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Xiang Li, Guibin Zou, Chenghan Zhou, Xincheng Zheng, Xinyi Du, Zhe Lu
2026,11(02):1-15 ,DOI: 10.23919/PCMP.2024.000474
Abstract:
The integration of inverter-interfaced distributed generations (IIDGs) has modified the fault characteristics of active distribution networks (ADNs), substantially affecting the range, sensitivity, and reliability of conventional single-ended protection. Conventional current differential protection and existing waveform similarity-based protection methods suffer from poor tolerance to transition resistance and rely on simulations or field experiences for setting threshold values. To address these problems, this paper proposes a pilot protection method based on improved Fréchet distance by analyzing the differences in amplitude-phase characteristics of short-circuit currents during internal and external faults in ADNs with IIDGs. This method fully considers the physical significance of applying Fréchet distance to power-frequency current waveforms, offering a short operating time, high tolerance to transition resistance, and strong resistance to synchronization errors. Furthermore, a compensation criterion based on the positive-sequence current amplitude of the virtual T-connected branch is established to handle the impact of multiple unmeasurable T-connected branches. PSCAD simulations verify the effectiveness of the proposed method under different fault conditions and demonstrate its improvement over existing methods. Finally, a real-time digital simulator (RTDS)-based hardware test platform is used to further verify the developed differential relay prototypes based on the proposed method.
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Ali Sait Özer, Fehmi Sevilmiş, Hulusi Karaca, Hafiz Ahmed
2026,11(02):16-34 ,DOI: 10.23919/PCMP.2025.000070
Abstract:
In self-excited induction generator (SEIG)-based wind energy systems, voltage and frequency fluctuate with variations in wind speed and load, reducing power quality and efficiency. A distribution static synchronous compensator (DSTATCOM) is an effective solution to mitigate these fluctuations but requires real-time and accurate control, including precise estimation of voltage and current parameters. This paper proposes a fast hybrid-phase locked loop (FH-PLL)-based DSTATCOM control algorithm, offering superior filtering capabilities and enhanced sensitivity in detecting amplitude, frequency, and phase angle variations. The proposed method significantly improves the performance of DSTATCOM-assisted SEIG energy systems. Unlike conventional alternatives, which often suffer from either low estimation accuracy or high computational complexity, the proposed approach achieves an optimal balance between computational efficiency and estimation precision, making it a superior alternative to existing control algorithms. Comprehensive comparative performance evaluations under various challenging conditions such as non-linear loads, unbalanced loads, open-circuit faults, and measurement offsets, demonstrate that the proposed method achieves the lowest total harmonic distortion (THD) and total demand distortion (TDD) compared to state-of-the-art techniques, including the enhanced phase locked loop (EPLL), second-order generalized integrator (SOGI), and conventional synchronous reference frame PLL (SRF-PLL), while remaining compliant with the relevant IEEE 519-2014 standards.
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Yuan Zhang, Mingxu Xiang, Zhengwen Huang, Zhifang Yang
2026,11(02):35-47 ,DOI: 10.23919/PCMP.2024.000463
Abstract:
With the increase of adjustable loads connected to power systems, there is a growing risk of intentionally exploiting load adjustability to cause power balance deviations. This poses an obvious threat to power system frequency, which has been noticed by many system operators. However, the current dispatch method cannot consider the attack of load on frequency, let alone providing a preventive dispatch decision that reduces the frequency deviation. To address this challenge, a preventive dispatch method that mitigates the impact of adjustable load on power system frequency is presented for the first time. The relationship between the time-varying power mismatch caused by the attack of adjustable load and frequency deviation is established. This is achieved by theoretically deriving the transfer function between system frequency and power mismatch in time domain and discretizing the function into several segments according to the division of time horizons. A formal analysis of the error caused by the transformation is performed, which provides quantitative guidance on the accuracy of the frequency modeling. Based on this, the worst-case scenario of frequency deviation with adjustable load is determined through solving an optimization model. Then, a novel preventive dispatch method that guarantees the system frequency security under the worst-case scenario is presented. Particularly, the generator ramping behavior after receiving the AGC adjustment command is modeled by a group of linear constraints to distinguish the load tracking abilities of generators. Case studies based on the IEEE30-bus system and a 661-bus utility system show that the proposed preventive dispatch method can achieve a 5.8%-19.42% improvement of the maximum absolute frequency deviation.
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Haixiang Zang, Yongkai Zhao, Kang Sun, Guoqiang Sun, Lilin Cheng, Jingxuan Liu, Zhinong Wei
2026,11(02):48-61 ,DOI: 10.23919/PCMP.2024.000440
Abstract:
With the increasing penetration of large-scale renewable energy sources into the power grid, distribution networks are facing significant challenges, including intensified voltage fluctuations and increased network losses. Although deep reinforcement learning has made considerable advancements in addressing optimization problems compared to traditional algorithms, there has been limited focus on enhancing convergence and safety in cooperative optimization scenarios, particularly those involving topological reconstruction. To overcome these challenges, this paper proposes a distribution network optimization model that incorporates topological security-constrained integrated reinforcement learning. The model improves the encoding of topologies by representing them in a multi-dimensional discrete space and introduces a topological masking mechanism to achieve high safety and computational efficiency. Additionally, an ensemble strategy is utilized to develop an action network group, improving action prediction and screening, thereby achieving better training stability. Experiments conducted on an enhanced IEEE33-node distribution network system indicate that the proposed improvements significantly enhance training stability and support the safe and efficient operation of the system.
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Lipeng Zhou, Zhenguo Shao, Guoyang Cheng, Junjie Lin, Feixiong Chen
2026,11(02):62-76 ,DOI: 10.23919/PCMP.2024.000400
Abstract:
Harmonic state estimation in distribution networks is essential for identifying harmonic sources. However, issues such as limited measurement redundancy, asynchronous measurements, and unbalanced load distributions in three-phase networks undermine the reliability of existing methods in practical applications. To address these issues, this paper proposes an interval harmonic state estimation method in three-phase unbalanced distribution networks, integrating data from multiple sources. First, the interval multi-source harmonic measurement dataset is constructed by integrating asynchronous harmonic measurement data from multiple sources. The time asynchrony of measurement data from power quality monitoring devices is calibrated using the sliding window weighted dynamic time warping algorithm. Second, the interval harmonic state estimation model for the three-phase asymmetric distribution network is constructed. The model is solved using the interval-weighted least squares method, enhanced by the improved Krawczyk operator, thereby minimizing the expansion resulting from interval operations. Finally, the feasibility and accuracy of the proposed interval harmonic state estimation method are validated.
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Huabo Shi, Yufei Teng, Zhaohua Hu, Gang Chen, Lijie Ding, Xueyang Zeng, Pengyu Pan, Baorui Chen
2026,11(02):77-88 ,DOI: 10.23919/PCMP.2024.000392
Abstract:
To ensure safety while maintaining efficient operation and fast power regulation, this paper proposes a coordinated control strategy for variable-speed pumped storage units with full-size converters (FSC-VSPSU) in generation state. First, the dynamic stability characteristics and the key influencing factors in the fast power control mode and fast speed control mode are analyzed using the eigenvalue analysis method. The results indicate that the fast speed control mode can effectively address the issue of ultra-low frequency oscillation induced by fast power control. Then, the characteristics among the optimal speed, guide vane opening, and efficiency are clarified through laboratory testing of a pump turbine model machine, laying the foundations for developing optimized operation for the pumped storage units. Based on the analysis of slow load regulation and power step regulation, the power frequency regulation characteristics of the two control modes are revealed. Finally, leveraging the advantages of dynamic stability and power-speed regulation ability under the two control modes, a novel coordinated control strategy is proposed. The strategy has been applied to the first FSC-VSPSU in China, and the field tests demonstrate that the unit achieves excellent speed regulation performance and fast power regulation capability.
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Guangxue Wang, Hongchun Shu, Botao Shi, Haoming Liu, Shunguang Lei
2026,11(02):89-106 ,DOI: 10.23919/PCMP.2025.000298
Abstract:
Energy storage batteries operating under high levels of renewable energy integration face significant power fluctuations and frequent charge-discharge cycles, leading to substantial errors and uncertainties in state-of-charge (SOC) estimation at short time scales. To address this challenge, this paper proposes a novel SOC estimation method by integrating adaptive forgetting factor recursive least squares (AFF-RLS) with a data-driven hybrid architecture based on bidirectional long short-term memory (BiLSTM) and Transformer model. A second-order equivalent RC circuit model is constructed, and AFF-RLS is employed for real-time identification of model parameters, which are subsequently used as input features for the BiLSTM-Transformer model. The learning rate is dynamically adjusted based on error variation, and network parameters are optimized using the Adam algorithm. The method is validated using experimental data obtained from lead-carbon batteries, with its reliability and robustness verified through widely accepted performance metrics, including mean absolute error, mean absolute percentage error, root mean square error, and the coefficient of determination. Comparative experiments against convolutional neural network, Transformer, and LSTM-based models indicate that the proposed SOC estimation method consistently achieves lower estimation errors within 1.5% across varying state-of-health, demonstrating superior accuracy and robustness.
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Zhe Zhang, Bo Wang, Mao Yang, Zhao Wang, Wei Zhang, Tao Huang, Xin Su
2026,11(02):107-125 ,DOI: 10.23919/PCMP.2025.000058
Abstract:
Recognizing the intricate spatiotemporal correlation (STC) among wind farms (WFs) is critical to achieving better predictions for wind farm clusters (WFCs). To describe the STC accurately, this paper employs the wind angular field method to transform the wind series of WFs into different 2-D feature maps, and then construct homogeneous and heterogeneous STC graphs from these maps. The graphs are dynamically updated at the frequency of data update to capture time-varying STC among WFs. Finally, a dynamic graph attention network, designed according to the STC graphs, is established for WFC prediction. Through the above process, dynamic and accurate descriptions of STC are realized in WFC prediction. From the case study of a large-scale WFC with a capacity over 5800 MW in Northeast China, the proposed method reduces the root mean square error of the prediction in the next 24 hours by 2.67%.
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Abdallah Aboelnaga, Maher Azzouz
2026,11(02):126-143 ,DOI: 10.23919/PCMP.2025.000059
Abstract:
Fault currents contributed by inverter-based resources (IBRs) differ fundamentally from those of conventional sources. As a result, many traditional protection functions, such as directional elements, may fail to operate correctly when faults are predominantly supplied by these IBRs. This paper analyzes the relative angle between positive-sequence voltage and current under symmetrical faults and evaluates its variation at both near-end and far-end buses. In addition, the relative angle between negative-sequence voltage and current is analytically derived for fault currents supplied by different IBR control strategies. Based on this analysis, a unified directional element is designed that operates reliably for both symmetric and asymmetric faults, across a wide range of fault locations and resistances, and independently of the IBR controller employed. By addressing the unique challenges presented by IBRs, this research aims to enhance the reliability and effectiveness of protection systems in modern power grids. Time-domain simulations demonstrate the accuracy of the proposed directional element in correctly identifying fault directions across a wide range of fault locations and resistances, as well as under different IBR control strategies.
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Zihao Peng, Fan Xiao, Chunming Tu, Lei Wang, Yuteng Yuan, Yajie Tang, Xin Guo
2026,11(02):144-158 ,DOI: 10.23919/PCMP.2024.000414
Abstract:
Transient issues arising from voltage drops in distribution networks with high penetration of renewable energy, as well as post-fault reclosing challenges, are often addressed separately through low-voltage ride-through (LVRT) and quasi-simultaneous control, without a comprehensive stability analysis covering the entire fault stage. This paper reveals the temporal correlation between LVRT control and quasi-simultaneous control and proposes an integrated optimal control strategy. The strategy enhances the transient stability of droop-controlled inverters following voltage drops, ensures reliable load supply during off-grid operation, and achieves seamless grid reconnection without current surges during reclosing. During the LVRT phase, the inverter power reference is dynamically adjusted based on power angle characteristics and reactive power-current relationships to stabilize the power angle and limit output current. In the reclosing transition phase, a combined frequency and phase angle regulation mechanism is employed to minimize discrepancies in voltage frequency and phase angle, accounting for transient operating condition changes. The effectiveness and practicality of the proposed strategy are validated through simulations and experimental results.
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Shen Chen, Yang Xu, Hengxin He, Siyuan Xie, Zitian Wang, Xupeng Mu, Zhaoyin Shi, Anqi Pang, Yang Chen, Bo Qian, Weijiang Chen
2026,11(02):159-174 ,DOI: 10.23919/PCMP.2024.000466
Abstract:
Determining the coupling matrix is crucial for reconstructing transient voltages on overhead transmission lines using non-contact measurement techniques. However, existing methods often fail to account for the effects of asymmetrical sensor placement and the presence of multiple adjacent conductors in substations. This paper proposes an optimization-based approach to estimate the coupling matrix elements, aiming to minimize the transient voltage reconstruction error, with the measured power frequency voltage imposed as a constraint. The influence of adjacent conductors on the measured electric field is assumed to have a waveform similar to that of the measured conductors, as ensured by the electrically small condition during switching transients. The method is applied to reconstruct the closing and opening transient voltage waveforms of a 500 kV overhead transmission line. The estimated coupling matrix coefficients exhibit consistent performance across 11 tests, with maximum estimation errors of 6.2% and 2.5% for the opening and closing transient voltages, respectively. Moreover, the results indicate that the low-frequency response characteristics of capacitive voltage transformers (CVTs) are insufficient for capturing the opening transient voltages on transmission lines. By leveraging the full waveform of the measured transient electric field signal, the proposed method eliminates the need for symmetrical sensors and ensures robust field performance.
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2026,11(02):175-188 ,DOI: 10.23919/PCMP.2024.000393
Abstract:
In the decarbonization in the electricity sector, the emergence of prosumers in the medium/low voltage power distribution systems poses significant challenges for distribution system operators (DSOs), as bidirectional power exchange and carbon trading occur more frequently. This paper focuses the coordinated electricity and carbon management in a bi-level frame-work for DSOs and local distributed resources aggregators (DRAs). At the upper level, the optimal power flow (OPF) and carbon emission flow model (CEF) are solved to derive the locational marginal price (LMP) and nodal carbon intensity (NCI) for DRAs. At the lower level, an exponential-based pricing model is designed to enable peer-to-peer (P2P) carbon emission permit (CEP) trading among DRAs, which involves CEP demand-supply situation and emission assessment pressure. Chance constraints are formulated to address uncertainties in DRAs. Numerical results confirm the effectiveness of the proposed solution in coordinated electricity and carbon operation of multi-stakeholders in power distribution systems.
Volume 11,2026 Issue 02
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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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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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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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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.
