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19 pages, 4952 KiB

Open AccessArticle

New Class of Power Converter for Performing the Multiple Operations in a Single Converter: Universal Power Converter

by Dhananjaya Mudadla, Devendra Potnuru, Raavi Satish, Almoataz Y. Abdelaziz and Adel El-Shahat

Energies 2022, 15(17), 6293; https://doi.org/10.3390/en15176293 - 29 Aug 2022

Cited by 1 | Viewed by 1252

Abstract

Universal power converters (UPCs) have aroused significant attention in performing multiple operations in a single power converter. Furthermore, they contribute to economic operation and improved system performance. In this work, a new configuration of the universal power converter (UPC) was proposed by using [...] Read more.

Universal power converters (UPCs) have aroused significant attention in performing multiple operations in a single power converter. Furthermore, they contribute to economic operation and improved system performance. In this work, a new configuration of the universal power converter (UPC) was proposed by using a simple switching arrangement. It can perform different modes of operations, such as AC–DC, DC–DC, DC–AC, AC–AC, and cyclo-converter operations. In DC–DC conversion, the proposed configuration can perform buck mode, boost mode, and buck–boost mode of operations. Moreover, in DC–AC conversion, it gives better total harmonic distortion (THD). The effectiveness of the proposed configuration was verified by an extensive simulation, using MATLAB/Simulink environment. A low-power prototype circuit was designed to test the viability of the proposed circuit configuration and validated with simulation results. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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21 pages, 10593 KiB

Open AccessArticle

DE-Algorithm-Optimized Fuzzy-PID Controller for AGC of Integrated Multi Area Power System with HVDC Link

by Solomon Feleke, Raavi Satish, Workagegn Tatek, Almoataz Y. Abdelaziz and Adel El-Shahat

Energies 2022, 15(17), 6174; https://doi.org/10.3390/en15176174 - 25 Aug 2022

Cited by 6 | Viewed by 1185

Abstract

A power system’s nonlinearity and complexity increase from time to time due to increases of power demand. Therefore, properly designed power system controlsare required. Without these, system instability will cause equipment failures, and possibly even cascading events and blackouts. To cope with this, [...] Read more.

A power system’s nonlinearity and complexity increase from time to time due to increases of power demand. Therefore, properly designed power system controlsare required. Without these, system instability will cause equipment failures, and possibly even cascading events and blackouts. To cope with this, intelligent controllers using soft computing are necessary for real time operation. In this paper, the reheat type three-area thermal power system is considered, and the output scaling factors, gain parameters of fuzzy membership functions, and parameters of fuzzy-proportional integral derivative (FPID) controllers are optimized using a differential evolution (DE) optimization techniqueand integral time multiplied absolute error (ITAE) as objective functions. To improve the limitations of the controller and to enhance stability of the system, high voltage direct current (HVDC) technology is advantageous due to its quickresponse capabilities. In this paper, a HVDC is connected in parallel to the system, revealing that a FPID controller with a HVDC provides better and more accurate resultscompared to a system without a controller. The test results presented in this paper show the proposed controller’s suitability for managing random load changes. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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18 pages, 3676 KiB

Open AccessArticle

Full-Order Terminal Sliding-Mode Control for Soft Open Point

by Minghao Zhou, Hongyu Su, Haoyu Zhou, Likun Wang, Yi Liu and Haofan Yu

Energies 2022, 15(14), 4999; https://doi.org/10.3390/en15144999 - 08 Jul 2022

Cited by 1 | Viewed by 1173

Abstract

In this paper, a full-order terminal sliding-mode control method is proposed for the rectifier side and the inverter side of the soft open point (SOP). The rectifier-side DC voltage control system consists of the voltage- and current-loops with controllers which are designed using [...] Read more.

In this paper, a full-order terminal sliding-mode control method is proposed for the rectifier side and the inverter side of the soft open point (SOP). The rectifier-side DC voltage control system consists of the voltage- and current-loops with controllers which are designed using full-order sliding-mode (FOSM) to enhance the dynamic performances and anti-disturbance. The integral type virtual control signal without chattering is designed to compensate for the unmatched uncertainties including external disturbances and some parameter perturbations. The full-order terminal sliding-mode (FOTSM) controller for the current-loop can force the current response to track its reference in finite time. The inverter side power control system is designed to regulate the power. The FOTSM controller for the power-loop ensures the power-tracking accuracy under a disturbed condition. Finally, the simulations demonstrate the effectiveness of the proposed controllers for the rectifier and inverter sides in the soft open point (SOP). Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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15 pages, 7711 KiB

Open AccessArticle

Adaptive Sliding-Mode Control for Electric Spring in Microgrids with Distributed Renewable Energy

by Fagen Yin, Chun Wang and Weizhang Wang

Energies 2022, 15(13), 4842; https://doi.org/10.3390/en15134842 - 01 Jul 2022

Cited by 2 | Viewed by 1268

Abstract

Electric springs (ESs) are novel electric-power devices that alleviate power-quality problems such as voltage fluctuations induced by grid access to renewable energy resources. However, with the continuous increase of uncertain factors such as parameter perturbation and external disturbance, the environment becomes more complicated, [...] Read more.

Electric springs (ESs) are novel electric-power devices that alleviate power-quality problems such as voltage fluctuations induced by grid access to renewable energy resources. However, with the continuous increase of uncertain factors such as parameter perturbation and external disturbance, the environment becomes more complicated, so traditional linear controllers for ESs are finding it increasingly difficult to meet the control requirements due to narrow stability regions, low precision, and poor robustness. To overcome this problem, we propose herein a control method that combines adaptive control and sliding-mode control and apply it to ESs. First, an inexact model of the ES system was established and analyzed. Next, an ES control system was designed based on adaptive sliding-mode control, and then the asymptotic stability of the closed-loop system is proven. Finally, the proposed control system was verified through a MATLAB simulation. The results show that adaptive sliding-mode control not only ensures the voltage stability of critical loads in the microgrid but also resists the influence of parameter perturbation and external disturbances, leading to better steady-state and dynamic performance than a linear controller. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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16 pages, 1951 KiB

Open AccessArticle

An Evaluation Method of Renewable Energy Resources’ Penetration Capacity of an AC-DC Hybrid Grid

by Chenghao Li, Di Zhang, Zhiwei Liu, Yulong Xiong, Tianhang Yu, Ze Gao and Shihong Miao

Energies 2022, 15(7), 2550; https://doi.org/10.3390/en15072550 - 31 Mar 2022

Viewed by 1010

Abstract

With increasingly more renewable energy being integrated into the AC-DC hybrid grid, the grid shows more complex dynamic characteristics due to the mutual coupling of HVDC and renewable energy. To evaluate the renewable energy resources’ penetration capacity of the AC-DC hybrid grid, this [...] Read more.

With increasingly more renewable energy being integrated into the AC-DC hybrid grid, the grid shows more complex dynamic characteristics due to the mutual coupling of HVDC and renewable energy. To evaluate the renewable energy resources’ penetration capacity of the AC-DC hybrid grid, this paper proposes an evaluation method of the renewable energy resources’ penetration capacity of an AC-DC hybrid grid, which considers both economy and safety. Firstly, indicators are proposed for an evaluation of the economy and safety of the AC-DC hybrid grid integrated with renewable energy, where both static and transient stability indicators are considered. Secondly, to maximize the renewable energy penetration capacity and minimize the network loss, an optimization model of the renewable energy penetration capacity of the AC-DC hybrid grid is established considering the static and transient stability constraints. Then, a heuristic solution method for solving the renewable energy penetration capacity optimization model is proposed. Finally, based on the improved IEEE 39 node system, a case analysis is carried out. The simulation results verify the correctness and effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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26 pages, 4927 KiB

Open AccessArticle

Mitigating Generation Schedule Deviation of Wind Farm Using Battery Energy Storage System

by Asmamaw Sewnet, Baseem Khan, Issaias Gidey, Om Prakash Mahela, Adel El-Shahat and Almoataz Y. Abdelaziz

Energies 2022, 15(5), 1768; https://doi.org/10.3390/en15051768 - 27 Feb 2022

Cited by 7 | Viewed by 1605

Abstract

Meeting the generation schedule in a wind farm is a major issue. This work utilized battery energy storage systems (BESS) integrated wind farms (WF) to supply energy to the power grid at a pre-determined generation schedule, which was set previously based on the [...] Read more.

Meeting the generation schedule in a wind farm is a major issue. This work utilized battery energy storage systems (BESS) integrated wind farms (WF) to supply energy to the power grid at a pre-determined generation schedule, which was set previously based on the meteorological forecast and BESS characteristics. This study proposed the integration of two independently controlled BESS into the WF to balance stochastic power deviations between actual wind power and scheduled power. By utilizing linear optimization and solving in MATLAB, simulation models of the operations of BESS-integrated WF have been developed. The technical performance of the BESS-integrated wind farm on meeting the generation schedule, along with the cost benefits and profit attributed to the BESS, is therefore measured by a series of indices. The simulation on a practical wind farm, i.e., Adama-I WF, Ethiopia shows that even though it depends on the type of state exchanging strategy adopted, the developed methodology of integrating BESS into the WF is effective and BESS profits can totally cover the cost. Technical and economic indices that resulted from the integration of two separate BESSs with independent control were compared with indices that resulted from integrating a single BESS. Simulation results show that operating the wind farm with two independently controlled batteries has better performance as compared to operating with a single battery. It also shows that the discharging and charging state exchanging approaches of the BESS (in the case of two battery integration), as well as the number of batteries integrated into the wind farm, have significant impacts on the performance of the WF integrated with BESS. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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17 pages, 2502 KiB

Open AccessArticle

Wind-Photovoltaic-Energy Storage System Collaborative Planning Strategy Considering the Morphological Evolution of the Transmission and Distribution Network

by Defu Cai, Zuowei Wang, Shihong Miao, Rusi Chen, Zhong Zheng and Kunpeng Zhou

Energies 2022, 15(4), 1481; https://doi.org/10.3390/en15041481 - 17 Feb 2022

Cited by 4 | Viewed by 1273

Abstract

The collaborative planning of a wind-photovoltaic (PV)-energy storage system (ESS) is an effective means to reduce the carbon emission of system operation and improve the efficiency of resource collaborative utilization. In this paper, a wind-PV-ESS collaborative planning strategy considering the morphological evolution of [...] Read more.

The collaborative planning of a wind-photovoltaic (PV)-energy storage system (ESS) is an effective means to reduce the carbon emission of system operation and improve the efficiency of resource collaborative utilization. In this paper, a wind-PV-ESS collaborative planning strategy considering the morphological evolution of the transmission and distribution network is proposed. Firstly, aiming at the optimal economy of transmission and distribution network and considering the constraints of safe and stable operation of the system, the planning model of the transmission network based on DC power flow and the planning model of the distribution network based on AC power flow are constructed. Further, considering the coupling interaction between the transmission and distribution networks, a collaborative planning model of transmission and distribution networks based on second-order cone relaxation (SOCR) is constructed. Secondly, in order to reduce the computational complexity of the model and ensure the global optimality of the model solution, a fast model solution method based on heterogeneous decomposition architecture is proposed. Thirdly, the multiple driving factors of the morphological evolution of transmission and distribution network are analyzed, the morphological evolution path and typical characteristics of transmission and distribution network are determined, and a wind-PV-ESS collaborative planning strategy considering the morphological evolution of a transmission and distribution network is proposed. Finally, the results show that, compared with the sprouting period, the overall economy of the development period and maturity period is improved by 3342 k$ and 5751 k$ respectively, and the effectiveness and necessity of the collaborative planning strategy proposed in this paper is verified. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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20 pages, 4685 KiB

Open AccessArticle

Transaction Model Based on Stackelberg Game Method for Balancing Supply and Demand Sides of Multi-Energy Microgrid

by Meifang Wei, Youyue Deng, Min Long, Yahui Wang and Yong Li

Energies 2022, 15(4), 1362; https://doi.org/10.3390/en15041362 - 14 Feb 2022

Cited by 5 | Viewed by 1529

Abstract

To improve the coordination and complementarity of multiple energy sources, balancing the interests of different participants in a multi-energy system is of great importance. However, traditional centralized optimization can hardly reflect the game relationship between supply side and demand sides. A trading model [...] Read more.

To improve the coordination and complementarity of multiple energy sources, balancing the interests of different participants in a multi-energy system is of great importance. However, traditional centralized optimization can hardly reflect the game relationship between supply side and demand sides. A trading model based on the Stackelberg game model is proposed in this paper to balance the interests of the supply side and demand side and reduce the carbon emissions. First of all, the process of trading between the supply side and demand side based on smart contracts is described. A contractual consensus is obtained through an internal game, and the transaction is completed automatically. Secondly, a bilevel optimization model is established to coordinate the benefits of both parties based on the Stackelberg game model. The energy operator acts as a leader, and considers the two objectives, i.e., maximizing net income and minimizing carbon emissions, and uses the linear weighting method to convert the dual objectives into single objective. Users act as followers and aim to increase the comprehensive benefits, including energy cost and comfort. Then, Karush–Kuhn–Tucker optimality condition is used to transform the bilevel optimization model into an equivalent single-level model. Finally, simulation results show that the proposed method can coordinate the economic interests of both sides of supply and demand and effectively reduce the carbon emissions of the energy operator. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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16 pages, 688 KiB

Open AccessArticle

Self-Triggered Model Predictive Control of AC Microgrids with Physical and Communication State Constraints

by Xiaogang Dong, Jinqiang Gan, Hao Wu, Changchang Deng, Sisheng Liu and Chaolong Song

Energies 2022, 15(3), 1170; https://doi.org/10.3390/en15031170 - 05 Feb 2022

Cited by 3 | Viewed by 1283

Abstract

In this paper, we investigate the secondary control problems of AC microgrids with physical states (i.e., voltage, frequency and power, etc.) constrained in the process of actual control, namely, under the condition of state constraint. On the basis of the primary control (i.e., [...] Read more.

In this paper, we investigate the secondary control problems of AC microgrids with physical states (i.e., voltage, frequency and power, etc.) constrained in the process of actual control, namely, under the condition of state constraint. On the basis of the primary control (i.e., droop control), the control signals generated by distributed secondary control algorithm are used to solve the problems of voltage and frequency recovery and power allocation for each distributed generators (DGs). Therefore, the model predictive control (MPC) with the mechanism of rolling optimization is adopted in the second control layer to achieve the above control objectives and solve the physical state constraint problem at the same time. Meanwhile, in order to reduce the communication cost, we designed the self-triggered control based on the prediction mechanism of MPC. In addition, the proposed algorithm of self-triggered MPC does not need sampling and detection at any time, thus avoiding the design of observer and reducing the control complexity. In addition, the Zeno behavior is excluded through detailed analysis. Furthermore, the stability of the algorithm is verified by theoretical derivation of Lyapunov. Finally, the effectiveness of the algorithm is proved by simulation. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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18 pages, 8942 KiB

Open AccessArticle

Joint Acquisition Time Design and Sensor Association for Wireless Sensor Networks in Microgrids

by Liang Zhong , Shizhong Zhang , Yidu Zhang , Guang Chen and Yong Liu

Energies 2021, 14(22), 7756; https://doi.org/10.3390/en14227756 - 19 Nov 2021

Viewed by 1483

Abstract

Wireless sensor networks are used to monitor the operating status of the microgrids, which can effectively improve the stability of power supplies. The topology control is a critical issue of wireless sensor networks, which affects monitoring data transmission reliability and lifetime of wireless [...] Read more.

Wireless sensor networks are used to monitor the operating status of the microgrids, which can effectively improve the stability of power supplies. The topology control is a critical issue of wireless sensor networks, which affects monitoring data transmission reliability and lifetime of wireless sensor networks. Meanwhile, the data acquisition accuracy of wireless sensor networks has a great impact on the quality of monitoring. Therefore, this paper focuses on improving wireless sensor networks data acquisition satisfaction and energy efficiency. A joint acquisition time design and sensor association optimization algorithm is proposed to prolong the lifetime of wireless sensor networks and enhance the stability of monitoring, which considers the cluster heads selection, data collection satisfaction and sensor association. First, a multi-constrained mixed-integer programming problem, which combines acquisition time design and sensor association, is formulated to maximize data acquisition satisfaction and minimize energy consumption. To solve this problem, we propose an iterative algorithm based on block coordinate descent technology. In each iteration, the acquisition time is obtained by Lagrangian duality. After that, the sensor association is modeled as a 0–1 knapsack problem, and the three different methods are proposed to solve it. Finally, the simulations are provided to demonstrate the efficiency of the algorithm proposed in this paper. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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19 pages, 9660 KiB

Open AccessArticle

Mechanical Switch Based Adaptive Fault Ride-through Strategy for Power Quality Improvement Device

by Yu Shen, Wei Hu, Yaoyao Xiao, Ganghua Zhang, Mingyu Han, Fan Yang and Wenping Zuo

Energies 2021, 14(20), 6623; https://doi.org/10.3390/en14206623 - 14 Oct 2021

Viewed by 1370

Abstract

Cascaded H-bridge power quality improving device (PQID) has garnered extensive attention for its flexible electric energy conversion and fast voltage response. However, the failure rate of PQID is relatively high due to the use of large numbers of power electronic devices. This paper [...] Read more.

Cascaded H-bridge power quality improving device (PQID) has garnered extensive attention for its flexible electric energy conversion and fast voltage response. However, the failure rate of PQID is relatively high due to the use of large numbers of power electronic devices. This paper proposes a mechanical-switch based adaptive fault ride-through strategy for improving the operational stability and power supply reliability of PQID. According to the features of the topology and working principle of PQID, this paper summarized the types of internal faults and analyzed the characteristics of different types of faults. Based on the shortcomings of existing mechanical switches as a bypass method, corresponding adaptive fault ride-through strategies are proposed for different types of faults, and a comprehensive simulation test has been carried out. The results show that the proposed strategy can adaptively ride through unit faults and effectively improve the output waveform quality during the ride through time. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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21 pages, 3462 KiB

Open AccessArticle

A Novel Three-Phase Power Flow Algorithm for the Evaluation of the Impact of Renewable Energy Sources and D-STATCOM Devices on Unbalanced Radial Distribution Networks

by Raavi Satish, Kanchapogu Vaisakh, Almoataz Y. Abdelaziz and Adel El-Shahat

Energies 2021, 14(19), 6152; https://doi.org/10.3390/en14196152 - 27 Sep 2021

Cited by 6 | Viewed by 1466

Abstract

The impacts of the fast growth of renewable energy sources (RESs) and distribution static synchronous compensators (D-STATCOMs) on unbalanced radial distribution networks (URDNs) are analyzed with three-phase power flow algorithms (PFAs). As the URDNs are unbalanced, they can experience voltage unbalance (VU). This [...] Read more.

The impacts of the fast growth of renewable energy sources (RESs) and distribution static synchronous compensators (D-STATCOMs) on unbalanced radial distribution networks (URDNs) are analyzed with three-phase power flow algorithms (PFAs). As the URDNs are unbalanced, they can experience voltage unbalance (VU). This paper proposes a novel three-phase PFA for URDNs with multiple RES and D-STATCOM device integrations. The bus number matrix (BNM) and branch number matrix (BRNM) developed in this paper make the implementation of the proposed PFA simple. These matrices are developed to store the bus numbers and branch numbers of newly created sections of the URDN. Both PQ and PV modeling of RES and PV modeling of D-STATCOM devices are effectively integrated into the proposed three-phase PFA. The accuracy of the proposed PFA has been tested on the IEEE-13 bus URDN and the results are found to be accurate with the IEEE results. Several study examples have been conducted on the IEEE-13 bus and the IEEE-34 bus URDNs with multiple integrations of three-phase RESs and three-phase D-STATCOMs. Test results indicate that these integrations improve the voltage profile, reduce the power loss and reduce the severity of the VU. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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19 pages, 4821 KiB

Open AccessArticle

Optimal Power Flow Solution of Wind-Integrated Power System Using Novel Metaheuristic Method

by Amr Khaled Khamees, Almoataz Y. Abdelaziz, Makram R. Eskaros, Adel El-Shahat and Mahmoud A. Attia

Energies 2021, 14(19), 6117; https://doi.org/10.3390/en14196117 - 26 Sep 2021

Cited by 24 | Viewed by 1760

Abstract

Wind energy is particularly significant in the power system today since it is a cheap and clean power source. The unpredictability of wind speed leads to uncertainty in devolved power which increases the difficulty in wind energy system operation. This paper presents a [...] Read more.

Wind energy is particularly significant in the power system today since it is a cheap and clean power source. The unpredictability of wind speed leads to uncertainty in devolved power which increases the difficulty in wind energy system operation. This paper presents a stochastic optimal power flow (SCOPF) for obtaining the best scheduled power from wind farms while lowering total operational costs. A novel metaheuristics method called Aquila Optimizer (AO) is used to address the SCOPF problem due to its highly nonconvex and nonlinear nature. Wind speed is represented by the Weibull probability distribution function (PDF), which is used to anticipate the cost of wind-generated power from a wind farm based on scheduled power. Weibull parameters that provide the best match to wind data are estimated using the AO approach. The suggested wind generation cost model includes the opportunity costs of wind power underestimation and overestimation. Three IEEE systems (30, 57, and 118) are utilized to solve optimal power flow (OPF) using the AO method to prove the accuracy of this method, and results are compared with other metaheuristic methods. With six scenarios for the penalty and reverse cost coefficients, SCOPF is applied to a modified IEEE-30 bus system with two wind farms to obtain the optimal scheduled power from the two wind farms which reduces total operation cost. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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Review

Jump to: Research

22 pages, 1418 KiB

Open AccessReview

A Survey on Load Frequency Control of Multi-Area Power Systems: Recent Challenges and Strategies

by Xinghua Liu, Siwei Qiao and Zhiwei Liu

Energies 2023, 16(5), 2323; https://doi.org/10.3390/en16052323 - 28 Feb 2023

Cited by 4 | Viewed by 2112

Abstract

Load frequency control (LFC) is well known for balancing the load demand and frequency for a multi-area power system. Studies have proven that LFC can improve the global performance of multi-area power systems. In recent years, the increasing proportion of renewable energy, integration [...] Read more.

Load frequency control (LFC) is well known for balancing the load demand and frequency for a multi-area power system. Studies have proven that LFC can improve the global performance of multi-area power systems. In recent years, the increasing proportion of renewable energy, integration of EVs, and cyber-attacks have become the main challenges in LFC power systems. Different strategies have been applied in the literature for LFC power systems and the possible impacts of renewable energy, EVs, and cyber-attacks. This survey paper is devoted to the research on directions in LFC multi-area power systems. The mathematical model of recent challenges in LFC multi-area power systems is summarized and the similarities and differences of these challenges are analyzed. The uncertainty of renewable energy is a frequently noted issue in LFC power systems; however, the uncertainty that exists in controller design is often ignored. In this survey, we analyze methods for treating the uncertainty of renewable energy and controller. This survey paper introduces the most recent research on LFC and acquaints anyone interested in its development, such that the most effective strategies can be developed by the researchers. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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22 pages, 3626 KiB

Open AccessReview

A Review of Remaining Useful Life Prediction for Energy Storage Components Based on Stochastic Filtering Methods

by Liyuan Shao, Yong Zhang, Xiujuan Zheng, Xin He, Yufeng Zheng and Zhiwei Liu

Energies 2023, 16(3), 1469; https://doi.org/10.3390/en16031469 - 02 Feb 2023

Cited by 8 | Viewed by 2136

Abstract

Lithium-ion batteries are a green and environmental energy storage component, which have become the first choice for energy storage due to their high energy density and good cycling performance. Lithium-ion batteries will experience an irreversible process during the charge and discharge cycles, which [...] Read more.

Lithium-ion batteries are a green and environmental energy storage component, which have become the first choice for energy storage due to their high energy density and good cycling performance. Lithium-ion batteries will experience an irreversible process during the charge and discharge cycles, which can cause continuous decay of battery capacity and eventually lead to battery failure. Accurate remaining useful life (RUL) prediction technology is important for the safe use and maintenance of energy storage components. This paper reviews the progress of domestic and international research on RUL prediction methods for energy storage components. Firstly, the failure mechanism of energy storage components is clarified, and then, RUL prediction method of the energy storage components represented by lithium-ion batteries are summarized. Next, the application of the data–model fusion-based method based on kalman filter and particle filter to RUL prediction of lithium-ion batteries are analyzed. The problems faced by RUL prediction of the energy storage components and the future research outlook are discussed. Full article

(This article belongs to the Special Issue Challenges and Research Trends of Distributed Control and Optimization)

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