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Jingxuan Peng, Member, IEEE, Zhao Yuan, Zhuo Wang, Jingang Lai, Senior Member, IEEE, Yuanzheng Li, Senior Member, IEEE, Xiaolong Wu, Yuanwu Xu, Guoqiang Liu, Xi Li
2026,11(04):1-22 ,DOI: 10.23919/PCMP.2025.000294
Abstract:
Solid oxide fuel cell (SOFC) is an efficient and environmentally friendly energy technology, used in distributed generation, transportation and residential systems. However, high-temperature operation, multi-physics coupling, and long-term degradation issues create significant control challenges. This paper reviews recent advances in SOFC control with key findings showing a shift from classical methods to intelligent systems. Parameter optimization currently employs algorithms such as the response surface method to obtain optimal control objectives. Fault diagnosis and performance prediction combine physical models with machine learning. Control strategies are evolving from traditional control toward intelligent control. Furthermore, application studies guide the tailoring of these advanced controllers to real-world settings. Despite these progresses, challenges remain due to insufficient control intelligence or weak fault tolerance. To address these gaps, this paper outlines two future research paths, including lifecycle digital twins for predictive health management, and explainable AI control for creating trustworthy systems by embedding physical constraints and ensuring decision transparency.
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Maveeya Baba, Nursyarizal Bin Mohd Nor, Muhammad Aman Sheikh
2026,11(04):23-52 ,DOI: 10.23919/PCMP.2025.000373
Abstract:
Microgrid (µG) systems have emerged as a rapidly expanding concept in modern power systems due to its inherent capability to integrate multiple distributed generators (DGs) and renewable energy sources (RESs). However, the intermittent and dynamic nature of these sources, whose outputs depend heavily on weather conditions, introduces several operational challenges to µG systems, among which arc faults (AFs) represent a critical safety concern. Despite increasing research interest in µG protection, comprehensive review studies focusing on hybrid AC/DC microgrids (HAC/DCµGs), particularly regarding AF classification, detection, and protection strategies, remain limited. In HAC/DCµG systems, the simultaneous operation of AC and DC subsystems introduces additional complexity, as AFs occurring on either side can significantly compromise system reliability and operational safety. Accordingly, this paper provides a systematic review of AF phenomena, fault types, and reported case studies, along with existing mitigation strategies and their technical limitations. Furthermore, AF detection approaches based on metaheuristic optimization are critically reviewed, with particular emphasis on their effectiveness in improving detection accuracy and reducing misclassification. The review reveals that no single detection technique can reliably address AFs under diverse operating conditions and uncertainties, thereby highlighting the need for adaptive, multi-domain, and optimization-assisted protection frameworks to ensure reliable HAC/DCµG operation.
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Yongjun Zhang, Senior Member, IEEE, Chongying Jiang, Runting Cheng, Yingqi Yi, Otabek Ismailov, Yufei Liu
2026,11(04):53-67 ,DOI: 10.23919/PCMP.2025.000320
Abstract:
Zero-carbon islanded microgrids (ZC-IMGs) operating without fossil-fuel generators, face major challenges in maintaining frequency and voltage stability due to the lack of synchronous inertia and reliable voltage reference. The integration of inverter-based grid-forming energy storage systems (GFM-ESSs) provides a viable solution; however, their coordination requires communication-efficient and scalable control strategies. To address these issues, this paper proposes a novel event-triggered distributed control framework for ZC-IMGs. First, a detailed nonlinear state-space model is developed to accurately characterize the dynamic behavior of the microgrid and provide a solid foundation for control design. Then, adaptive event-triggering and distributed parameter estimation mechanisms are introduced, which significantly reduce communication requirements, ensure minimum inter-event intervals, and eliminate Zeno behavior without centralized coordination. Subsequently, a distributed priority-based charging protocol is designed to guarantee fair and stable state-of-charge management across multiple GFM-ESS units. Simulation results show that the proposed method achieves excellent frequency and voltage regulation, fast recovery from disturbances, and effective state-of-charge management. At the same time, it reduces communication events by 92% compared with traditional continuous distributed control. The proposed framework therefore provides a scalable solution with significantly reduced communication requirements.
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Junmin Wu, Shidong Liu, Xiande Bu, Chuan Liu, Ying Liu
2026,11(04):68-80 ,DOI: 10.23919/PCMP.2025.000019
Abstract:
The rapid advancements in cloud computing and other next-generation information and communication technologies have fueled the swift development of data centers (DCs). Aggregating these DCs to form virtual power plants (VPPs) for supporting grid frequency regulation has substantial potentials. However, previous research on DC frequency regulation has overlooked two major issues: inadequate consideration of clustering analysis for geographically dispersed DCs with similar load characteristics, and neglecting the influence of uncertainty within communication networks on power dispatch strategies for frequency regulation. To address these issues, this paper proposes a novel co-design method for power dispatch and communication transmission to facilitate frequency regulation for multiple VPPs based on DC aggregation. First, a DC aggregation strategy based on Ng-Jordan-Weiss spectral clustering algorithm is devised to construct the VPPs aggregated by DCs and determine their aggregation regulation capability. Based on this, a joint design approach is developed, which integrates a power dispatch strategy considering communication network uncertainty with a routing path optimization scheme for mitigating the network uncertainty. The method obtains precise power regulation tasks, thereby ensuring the reliability of VPPs' frequency regulation. Finally, comprehensive simulation results substantiate the viability and efficacy of the proposed methodology.
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Jing Ma, Fellow, IET, Lincheng Su, Xuezhi Deng, Xian Wen
2026,11(04):81-96 ,DOI: 10.23919/PCMP.2025.000362
Abstract:
Existing oscillation suppression strategies based on parameter tuning involve complex modeling processes, and their parameter adjustment ranges are constrained by the fundamental frequency performance. Meanwhile, oscillation suppression strategies based on control structure optimization fail to meet the suppression requirements under varying oscillation frequency conditions. Therefore, neither approach can achieve rapid and stable suppression of oscillations in permanent magnet synchronous generator (PMSG) connected voltage source converter-based multi-terminal direct current (VSC-MTDC) transmission systems under diverse operating conditions and scenarios. To address this problem, the response characteristics of different control system links under disturbances are analyzed, revealing the mechanism by which sending-end disturbances induces oscillatory instability. Based on the growth rates of interaction energy amplitudes between subsystems, the dominant interaction energy components responsible for oscillatory instability are identified. Then, using the output power of the static var generator and super capacitor as feedback signals, a control strategy is proposed to regulate the reference values of their inner current loops and compensate for the dominant interaction energy components. By suppressing the increasing of stored energy, this method can quickly suppress the oscillation. Simulation tests conducted on an RT-LAB semi-physical platform verify that, the proposed method can effectively suppress oscillations caused by sending-end disturbances within hundreds of milliseconds, while preserving the fundamental-frequency response characteristics of system power and voltage.
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Junjie Feng, Ziyu Feng, Ruosong Shang, Rui Liang, Senior Member, IEEE, Huijun Zhu, Yongzheng Dai, Yunhao Bai
2026,11(04):97-111 ,DOI: 10.23919/PCMP.2025.000251
Abstract:
Single-signal analysis is typically used to monitor the condition of oil-immersed transformers (OITs) for post-fault diagnosis. However, existing methods lack sensitivity to detect early-stage operational deviations that precede equipment failures. This paper focuses on proactive health monitor and detects pre-fault anomalies through multi-physics signal analysis. Current, oil temperature, and box amplitude of OITs are systematically analyzed considering their cross-domain interactions. A novel Transformer-Kolmogorov-Arnold networks (Transformer-KAN) architecture is developed to predict OIT electrical-thermal-vibration signal, and detect pre-fault anomalies. First, the cross-correlation analysis method is used to accurately quantify the delay time between OIT current, oil temperature, and vibration signals. Then, a prediction model is constructed based on Transformer self-attention mechanism and KAN nonlinear feature decomposition capability. Finally, reconstruction error is introduced to jointly optimize the OIT pre-fault anomaly detection model with the prediction error. The prediction task and anomaly detection task are combined. An on-site 500 kV OIT is used as a case study. The results show that the proposed method can significantly enhance the prediction accuracy of multi-dimensional OIT operation data and effectively detect pre-fault anomalies, providing support for OIT health monitoring and early warning.
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Lei Xi, Member, IEEE, Zongze Li, Yixiao Wang, Jiaqi Zhang, Zihao Li
2026,11(04):112-124 ,DOI: 10.23919/PCMP.2025.000396
Abstract:
The open environment of cyber-physical power systems (CPPS) exposes the safe operation of power grids to the threat of false data injection attacks (FDIA). Most existing detection methods for such cyberattacks suffer from limitations such as insufficient feature learning ability, slow detection speed, and inability to accurately identify attack locations. Therefore, this paper proposes a FDIA localizing detection method based on sparrow search algorithm with circle chaos initialization and firefly disturbance strategy improved multi-layer extreme learning machine, i.e., CFSSA-ELMML. The multi-layer extreme learning machine (ELMML) is adopted as the deep feature extraction model and the basic classifier to address the limitation of insufficient feature learning ability of existing detection methods. Moreover, an improved sparrow search algorithm (i.e., CFSSA) with strong local search ability is utilized to optimize the initial weight and bias of the multi-layer extreme learning machine, enabling fast and accurate localization of false data injection attacks. The effectiveness of the proposed method is verified through simulations on the IEEE14-bus and 57-bus systems. It is verified that the proposed method results in better location performance evaluation criteria compared with other detection methods.
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Ziqing Yang, Shunjiang Lin, Senior Member, IEEE, Yuerong Yang, Shiyuan Chen, Mingbo Liu, Member, IEEE
2026,11(04):125-142 ,DOI: 10.23919/PCMP.2024.000436
Abstract:
Large-scale renewable generation bases transmitted via voltage source converter (VSC)-HVDC system (RGBTVS) have emerged as a key approach for renewable power transmission in China's desert regions. The controller parameters of the VSCs significantly affect the small-signal stability (SSS) of RGBTVS. In this paper, a robust controller parameter optimization (RO) model for improving the SSS of a RGBTVS considering the injected power uncertainty is established. A support vector machine regression surrogate model is employed to approximate the highly nonlinear relationship of minimum damping ratio (MDR) and both controller parameters and renewable energy station (RES) output, thereby eliminating the need for matrix inversion and eigenvalue calculation in the SSS constraints. The RO problem is decomposed into two single-layer optimization problems which are solved iteratively using column-and-constraint generation (C&CG) algorithm. The master problem focuses on optimizing controller parameters to improve the system SSS under the worst scenario of RES output, while the sub-problem searches the RES output corresponding to the worst MDR under the specific controller parameters within the uncertainty set. A case study based on a practical RGBTVS in China verifies the correctness and effectiveness of the proposed method.
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Xiaotong Ji, Dan Liu, Kezheng Jiang, Yunhui Huang, Member, IEEE, Yifan Zhao
2026,11(04):143-158 ,DOI: 10.23919/PCMP.2025.000024
Abstract:
Existing studies on large-signal stability of grid-following (GFL) converters predominantly focus on the AC current control timescale, often assuming a constant DC-link voltage or relying on chopper control. In contrast, this paper addresses the overlooked dynamics within the DC-link voltage control timescale, where the cumulative effects of multiple control loops critically influence system stability. First, a novel dynamic model of the GFL converter is proposed. This model uniquely captures the transient trajectory of the internal voltage, enabling a physics-based quantification of stability through average acceleration during a swing. The transient stability margin of the GFL converter is then quantified based on whether the average acceleration of the internal voltage swing is positive or negative. This trajectory-based analysis provides a unique method for investigating transient stability. Furthermore, the large-signal stability of the GFL converter connected to a weak grid is analyzed under various physical scenarios. This is achieved by analyzing the average acceleration during the swing process in conjunction with phase portraits, which together provide valuable insights into the transient stability mechanism of this nonlinear system. The research reveals that, in a weak grid, the large-signal stability of the GFL converter diminishes as the DC-link voltage control bandwidth approaches the phase-locked loop (PLL) bandwidth. Conversely, stability improves as these two bandwidths diverge. Time-domain simulations and experimental tests are conducted to validate the theoretical analysis.
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Yanxu Chen, Shiji Pan, Yongning Zhao, Member, IEEE, Lin Ye, Senior Member, IEEE
2026,11(04):159-176 ,DOI: 10.23919/PCMP.2025.000029
Abstract:
The data used for intraday wind power forecasting (WPF) are often collected in non-stationary environments. Accuracy can be substantially reduced due to concept drift caused by significant changes in operational conditions of wind farms or in the probability distribution of samples. An adaptive intraday WPF model considering multi-timescale concept drift detection is proposed to address the above challenges. First, a spatio-temporal forecasting model is constructed to achieve intraday WPF. Then, an integrated mask-reconstruction representation learning pretraining strategy is employed to extract hidden representations of input historical wind power measurements and numerical weather prediction data. The degree of concept drift in the sample stream is quantified by measuring the cosine similarity between current and historical hidden representations. Finally, two concept drift detection modules with different time-scales are employed to guide the model in performing multi-stage adaptive update, enabling it to accommodate varying degrees of concept drift and achieve a balance between accuracy and flexibility during the detection process. Case studies based on 3 real wind farm clusters demonstrate the proposed method's superior forecasting accuracy and computational efficiency.
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Lili He, Zhikang Shuai, Senior Member, IEEE, Jingying Wan, Cong Zhang, Chao Shen, Jiayong Li, Daming Wang, Kecun Gao, Quan Zhou, Senior Member, IEEE
2026,11(04):177-195 ,DOI: 10.23919/PCMP.2025.000151
Abstract:
Fault behaviors of inverter-interfaced renewable energy sources (IIRESs) are primarily governed by the inverter control strategy. Uncertainties introduced by control response and network topology change pose challenges to the protection design of islanded microgrids. First, this paper establishes equivalent positive-sequence fault component (PSFC) models of IIRESs with and without activation of fault ride through (FRT) control. Their equivalent impedance angles are then analyzed under high- and low-resistance faults, revealing the dominant differences in fault direction features between forward and reverse faults. Subsequently, binary state fault direction indicators are constructed using the base frequency phase difference and high frequency cosine similarity between the PSFC voltage and current. A hybrid frequency direction feature-based protection scheme is then proposed, and its robustness against variations in FRT control response, fault scenarios, and network topology is demonstrated. The exchanging of binary state indicators between line terminals requires only low communication bandwidth. Finally, simulation results on a 10 kV islanded microgrid system validate the effectiveness of the proposed scheme under various conditions, including different fault resistances, fault inception angles, measurement noises, network topological changes, and IIRES control strategies.
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Xiaokang Wang, Long Chen, Member, IEEE, Yang Song, Senior Member, IEEE, Zhigang Liu, Fellow, IEEE, Yan Wang, Like Pan
2026,11(04):196-208 ,DOI: 10.23919/PCMP.2025.000156
Abstract:
Pantograph-rigid catenary (PC) systems are used for transferring electric energy to locomotives via a sliding contact between the contact wire and the pantograph slide. Contact surface ablation caused by frequent offline arcs significantly affects the service life of the PC system. While previous studies mainly focus on PC arcs at static separation distances, this paper discusses the ablation characteristics of the contact wire caused by transient arcing during a single complete dynamic separation process of the PC system. First, the multi-physics theory of PC arcs is introduced, and a corresponding magnetohydrodynamic model is established to accurately simulate the arc occurrence, development, and extinction. Next, by accounting for heat loss due to material evaporation, an ablation model for transient arcing effects on the contact wire is developed, and the model is verified using experimental data from a metro line. Finally, by introducing different dynamic separation behaviors, the ablation characteristics of the contact wire under various factors are revealed. The results indicate that the ablation of the contact wire due to transient arcing is directly proportional to the current and inversely proportional to the crosswind velocity. Furthermore, the ablation is more severe during the re-contact process of the PC system than during its separation process.
Volume 11,2026 Issue 04
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Yin Chen, Haibin Li, Tao Jin, Senior Member, IEEE
2025,10(1):132-147 ,DOI: 10.23919/PCMP.2023.000264
Abstract:
A high-boost interleaved DC-DC converter that utilizes coupled inductors and voltage multiplier cells (VMC) is proposed in this paper. The input power supply connects to switches through the primary sides of two coupling inductors with an interleaved structure, which reduces the voltage stresses of the switches and lowers the input current ripple. Two capacitors and a diode are placed in series on the secondary side of the coupled in ductors to enhance the high boost capability. The imple mentation of maximum power point tracking (MPPT) is facilitated by the simplification of the control system through common ground. To verify the effectiveness of the proposed converter, an experimental platform and a prototype based on a turns ratio of 1 are presented. The test results show that the voltage stresses on the switches are only 1/8 of the output voltage. The operating principle and design guidelines of the proposed converter are de scribed in detail. The experimental results show that the converter is efficient and stable over a wide power range.
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Amir Hossein Poursaeed, Farhad Namdari
2025,10(1):1-17 ,DOI: 10.23919/PCMP.2023.000032
Abstract:
Weighted least-square support vector machine (WLS-SVM) is proposed in this research as a real-time transient stability evaluation method using the synchrophasor measurement received from phasor measurement units (PMUs). This method considers the directional overcurrent relays (DOCRs) for the transmission system, whereas in previous studies, the effect of protective mechanisms on the transient stability was largely ignored. When protective relays are activated in power system, the configuration of the power system is altered to mitigate the risk of the power system becoming unstable. The present study considers the operation of DOCRs in transmission lines for the transient stability so that the proposed method can respond to changes in the configuration of the case study system. In addition, WLS-SVM is employed for an online assessment of the transient stability. WLS-SVM not only is effective in response due to its faster speed, but also is resistant to noise and has excellent performance against the measurement errors of PMUs. To extract the characteristics of the vectors that are fed into the WLS-SVM algorithm, principal component analysis is used. The findings of the suggested technique reveal that it has higher accuracy and optimum performance, as compared to the extreme learning machine method, the adaptive neuro-fuzzy inference system method, and the back-propagation neural network method. The proposed technique is validated in the New England 39-bus system and the IEEE 118-bus system.
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Zhe Yang, Member, IEEE, Hongyi Wang, Student Member, IEEE, Wenlong Liao, Member, IEEE, Claus Leth Bak, Senior Member, IEEE, Zhe Chen, Fellow, IEEE
2025,10(1):18-39 ,DOI: 10.23919/PCMP.2023.000279
Abstract:
Numerous renewable energy sources (RESs) are coupled with the power grid through power electronics to advance low-carbon objectives. These RESs predominantly connect to the AC collection network via inverters, with the electricity they produce either transmitted over long distances through high-voltage lines or utilized locally within the distribution system. The unique interfacing of RESs alters their fault response characteristics, typically resulting in limited fault currents, frequency deviations, and fluctuating sequence impedance angles. Therefore, existing protection principles based on fault signatures of synchronous generators will face significant challenges including distance relays, directional elements, differential relays, phase selectors, and overcurrent relays. To solve these issues, innovative protection technologies have been developed to bolster grid stability and security. Furthermore, the superior controllability of power converters presents an opportunity to devise effective control strategies that can adapt existing protection mechanisms to function correctly in this new energy landscape. Nevertheless, the complexity of fault behaviors exhibited by RESs necessitates further refinement of these schemes. Therefore, this paper aims to consolidate current research methodologies and explore prospective avenues for future investigation.
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Zhongqi Cai, Chengxiao Wei, Sui Peng, Xiuli Wang
2025,10(1):64-75 ,DOI: 10.23919/PCMP.2023.000285
Abstract:
The rapid expansion of offshore wind power plays a crucial role in China’s pursuit of its ‘dual carbon goals’. Fractional frequency transmission, an emerging technology for delivering large-scale offshore wind power, currently lacks extensive research attention. This paper addresses this gap by proposing a reliability assessment model for fractional frequency systems, encompassing generation, boosting, transmission, and conversion processes. Additionally, the study conducts a quantitative analysis of severe weather impacts on offshore component maintenance. With a focus on China’s offshore wind power development, the research includes comparative analyses of various offshore regions, system topologies, and transmission methods to evaluate system reliability. This comprehensive analysis serves as a valuable reference for the strategic planning and large-scale deployment of grid-connected offshore wind power systems.
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Sen Huang, Jun Yao, Member, IEEE, Wenwen He, Dong Yang, , Hai Xie
2025,10(05):165-180 ,DOI: 10.23919/PCMP.2024.000289
Abstract:
Similar to synchronous generators (SGs), symmetrical short-circuit faults can reduce the stability margin of grid-forming renewable power generation (GFM-RPG), thereby heightening the risk of transient instability. While existing studies primarily examine single-machine infinite-bus systems, this work explores transient stability challenges inherent in paralleled GFM-RPG systems. First, through rigorous mathematical derivation, it establishes that the transient characteristics of paralleled systems can still be effectively characterized by a second-order motion equation. Subsequently, by applying the extended equal area criterion (EEAC) and numerical solutions to differential equations, the study uncovers the governing principles behind the variations in the critical clearing angle (CCA) and critical clearing time (CCT) for the paralleled GFM-RPG system under various operating conditions. Finally, to mitigate potential instability risks, two corrective strategies, namely adaptive damping enhancement and power switching control, are proposed to improve the transient stability of the paralleled system during symmetrical faults. Simulation results confirm the accuracy of the theoretical analysis and demonstrates the effectiveness of the proposed strategy.
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Haizhen Xu, Changzhou Yu, Member, IEEE, Chen Chen, Leilei Guo, , Jianming Su, Ming Li, Member, IEEE, Xing Zhang, Senior Member, IEEE
2025,10(04):130-145 ,DOI: 10.23919/PCMP.2024.000197
Abstract:
The rapid and sustained advancement of photovoltaic (PV) power generation technology has introduced significant challenges to the power grid operation, including reduced grid strength and poor damping, thereby causing occurrence of harmonic resonance and potential instability. Conventional stability assessments of PV inverters often overlook critical factors-such as DC-side voltage control and operating mode variations-which arise from the characteristics of the connected PV array. Consequently, these assessments yield inaccurate stability assessments, particularly under weak grid conditions. This study addresses this issue by integrating the characteristics of PV output and DC-side power control into small-signal models while accounting for different control modes, such as constant current (CC), constant voltage (CV), and maximum power point tracking (MPPT). Initially, the study integrates the inverter's output control, LCL filter, and characteristics of the grid to develop a comprehensive framework for the entire PV system. Subsequently, the study uses amplitude and phase stability margins to evaluate how DC-side operating modes, the short-circuit ratio (SCR) of the power grid, and inverter controller parameters influence the system stability. Finally, the accuracy and stability of the model are validated through simulations and a 20-kW three-level prototype PV inverter.
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Hao Chen, Yongqiang Liu, Fan Yang, Xing Wang, Zefu Tan, Li Cai, Antonino Musolino, Qian Huang, Yong Qi, Guanjun Wang, Lijun Xu, Kai Ge, Yokub Tairov, Murat Shamiyev
2025,10(04):72-88 ,DOI: 10.23919/PCMP.2024.000092
Abstract:
Excessive temperature rise during the operation of the generator system can affect the safety and life cycle of the machine. Therefore, in order to accurately obtain the internal temperature of the switched reluctance generator (SRG), an internal temperature estimation model based on electric heating is established in this paper. First, an improved variable coefficient Bertotti loss separation calculation formula is adopted to solve the iron loss of the generator under various operating conditions. Subsequently, the accurate heat source parameters in the temperature model can be obtained, and the corresponding heat source data can be calculated. Then, based on the obtained heat source data, an equivalent thermal circuit model is established for SRG. Meanwhile, in order to effectively reduce the internal temperature during SRG operation, a new water-cooled structure for direct cooling of SRG stator windings is proposed in this paper, which can effectively reduce the temperature rise during operation, thus improving the reliability of the generator. Finally, by comparing the equivalent thermal circuit model, finite element thermal model, and experimental temperature measurements of SRG, it is found that results from the equivalent thermal circuit model of the SRG are closer to the measured temperatures, while the effectiveness of the water-cooled structure is verified.
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Huanlong Zhang, Chenglin Guo, Denghui Zhai, Yanfeng Wang, Heng Liu, Fuguo Chen, Dan Xu
2025,10(06):101-127 ,DOI: 10.23919/PCMP.2024.000413
Abstract:
Unmanned aerial vehicle (UAV) path planning plays an important role in power systems. In order to address the challenge in UAV path planning, an improved crested porcupine optimizer (ICPO) combining the Cauchy inverse cumulative distribution function and JAYA algorithm is proposed in this paper. First, the traditional random initialization is replaced by sine chaotic mapping, making the initial population more evenly distributed in the search space and improving the quality of the initial solution. Since the global search ability of the crested porcupine optimizer (CPO) is limited, the Cauchy inverse cumulative distribution strategy is introduced. In addition, as CPO is prone to fall into local optima in later stages, a weighted JAYA-CPO attack strategy is proposed to balance the global exploration and local exploitation, thereby improving the algorithm's ability to escape from local optima. Finally, ICPO is compared with another 10 algorithms on the cec2017 and cec2020 test sets. The experimental results show that ICPO has excellent competitiveness and optimization performance. The ICPO algorithm is applied to the path planning problem of power inspection UAV and is compared with four algorithms. The results show that the algorithm can generate more feasible path trajectories across two terrains with varying complexity, demonstrating the effectiveness and significance of the ICPO algorithm for UAV power inspection path planning.
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Wanqi Yuan, Yongli Li, Member, IEEE, Xiaolong Chen, Member, IEEE, Shaofan Zhang, Jing Wan, , Huili Tian
2025,10(05):123-141 ,DOI: 10.23919/PCMP.2024.000287
Abstract:
When a single-phase to ground fault (SPGF) occurs near the main power source in an active distribution network, distance protection section II (DPS-II) located at the distributed generator (DG) side operates with a delay. In gap-grounded transformers, this delay can lead to gap breakdown due to neutral-point overvoltage, which adversely affects the operation of DPS-II on the DG side. To address this issue, this paper proposes an improved DPS designed for active distribution networks with gap-grounded transformers. First, the factors influencing the additional impedance are analyzed after gap breakdown. To mitigate the effects of the additional impedance on DPS performance, an improved DPS based on real short-circuit impedances is introduced for active distribution networks. This scheme utilizes the negative-sequence current distribution factor on the DG side to accurately calculate the additional impedance angle, ensuring reliable protection. Simulation results demonstrate that the proposed scheme effectively operates under forward faults across various DG capacities, fault locations, local loads, and fault transition resistances. In addition, it avoids tripping under reverse faults, thereby confirming its reliability and superiority.
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Hongchun Shu, Cong Li, Yue Dai, Yutao Tang, Yiming Han
2025,10(04):58-71 ,DOI: 10.23919/PCMP.2024.000162
Abstract:
Automatic reclosing is widely employed in wind farm transmission lines. However, conventional reclosing strategies cannot identify the nature of the fault before reclosing, thereby posing a risk to the safe operation of the wind farm transmission system and associated equipment, especially during permanent faults. This study focuses on 220 kV wind farm transmission lines without parallel reactors. A single-phase ground fault circuit model is established first, and expressions for faulted phase-end voltages are derived before and after arc extinction. Then, the variations in voltage amplitude before and after fault arc extinction are revealed. The short-time Fourier transform is employed to extract fundamental frequency voltage amplitude from the secondary side of the capacitive voltage transformer (CVT). Subsequently, an adaptive reclosing strategy based on fundamental frequency voltage amplitude detection for wind farm transmission lines is proposed to enhance feature variations through sequential overlapping derivative (SOD) transformation. Finally, through analysis and validation on the RTDS platform, the proposed adaptive reclosing strategy is demonstrated to be simple, feasible, robust against transient resistances, and characterized by high sensitivity.
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Dongran Song, Asifa Yousaf, Javeria Noor, Yuan Cao, Mi Dong, Jian Yang, Rizk M. Rizk-Allah, M. H. Elkholy, , M. Talaat
2025,10(04):1-15 ,DOI: 10.23919/PCMP.2024.000074
Abstract:
Hybrid energy storage system (HESS) is an effective solution to address power imbalance problems caused by variability of renewable energy resources and load fluctuations in DC microgrids. The goal of HESS is to efficiently utilize different types of energy storage systems, each with its unique characteristics. Normally, the energy management of HESS relies on centralized control methods, which have limitations in flexibility, scalability, and reliability. This paper proposes an innovative artificial neural network (ANN) based model predictive control (MPC) method, integrated with a decentralized power-sharing strategy for HESS. In the proposed technique, MPC is employed as an expert to provide data to train the ANN. Once the ANN is finely tuned, it is directly utilized to control the DC-DC converters, eliminating the need for the extensive computations typically required by conventional MPC. In the proposed control scheme, virtual resistance droop control for fuel cell (FC) and virtual capacitance droop control for battery are designed in a decentralized manner to achieve power-sharing, enhance lifespan, and ensure HESS stability. As a result, the FC is able to support steady state loads, while the battery handles rapid load variations. Simulation results using Matlab/Simulink demonstrate the effective performance of the proposed controller under different loads and input variations, showcasing improved performance compared to conventional MPC.
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Guofeng Wang, Bei Jiang, Yuchen Liu, Licheng Wang, Youbing Zhang, Jun Yan, , Kai Wang
2025,10(05):103-122 ,DOI: 10.23919/PCMP.2024.000161
Abstract:
Addressing carbon reduction in the energy sector is crucial in the global fight against climate change. In response to this, a source-load coordinated optimization framework is proposed for distributed energy systems (DES). The high carbon-emitting power plants in the source side are transformed into carbon capture power plants to capture CO2 generated during power generation, thereby improving the power efficiency and decreasing the carbon emissions of the DES. On the load side, the low carbon demand response (LCDR) method is introduced to replace the traditional price-driven demand response. Governed by dynamic carbon emission factors, LCDR aims to facilitate a low carbon shift in end users' energy consumption patterns. An extensive analysis is conducted on the viability of the proposed source-load coordinated framework for low-carbon economic scheduling and an optimal optimization model is formulated by considering the comprehensive cost of the DES. The original problem is then transformed into a hierarchical Stackelberg game model with multi-leaders and multi-followers, which is further solved by an efficient quasi-potential game (QPG) algorithm. The practicality and scalability of the proposed work are validated through simulations conducted on the modified IEEE39-node and IEEE118-node test systems. The findings verify that the proposed framework is highly effective in improving power plant efficiency, optimizing the use of renewable energy, and substantially lowering carbon emissions.
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Gan Guo, Junhui Li, Gang Mu, Fellow, IET, Gangui Yan, Senior Member, CSEE
2025,10(06):176-197 ,DOI: 10.23919/PCMP.2024.000288
Abstract:
A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems (BESS). First, the time-dependent loss characteristics of both storage and non-storage components in BESS are analyzed. Based on this analysis, steady-state and transient methods for evaluating battery loss are proposed. Second, considering the distinct time-varying characteristics of various BESS components, the load-rate vs. equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools. These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy components of BESS. Building on this foundation, a time-varying optimization strategy for battery cluster power allocation is developed, aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS. Compared to real-time optimization, this strategy prioritizes global optimality in the time domain, mitigates the risk of dimensionality curse, and enhances BESS efficiency. Finally, a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS. The effectiveness of the proposed strategy is validated under a peak shaving scenario. Results indicate that, after optimization, the annual operational loss of BESS is reduced by 2.40%, while the energy round-trip efficiency is improved by 0.59%.
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Xinquan Chen, Graduate Student Member, IEEE, Aboutaleb Haddadi, Senior Member, IEEE, Evangelos Farantatos, Senior Member, IEEE, Ilhan Kocar, Senior Member, IEEE, Siqi Bu, Senior Member, IEEE
2025,10(04):116-129 ,DOI: 10.23919/PCMP.2024.000355
Abstract:
Integration of inverter-based resources (IBRs) reshapes conventional power swing patterns, challenging the operation of legacy power swing protection schemes. This paper highlights the significant consequences of the distinctive power swing patterns exhibited by grid-forming IBRs (GFM-IBRs). The swing mechanism involving GFM-IBRs is elucidated using analytical modeling of GFM-IBRs with various power synchronization loops (PSLs). With varying GFM-IBR penetration levels and different generator scenarios, the performance of power swing protection functions is examined, including power swing blocking (PSB) and out-of-step tripping (OST). Additionally, the IEEE PSRC D29 test system is employed to present power swing protection results in a large-scale power system integrated with synchronous generators (SGs) and IBRs. The results indicate that, GFM-IBRs with sufficient voltage support capability can provide positive impact on power swing dynamics, and power swing protection performance can be enhanced by emulating the inertia and droop mechanism of SGs and rapidly adjusting the active power output. However, with high penetration levels of GFM-IBRs, OST maloperation may occur in scenarios with inadequate voltage support capability.
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Bo Yang, Yimin Zhou, Yunfeng Yan, Shi Su, Jiale Li, Wei Yao, Hongbiao Li, Dengke Gao, , Jingbo Wang
2025,10(05):1-27 ,DOI: 10.23919/PCMP.2024.000297
Abstract:
To effectively promote renewable energy development and reduce carbon dioxide emissions, the new power system integrating renewable energy sources (RES), energy storage (ES) technology, and electric vehicles (EVs) is proposed. However, the generation variability and uncertainty of RES, the unpredictable charging schedule of EVs, and access to energy storage systems (ESS) pose significant challenges to the planning, operation, and scheduling of new power systems. Game theory, as a valuable tool for addressing complex subject and multi-objective problems, has been widely applied to tackle these challenges. This work undertakes a comprehensive review of the application of game theory in the planning, operation, and scheduling of new power systems. Through an analysis of 143 research works, the applications of game theory are categorized into three key areas: RES, ESS, and EV charging infrastructure. Moreover, the game theory approaches, payoff/objective functions, players, and strategies used in each study are thoroughly summarized. In addition, the potential for game theory based on artificial intelligence is explored. Lastly, this review discusses existing challenges and offers valuable insights and suggestions for the future research directions.
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Jimin Chai, Yuping Zheng, Shuyan Pan
2025,10(04):42-57 ,DOI: 10.23919/PCMP.2024.000128
Abstract:
Based on the dual equivalent model of a single-phase two-winding transformer and a single-phase three-winding autotransformer, a method for identifying inrush current in single-phase transformers is proposed. This method distinguishes inrush current from internal fault current using the instantaneous equivalent inductance of the dual model. The setting principle of the method is determined by analyzing the air-core inductance and the equivalent model of the faulty transformer. PSCAD simulations and recorded transformer protection data demonstrate that the proposed method can accurately identify inrush current when the transformer core is deeply saturated, and can quickly discriminate between currents during a critical internal fault. Furthermore, the simulation results show that the proposed method is sensitive to minor turn-to-turn faults but is less sensitive to the equivalent impedance of an external source.
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Jingbo Wang, Jianfeng Wen, Shaocong Wu, Bo Yang, Pingliang Zeng, Lin Jiang
2025,10(06):63-80 ,DOI: 10.23919/PCMP.2025.000004
Abstract:
This study develops a hybrid photovoltaic-thermoelectric generator (PV-TEG) system to reduce dependence on fossil fuels and promote sustainable energy generation. However, the inherent randomness of real-world operational environments introduces challenges such as partial shading conditions and uneven temperature distribution within PV and TEG modules. These factors can significantly degrade system performance and reduce energy conversion efficiency. To tackle these challenges, this paper proposes an advanced optimal power extraction strategy and develops a chaotic RIME (c-RIME) optimizer to achieve dynamic maximum power point tracking (MPPT) across varying operational scenarios. Compared with existing methods, this approach enhances the effectiveness and robustness of MPPT, particularly under complex working conditions. Furthermore, the study incorporates a comprehensive assessment framework that integrates both technical performance and sustainability considerations. A broader range of realistic operational scenarios are analyzed, with case studies utilizing onsite data from Hong Kong and Ningxia for technical and environmental evaluations. Simulation results reveal that the c-RIME-based MPPT technique can effectively enhance system energy output with smaller power fluctuations than existing methods. For instance, under startup testing conditions, the c-RIME optimizer achieves energy output increase by up to 126.67% compared to the arithmetic optimization algorithm.
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Xing Wang, Hao Chen, Zhengkai Yin, Fan Yang, Alecksey Anuchin, Galina Demidova, Nikolay Korovkin, Sakhno Liudmila, Popov Stanislav Olegovich, Bodrenkov Evgenii Alexandrovich, Mohamed Orabi, Mahmoud Abdelwahab Gaafar
2025,10(06):81-100 ,DOI: 10.23919/PCMP.2024.000377
Abstract:
In order to improve the control accuracy of switched reluctance motors (SRMs) without reducing the reliability of the driving system, multilevel power converters can be adopted. Compared to traditional asymmetric half bridge power converters which output three voltages (-U, 0, +U), asymmetric three-level T-type power converters can output five voltages (-U,-U/2, 0, U/2, U/2, U). Meanwhile, asymmetrical three-level T-type power converters can still independently control each phase winding in the SRM. However, research in the field of fault diagnosis for asymmetric three-level T-type power converters is insufficient. To optimize the control of SRM drive systems, this study adopts the asymmetric three-level T-type power converter as the research focus and conducts analysis in conjunction with an appropriate control strategy, thereby advancing both theoretical understanding and practical application in this field. A simulation model and an experimental platform of the SRM drive system based on the asymmetric three-level T-type power converter are developed. Both simulation and experimental results confirm the feasibility of the adopted converter topology and its control strategy, demonstrate the speed and accuracy of the proposed fault diagnosis method, and confirm that the drive system exhibits good dynamic performance.
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Pengfei Yu, Xiaofu Xiong, Xiangzhen He, Jizhong Zhu, Jun Liang, Dongliang Nan
2025,10(04):28-41 ,DOI: 10.23919/PCMP.2024.000090
Abstract:
Considering the escalating usage of renewable energy and rising frequency of extreme meteorological events, the risk of emergency load shedding (ELS) in power grids due to faults is increasing. The existing ELS strategies fail to provide users with advance warnings and blackout preparation time. To address this issue, an innovative strategy called warning and delayed load shedding is proposed in this study. In this approach, when it becomes necessary to shed load for emergency control, users are immediately notified with a power outage warning. Subsequently, energy storage and other regulatory resources are employed to substitute for load shedding, thus postponing the execution of the load shedding command. This delay equips users with the ability and time to respond and prepare. To implement this strategy, the operational principles supported by energy storage and backup power are further discussed. Five performance indexes are utilized to evaluate the delayed load shedding capability. Moreover, the delayed load shedding switch function and energy storage power balance equation are constructed to determine the relationship between energy storage, backup power sources, and load shedding time. Subsequently, two optimized load shedding models supported by energy storage are established, i.e., maximum and flexible delayed models. For comparison, improvements are made to the conventional load shedding model without delay by incorporating energy storage. An IEEE 30-node network with energy storage is used to test the three load shedding models. Accordingly, the evaluation indexes are calculated and compared. The results of the performance indexes and comparative analysis validate the effectiveness of the proposed methods, indicating that by using energy storage, users can be notified with advance power outage warnings and preparation time.
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Zeyin Zheng, Jianfeng Xu, Moufa Guo
2025,10(04):103-115 ,DOI: 10.23919/PCMP.2024.000174
Abstract:
Since the effectiveness of the flexible current arc suppression method heavily relies on the accurate measurement of the distribution line-to-ground parameters, the suppression of single line-to-ground (SLG) fault current may deteriorate due to factors such as line switching and other disturbances during SLG fault arc suppression. Additionally, during SLG fault arc suppression, promptly identifying the fault type and rapidly deactivating the flexible arc suppression device (FASD) can reduce the overvoltage risk in non-faulted phase devices. To address these issues, this paper presents a parameter identification method based on recursive least squares (RLS) while a variable forgetting factor strategy is introduces to enhance the RLS algorithm's disturbance rejection capability. Simulations verify that the variable forgetting factor recursive least squares (VFF-RLS) algorithm can accurately identify distribution line-to-ground parameters in real time and effectively suppress SLG fault current. The online identification of grounding transition conductance is simultaneously used to determine the fault type and quickly detect when the SLG fault has been cleared.
