be able to match the load requirement. Accordingly, much attention has been focused on the development of energy storage technologies to guarantee renewable power penetrations. Recently, advances in the supercapacitor (SC) have made the SC and battery hybrid energy storage systems (HESS) technically attractive. Compared with other energy storage technologies the principal advantages of SC are: the high power density, high cycling life, and high peak current handling capacities. However, SC is also deficient in low energy density. The battery is characterised by large energy density but low in power capacity. In the microgrid systems, high-frequency power fluctuations will cause a significant degree of battery power cycling. This, in turn, has been shown to lead to a significant reduction in battery service life. Therefore, the concept of the SC and battery hybrid scheme is proposed. A case study of the HESS based on a microgrid is introduced in this paper. A simplified microgrid system is established to test the performance of the proposed design.

A New State-of-Charge Control Derivation Method for Hybrid Battery Type Integration

The hybrid of ex-transportation and conventional new battery system integration has started gaining interests within energy storage systems as number of electric vehicle on-road increases. Each module within such a system may consist of batteries with different charging/discharging rates, characteristics and also different nominal voltage levels. Control of these hybrid batteries within the same system is more challenging compared to conventional battery management systems, which mainly deal with the homogeneous battery system. One of the key issues is how to control the state-of-charge trajectory of the hybrid modules to maximize the investment on the new hybrid battery system. To cater this problem, this paper brings a new rigorous derivation method of state-of-charge control based on converter sample time. The proposed method generates desired current reference in each time step to distribute the power among hybrid modules such that their discharging or charging trajectories finish at the same time. This technique makes sure that the energy delivered/absorbed from each cell in a uniform manner maximizing the overall lifespan. Detailed derivation of the current sharing method and suitable module based adaptive bidirectional control architecture has also been presented. Modeling, analysis, and experimental validations are performed on a three-module-based grid-tie hybrid battery energy storage system prototype to validate analysis.

Analysis and Design of Second-life Hybrid Battery Energy Storage System Based on Novel Modular Cascaded Dual-buck DC Converter for Photovoltaic System

A novel modular cascaded dual-buck DC converter which can be applied in Second-Life Hybrid Battery Energy Storage System is proposed. In order to suitably integrate and control these widely different batteries, a suitable multi-modular converter topology is required. A new type of boost converter is proposed, on the front end of each module. It is adapted to the working conditions of various second-life batteries, and it can be used as equipment and the interface of those batteries. The novel proposed boost converter has a higher efficiency compared with the traditional boost converter. The cascaded dual-buck DC converter has been used in this paper. This converter can flexibly connect each module and improve the output voltage. A brief discussion of the general operating principle of the topology is given. Therewith, the advantages of the structure compared with the conventional DC converter are introduced. Finally, simulation with 5kW system is given to prove the theoretical analysis and simulating feasibility of the proposed DC converter.

A New Design of Fuzzy Logic Control for SMES and Battery Hybrid Storage System

In this paper, the superconducting magnetic energy storage (SMES) and battery hybrid energy storage system has been designed to deal with high fluctuating power demand due to their complementary advantage. A lot of researchers are focusing on using battery technology to deal with low frequency demand and using SMES to deal with the remaining power demand. In this paper, a new energy management control method using 3 input parameters to a fuzzy logic controller is firstly proposed to deal with high fluctuating power demands. An example data processing result is shown in this paper. The results show that the hybrid storage system which applied fuzzy logic control has more flat battery charging/discharging current than an equivalent filtration control method. The low fluctuating battery demand is ideal for extending battery lifetime. Furthermore, the fuzzy logic controller can automatically adapt to the size of the SMES system by applying the state of the charge (SOC) of SMES as an input parameter to the fuzzy logic control.

A Novel use of the Hybrid Energy Storage System for Primary Frequency Control in a Microgrid

High penetration of renewable energycauses fluctuationsof power flow and results in system frequency fluctuation, which significantlyaffects the power system operation. The situation in microgrid (MG) is worse because of the low inertia and small time constant of the system. This paper present a novel use ofthesuperconducting magnetic energy storage (SMES) and battery hybrid energy storage system with the function of frequency control in the MG.A hybrid power management strategy for the SMES and the battery is used to achieve, firstly, a faster primary frequencycontroland secondly, an improvement of battery service time.

Ultracapacitor-Battery Hybrid Energy Storage System Based on the Asymmetric Bidirectional <italic>Z </italic>-Source Topology for EV

This paper proposes an ultracapacitor (UC)-battery hybrid energy storage system (HESS) for electric vehicle based on asymmetric bidirectional Z -source topology. Compared with the conventional two-stage design, the HESS can be incorporated into the traction inverter system, leading to better performance and lower cost. The UC energy can be effectively utilized due to the buck/boost characteristic in the Z -source converter; meanwhile, the battery converter gets eliminated in this case. The assumption about the symmetry in the Z -source topology impendence network states for the conventional analysis no longer applies to the proposed HESS configuration. The asymmetric characteristic related with the uneven power distribution of UCs and battery is mathematically excavated in detail. The frequency dividing coordinated control is proposed to exploit the advantages of UCs and battery. The battery peak current estimation is then investigated. Finally, the steady performance and transient response in both traction and regenerative modes are verified by simulation and experimental results.