- Current Issue
- Online First
- Adopt
- Most Downloaded Archive
-
Meysam Pashaei, Senior Member, IEEE, Kimmo Kauhaniemi, Member, IEEE, Hannu Laaksonen, Member, IEEE, Nikos Hatziargyriou, Life Fellow, IEEE
2026,11(01):1-25 ,DOI: 10.23919/PCMP.2025.000041
Abstract:
Power system protection has evolved significantly due to the ongoing energy transition and digitalization. The development and standardization of information and communication technologies (ICTs) used for power system protection, monitoring, and control have led to the digitalization of substations and the introduction of new protection and control schemes. These include virtualized centralized protection and control for intra-substation applications, as well as advanced wide-area monitoring, protection, and control (WAMPAC) for inter-substation applications. This paper reviews the development of virtualized centralized protection, with a focus on key practical advancements, emerging technologies, and state-of-the-art studies in centralized protection and control (CPC) and W AMP AC systems. It also identifies directions for future research.
-
Jiaxing Ning, Xiaoguang Wei, Zhichang Yuan, Longlong Chen, Hui Du, Zhanqing Yu
2026,11(01):26-39 ,DOI: 10.23919/PCMP.2024.000365
Abstract:
Hybrid commutation converters (HCCs) utilizing reverse-blocking integrated gate commutation thyristors (IGCTs) have gained significant attention due to their immunity to commutation failure. Leveraging the recovery enhancement characteristics of IGCTs, HCCs demonstrate superior performance at reduced extinction angles, thereby minimizing reactive power consumption. This study presents a comprehensive investigation into reactive power control strategies for HCCs operating at small extinction angles. First, the topological configuration and commutation principle of HCC are elucidated. Subsequently, the mechanism of HCC reactive power control is analyzed, and a reactive power control strategy is proposed by combining the converter transformer taps with extinction angles. Moreover, the relationship between transformer taps and reactive power exchange under different rated extinction angles is calculated, and the theoretically rated extinction angle is proposed. Finally, to validate the proposed control strategy, a four-terminal ultra-high voltage direct current power grid incorporating HCC technology is modeled and simulated using PSCAD/EMTDC. The simulation results demonstrate that the proposed strategy effectively supports AC systems by reducing reactive power absorption in HCCs, while simultaneously exhibiting enhanced reliability and economic efficiency.
-
Yixiang Zhang, Student Member, IEEE, Huifang Wang, Member, IEEE, Yuzhen Zheng, Zhengming Fei, Hui Zhou, Huafeng Luo
2026,11(01):40-52 ,DOI: 10.23919/PCMP.2024.000406
Abstract:
The increasing significance of text data in power system intelligence has highlighted the out-of-distribution (OOD) problem as a critical challenge, hindering the deployment of artificial intelligence (AI) models. In a closed-world setting, most AI models cannot detect and reject unexpected data, which exacerbates the harmful impact of the OOD problem. The high similarity between OOD and in-distribution (IND) samples in the power system presents challenges for existing OOD detection methods in achieving effective results. This study aims to elucidate and address the OOD problem in power systems through a text classification task. First, the underlying causes of OOD sample generation are analyzed, highlighting the inherent nature of the OOD problem in the power system. Second, a novel method integrating the enhanced Mahalanobis distance with calibration strategies is introduced to improve OOD detection for text data in power system applications. Finally, the case study utilizing the actual text data from power system field operation (PSFO) is conducted, demonstrating the effectiveness of the proposed OOD detection method. Experimental results indicate that the proposed method outperformed existing methods in text OOD detection tasks within the power system, achieving a remarkable 21.03% enhancement of metric in the false positive rate at 95% true positive recall (FPR95) and a 12.97% enhancement in classification accuracy for the mixed IND-OOD scenarios.
-
Jiangshan Liu, Fengting Li, Chunya Yin, Member, IEEE, Lu Han, Gaohang Zhang, Ruikang Chen, Wan Liu
2026,11(01):53-67 ,DOI: 10.23919/PCMP.2025.000097
Abstract:
During sending-end faults in the hybrid cascaded HVDC (HC-HVDC) system, the transient voltage drop characteristics under the interaction of the AC/DC hybrid system remain unclear, and the reactive power support provided by the HC-HVDC to the sending-end AC system requires further investigation. To address this problem, the reactive power interaction coupling mechanism between the sending-end AC system and the HC-HVDC is revealed, and the transient voltage mathematical model considering fault severity and duration is established. Under the dynamic change of the AC system voltage, the difference between the reactive power provided only by the reactive power compensation devices and by the combined modular multilevel converters (MMC) and reactive power compensation devices is analyzed. It is concluded that using MMC to provide a proportion of reactive power enhances the reactive power support to the AC system during faults. Then, the transient voltage model considering the reactive power support of MMC is established, and the critical reactive power consumption of line commutated converter (LCC) is quantified. It is concluded that the reactive power consumption of LCC exceeding its critical value deteriorates the transient voltage. A coordinated support strategy for the sending-end AC system based on reactive power support of MMC and reactive power regulation of LCC is proposed. It can effectively address the challenge of weakened reactive power support to the AC system due to voltage drop, thereby preventing the unbalanced reactive power from deteriorating the transient voltage, and realizing active support of the transient voltage. Finally, a simulation model is established on the PSCAD/EMTDC platform, and the simulation results validate the effectiveness of the proposed strategy in supporting the transient voltage, under different fault types, durations, severities, and locations.
-
Jiehui Zheng, Member, IEEE, Lexian Zhai, Mingming Tao, Wenhu Tang, Senior Member, IEEE, Zhigang Li, Senior Member, IEEE
2026,11(01):68-87 ,DOI: 10.23919/PCMP.2025.000183
Abstract:
The incorporation of high percentages of renewable resources into integrated energy systems (IES) is accelerating, and it becomes challenging to identify low-carbon economic dispatch options with significant uncertainties. This paper proposes an enhanced structure that combines hydrogen storage, power-to-gas, carbon capture and storage, and hydrogen fuel cells to extend CO2 reduction pathways. The structure is embedded within an IES that considers multi-energy network constraints. First, the low-carbon economic dispatch model is formulated as a multi-objective interval optimization problem minimizing the total fuel cost and carbon emissions of the IES comprising electricity, heat, gas, and hydrogen subsystems. Then, the multi-objective optimization problem is solved by set-based group search interval optimizer (Set-GSIO) to construct an interval-based Pareto frontier while preserving the uncertainty information for decision-making. In addition, a decision support method based on Shannon entropy and the technique of ordering preferences for similarity of ideal solutions (TOPSIS) evaluates the interval solutions in terms of convergence, stability, and security. Finally, case studies are conducted on a modified IEEE30-bus system integrated with a 15-node gas network and a 32-node heat network to verify the effectiveness of the proposed architecture and approach. Furthermore, the proposed approach is demonstrated on a larger-scale test case, and simulation results verify its scalability.
-
Yan Huang, Hadi Nabipour Afrouzi, Hieng Tiong Su, Yuan Ping, Ismat Hijazin, Yangtao Xu, Ke Yan
2026,11(01):88-104 ,DOI: 10.23919/PCMP.2024.000425
Abstract:
With the widespread adoption of digital equipment in intelligent substations, testing digital signals in power systems has become an important role for relay protection test equipment. Testing and calibrating digital signals require high accuracy. However, existing methods have low precision, cannot be calibrated at full range for all indexes, and have complex configuration, making them unsuitable for routine calibration work. To solve the above problems, a novel calibration method is designed and implemented using field programmable gate array (FPGA) to achieve accurate input and output time control. Accurate calibration relies on multiple forms of traceability including theoretical value traceability based on waveform comparison, time scale value traceability based on accurate time stamps, and algorithm traceability based on typical algorithms. Compared with other existing methods, the proposed approach reduces the mean absolute error of action time and time measurement by 92.88%, effectively addressing a key industry challenge and offering a valuable reference for further research, application, and standardization.
-
Hanxiao Liu, Luan Zhang, Bin Duan, Senior Member, IEEE, Liwei Li
2026,11(01):105-122 ,DOI: 10.23919/PCMP.2024.000385
Abstract:
Battery energy storage systems bolster power grids” absorption capacity, however, battery safety issues remain a formidable challenge. Timely and precise fault diagnosis, coupled with early-stage fault warnings., is crucial. This study introduces an eigen decomposition-based multi-fault diagnosis approach for lithium-ion battery packs, enabling online diagnosis of short circuits, electrical connection faults, and voltage sensor malfunctions. By incorporating an interleaved measurement topology, precise fault type differentiation is achieved. Eigenvector matching analysis is employed to increase sensitivity to fault characteristics and enhance robustness. The interleaved topology can be seamlessly integrated using common voltage measurement solutions, eliminating the need for additional design complexities, while sensor number redundancy enhances fault tolerance of battery management systems (BMS). A cloud-side collaboration method is proposed, where the BMS functions as an edge device for specific data computations, while the parameters are fine-tuned by the server through big data analytics. This approach circumvents cumber-some server calculations, thereby curbing server cost escalation. The edge computing process is divided into two steps, with partial calculations often sufficient to evaluate battery safety, thus reducing the computational load on edge devices. Several battery tests are conducted, and the results confirm the method's capability, feasibility, and validity in early-stage fault diagnosis.
-
Yi Luo, Jun Yao, Member, IEEE, Dong Yang, Hai Xie, Linsheng Zhao, Rongyu Jin
2026,11(01):123-140 ,DOI: 10.23919/PCMP.2024.000345
Abstract:
The transient behavior of DC-link voltage (DCV) significantly affects the low-voltage ride-through for phase-locked loop (PLL)-based grid-connected doubly-fed induction generator (DFIG) systems. This study investigates the DCV transient behavior of a PLL-based DFIG system under asymmetrical grid faults. First, by considering the coupling characteristics of positive and negative sequence (PNS) components, a nonlinear large-signal model of DCV is developed. Furthermore, the transient characteristics of DCV under varying parameters are analyzed using phase trajectory diagrams. In addition, the transient stability (TS) mechanism of DCV during asymmetrical faults is examined through an energy function approach. The analysis indicates that the transient instability of DCV is primarily associated with the control characteristics of PNS PLLs, while the TS level of DCV is mainly determined by the power coordination control between the rotor side converter and grid side converter. Moreover, a coordinated control strategy is proposed to enhance the TS of DCV under asymmetrical grid faults. Finally, both simulation and experimental results are presented to validate the theoretical analysis and the effectiveness of the proposed strategy.
-
Jing Yan, Jun Zhang, Luxi Zhang, Changhong Deng, Jinyu Zhang, Xin Wang, Tianlu Gao
2026,11(01):141-156 ,DOI: 10.23919/PCMP.2024.000412
Abstract:
This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity, gas, and heating networks. Introducing a cutting-edge stochastic gradient-enhanced distributionally robust optimization approach, this study integrates deep learning models, especially generative adversarial networks, to adeptly handle the inherent variability and uncertainties of re-newable energy and fluctuating consumer demands. The effectiveness of this framework is rigorously tested through detailed simulations mirroring real-world urban energy consumption, renewable energy production, and market price fluctuations over an annual period. The results reveal substantial improvements in the resilience and efficiency of the grid, achieving a reduction in power distribution losses by 15% and enhancing voltage stability by 20%, markedly outperforming conventional systems. Additionally, the framework facilitates up to 25% in cost reductions during peak demand periods, significantly lowering operational costs. The adoption of stochastic gradients further refines the framework's ability to continually adjust to real-time changes in environmental and market conditions, ensuring stable grid operations and fostering active consumer engagement in demand-side management. This strategy not only aligns with contemporary sustainable energy practices but also provides scalable and robust solutions to pressing challenges in modern power network management.
-
Xinyi Zhang, Student Member, IEEE, Bingyin Xu, Member, IEEE, , Zhaoru Han, Student Member, IEEE, Fang Shi, Member, IEEE
2026,11(01):157-172 ,DOI: 10.23919/PCMP.2025.000040
Abstract:
Traveling wave (TW) fault location technology has been widely used in transmission systems due to its high accuracy and simplicity. Recently, there has been growing interest in applying this technology to medium voltage (MV) distribution lines. However, current practices in its deployment, signal measurement, and threshold setting are usually from the application experiences in transmission lines, despite significant differences in fault-induced wave characteristics between transmission and distribution systems. To address these issues, this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs. The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied. Furthermore, it evaluates the influence of critical distribution network components including distribution transformers, multi-branch configurations, and busbar structures on wave propagation characteristics. Deployment strategies for traveling wave fault location (TWFL) devices is proposed to address the unique challenges of distribution networks, while the fault location method is also improved. Field test results demonstrate the effectiveness of the proposed methodology, showing improved fault detection accuracy and system reliability in distribution network applications. This research provides practical implementation suggestions for TWFL technology in distribution networks.
-
Shouyuan Shi, Zhenning Pan, Member, IEEE, Junbin Chen, Tao Yu, Senior Member, IEEE
2026,11(01):173-191 ,DOI: 10.23919/PCMP.2024.000327
Abstract:
The annual compliance cycle of the carbon trading system allows generation companies (GenCos) to decouple the timing of carbon allowance purchases from their actual emissions. However, trading a large volume of allowances within a single day can significantly impact on carbon prices. Faced with uncertain future carbon and electricity prices, GenCos must address a challenging multistage stochastic optimization problem to coordinate their carbon trading strategies with daily power generation decisions. In this paper, a two-layered hybrid mathematical-deep reinforcement learning (DRL) optimization framework is proposed. The upper DRL layer tackles the stochastic, year-long carbon trading and allowance usage optimization problem, aiming for long-term optimality and providing guidance for short-term decisions in the lower layer. The lower mathematical optimization layer addresses the deterministic daily power generation schedule problem while en-forcing strict technical constraints. To accelerate learning of the annual compliance cycle, a decision timeline transfer learning method is proposed, enabling the DRL agent to progressively refine its policy through sequentially training on monthly, weekly and daily decision environments. Case studies demonstrate that, with these methods, a GenCo can reduce emission costs and increase profits by effectively leveraging carbon price fluctuations within the compliance cycle.
-
Meng Tian, Xiaoxu Li, Ziyang Zhu, Zhengcheng Dong, Li Gong, Jingang Lai
2026,11(01):192-207 ,DOI: 10.23919/PCMP.2024.000342
Abstract:
With the prevalence of renewable distributed energy resources (DERs) such as photovoltaics (PVs), modern active distribution networks (ADNs) suffer from voltage deviation and power quality issues. However, traditional voltage control methods often face a trade-off between efficiency and effectiveness, and rarely ensure robust voltage safety under typical state perturbations in practical distribution grids. In this paper, a robust model-free voltage regulation approach is proposed which simultaneously takes security and robustness into account. In this context, the voltage control problem is formulated as a constrained Markov decision process (CMDP). A safety-augmented multi-agent deep deterministic policy gradient (MADDPG) algorithm is the trained to enable real-time collaborative optimization of ADNs, aiming to maintain nodal voltages within safe operational limits while minimizing total line losses. Moreover, a robust regulation loss is introduced to ensure reliable performance under various state perturbations in practical voltage controls. The proposed regulation algorithm effectively balance efficiency, safety, and robustness, and also demonstrates potential for generalizing these characteristics to other applications. Numerical studies validate the robustness of the proposed method under varying state perturbations on the IEEE test cases and the optimal integrated control performance when compared to other benchmarks.
Volume 11,2026 Issue 01
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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%.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
