Table of Content

28 February 2025, Volume 58 Issue 2

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Key Technologies of Relay Protection in the New Power System

Adaptive Current Differential Protection Method Considering Control and Protection Coordination

Bo ZHANG, Congbo WANG, Rongrong ZHAN, Yue YU

2025, 58(2):  1-8.  DOI: 10.11930/j.issn.1004-9649.202407104

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The VSC-HVDC transmission system for large-scale new energy has become a typical scenario in China's new power system. However, the transmission line between the new energy station and the flexible direct converter is special with its both sides being power electronic devices, and affected by different converter control strategies, the short-circuit current waveform is seriously distorted, which reduces the sensitivity of traditional longitudinal protection and increases the risk of rejection. Therefore, an adaptive current differential protection method considering control and protection coordination is proposed. Based on the fault ride throgh strategy of the VSC-HVDC, the fault current characteristics on both sides are analyzed, and an adaptive protection criterion for control and protection coordination is constructed by combining the control reference value of the converter and the protection criterion. Finally, a VSC-HVDC transmission system model for new energy is built based on PSCAD, and the performance of the proposed protection is verified by simulation. The results show that the proposed protection can quickly identify different fault types in the fault region with the sensitivity improved by 2~3 times compared with the traditional differential protection principle, which can meet the requirements of the new power systems for protection sensitivity and reliability.

Differential Protection of Main Transformer of Doubly-Fed Wind Farm Based on Current Synthesized Vector Trajectory Characteristics

Xupeng SONG, Xiaoyang YANG, Zhengzhen FAN

2025, 58(2):  9-21.  DOI: 10.11930/j.issn.1004-9649.202401014

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During the fault ride-through process of the doubly-fed wind farms, the short-circuit current provided by the wind farm side exhibits frequency deviation, which leads to errors in the Fourier algorithm based phasor extraction. Additionally, the second harmonic restraint element may act incorrectly, leading to longterm blockage of the differential protection. This paper proposes a novel time-domain protection scheme based on the characteristics of the current synthesis vector trajectory. Based on the intrinsic differences between internal faults and external faults of transformers, two current synthesis vectors are constructed accordingly, and corresponding protection schemes are designed according to the trajectory characteristics of each synthesis vector. A simulation model of the control and protection of the delivery system of doubly-fed wind farms is constructed in PSCAD/EMTDC. Experimental results show that the proposed scheme can identify various internal faults and is not affected by the interference of magnetizing inrush current, current transformer (CT) saturation accompanying external faults and CT measurement errors accompanying external faults. The proposed scheme can operate in 15ms at the fastest and the average operation time is less than a fundamental frequency cycle.

High Resistance Grounding Fault Perception and Identification Method in Asymmetric Distribution Network

Penghui YANG, Guochao QIAN, Hao BAI, Hongwen LIU, Wanxian YANG, Xiao SHI

2025, 58(2):  22-32.  DOI: 10.11930/j.issn.1004-9649.202406070

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Aiming at the problems of fault perception and identification in high resistance grounding fault of distribution network, a high resistance grounding fault perception method for parameter-asymmetric distribution network based on damping rate variation is proposed. In this method, the zero-sequence voltage is actively regulated by the active inverter device for a short time, and the fault is judged according to the variation of the system damping rate before and after fault. On the basis of realizing the sensitive perception of high resistance grounding fault, a fault type identification method based on the change characteristics of zero-sequence equivalent admittance phase angle of the system is further proposed. This identification method actively changes the zero-sequence voltage amplitude regulation coefficient, and accurately identifies the transient and permanent grounding fault types according to the change trajectory of admittance phase angle under different grounding modes. The simulation analysis shows that the proposed method can be applied to the three-phase parameter asymmetric distribution network. The proposed method can realize fault perception and identification in low and high resistance grounding faults under different operation modes, and has strong resistance to transition resistance and strong applicability.

Fault Type Recognition and Localization Method for Grounding Electrode Line Based on Modulus Backward Traveling Wave

Xinyang ZHAO, Hongsen ZOU, Chen YANG, Yuqi LI, Botong LI, Siyuan LIU

2025, 58(2):  33-42.  DOI: 10.11930/j.issn.1004-9649.202403069

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The traveling wave method is currently a common approach for fault distance measurement in grounding electrode line, but it generally relies on simulation in terms of threshold setting, and cannot determine the type of grounding electrode line fault. To address the above issues, this paper adopts an active traveling wave injection method, and through analytical calculations, obtains the time-domain expression of the modulus-backward traveling wave at the measuring point at the first end of the ground electrode line after a single-line ground fault, a cross-line fault, a single-line open-circuit fault and a double-line open-circuit fault. A grounding electrode line fault type recognition and localization method is proposed based on modulus backward traveling wave. The proposed injection wave method has a clear expression of distance measurement threshold setting, then can accurately identify the type of line fault. The reliability and robustness of this method is verified in PSCAD/EMTDC simulations. Simulation results show that this method can achieve accurate fault distance measurement, and reliably identifies grounding electrode fault type, demonstrating strong tolerance to transition resistance and resistance to noise interference.

Research on Modeling and Operational Decision of Distributed Flexible Resources in Cities and Towns for Smart Low-Carbon Development

Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations

Jin LI, Kemeng LIU, Danli XU, Weiju GAO, Lei HUANG, Haoxing WU, Haochen HUA

2025, 58(2):  43-56.  DOI: 10.11930/j.issn.1004-9649.202408007

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The strong uncertainty introduced by a high proportion of renewable energy sources integrated into the energy system complicates the internal optimization of system operation and may lead to the spillover of uncertainty risks, affecting the stable operation of the higher-level power grid. To address this issue, a two-layer coordinated optimization strategy for the external response of a multi-energy complementary micro-energy grid system based on a shared energy storage station is proposed. Firstly, operational models for energy equipment within the micro-energy grid system are constructed, and operational modes and profit mechanisms for the shared energy storage station are proposed. Secondly, a two-layer coordinated optimization model considering two different stakeholders is established, with the micro-energy grid system operator as the upper layer and the shared energy storage station operator as the lower layer. Subsequently, the Hong's (2m+1) point estimation method is used to quantify the uncertainty of wind and solar power, and the two-layer nonlinear optimization model is transformed into a single-layer mixed-integer optimization model using the KKT conditions and Big-M method. Finally, simulation results demonstrate that the proposed strategy can effectively prevent the spillover of uncertainty risks associated with wind and solar power, reducing the operational costs of the micro-energy grid operator by 6.3%.

Power Grid Optimization Operation and Resilience Improvement Strategy Considering the Participation of Energy Storage Resource Aggregation

Yening LAI, Zhongqing SUN, Zhiping LU, Qin LIU

2025, 58(2):  57-65.  DOI: 10.11930/j.issn.1004-9649.202402073

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Extreme weather brings many challenges to the construction and operation of new power system, and the continuous enrichment of the flexible resources of power system provides the power grid new ideas to deal with extreme weathers. Considering the scenarios of energy storage and other resources aggregation participating in power grid load recovery under extreme conditions, a study is made on the strategy and method for resource aggregation participating in power grid resilience improvement. Firstly, based on the operation status of energy storage resources, a resource surplus adjustment ability model is proposed. And then, a resource aggregation regulation model is established considering the resource surplus adjustment ability, and through "domain" characterization of the correlation between the surplus adjustment ability of resource aggregate and operation power, a power grid optimization operation and resilience improvement model is further built. Finally, the effectiveness of the proposed strategy for power grid resilience improvement is verified through case study.

Market Oriented Low-Carbon Optimal Scheduling of Virtual Power Plants Considering Multiple User-Side Resources Coordination

Mingbing LI, Qiang LI, Xiyang GUAN, Haoyang ZHOU, Rui LU, Yankun FENG

2025, 58(2):  66-76.  DOI: 10.11930/j.issn.1004-9649.202407102

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To leverage the synergistic effects of diverse user-side resources, enhance the revenue of Virtual Power Plants (VPPs) participating in the joint electricity-carbon market, and mitigate risks arising from the uncertainty of renewable energy sources (such as wind and solar) and electricity prices, an optimized low-carbon dispatching method for VPPs considering the coordination of diverse user-side resources in a market environment is proposed. Firstly, based on the synergistic effects of various user-side resources, a strategy for VPPs to participate in the joint electricity-carbon market operation is formulated. Secondly, a tiered carbon trading model with incentives and penalties for VPPs is established, where different transaction interval prices are set according to carbon trading volumes, thereby achieving carbon-electricity coupling. Finally, an optimized low-carbon dispatching model for VPPs participating in the joint electricity-carbon market is constructed. In this model, Conditional Value at Risk (CVaR) is introduced to measure the relationship between market returns and risks, and the model is transformed into a Mixed Integer Linear Programming (MILP) problem for solution. Through case studies, it is demonstrated that this method can effectively harness the synergistic effects of user-side resources, address the uncertainty risks associated with renewable energy sources and electricity prices, and achieve both economic efficiency and low-carbon performance for VPPs participating in market operations.

Optimal Scheduling of Integrated Energy System Considering The Ladder-Type Carbon Trading Mechanism

Jianhua ZHOU, Changyu LIANG, Linjun SHI, Yang LI, Wenfei YI

2025, 58(2):  77-87.  DOI: 10.11930/j.issn.1004-9649.202404059

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Under the "dual-carbon" goal, the energy industry is facing many challenges such as the level of technological development, the tight timeframe for carbon reduction, structural transformation and environmental governance, so integrated energy system (IES) plays an important role in realizing a new power system. Considering the ladder-type carbon trading mechanism and demand-side response, a low-carbon economic operation optimal scheduling model for IES is proposed. Firstly, gas load emission factor is introduced into the carbon emission model, and the ladder-type carbon trading mechanism is adopted. Then, based on the time-of-use price and substitution of each energy source, two types of demand-side response, price-based and substitution-based, are investigated separately. Finally, with the objective of minimizing the integrated cost, the simulation results show that the model that takes into account the ladder-type carbon trading mechanism and demand-side response, and considers the impact of gas load emission, can significantly reduce carbon emission of IES. After demand response, the energy purchase cost, carbon trading cost and carbon emission are reduced by about 3.38%, 36.25% and 18.52%, respectively.

Optimal Dispatch of Integrated Electric-Heat Energy System Considering Supply Flexibility of Heat Networks Under Different Operation States

Yumin ZHANG, Yanbin Yin, Xingquan JI, Pingfeng YE, Donglei SUN, Aiquan SONG

2025, 58(2):  88-102.  DOI: 10.11930/j.issn.1004-9649.202407088

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The increasing penetration of renewable energy sources has made the fluctuation of system net load increasingly prominent, posing higher flexibility requirements on system operation. To address this, an optimized dispatch strategy for integrated energy systems (IES) is proposed, taking into account the flexibility supply capacity under different operational states of the heating network. Firstly, based on interval optimization, the sub-hourly operational flexibility demand of the system is determined in response to the uncertainty of wind power and load. Secondly, by analyzing the impact of four types of changes in heat load and electrical net load on system operational flexibility and considering the upward/downward flexibility supply mechanism of combined heat and power units under dynamic heating network characteristics, a flexibility supply model for the heating network under different operational states is derived. Then, by clarifying the charging, discharging, and non-operating states of energy storage devices as well as their energy limit characteristics, a mathematical model for providing sub-hourly operational flexibility through energy storage is derived. A coordinated relationship between hourly-scale optimized dispatch decisions for the IES and sub-hourly operational flexibility constraints is established, thereby constructing an IES optimized dispatch model that takes into account the operational flexibility of multiple links including sources, networks, and storage. Finally, the proposed model is tested using the integrated energy E6-H8 and E57-H16 systems as examples, verifying that it can effectively improve system operational flexibility by optimizing energy storage and heating network flexibility resources.

Optimal Scheduling Strategy for Microgrid Considering the Support Capabilities of Grid Forming Energy Storage

Zhibin YAN, Li LI, Peng YANG, Huihui SONG, bin CHE, Panlong JIN

2025, 58(2):  103-110.  DOI: 10.11930/j.issn.1004-9649.202409056

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In order to coordinate the stability and operation efficiency of the microgrid, the inertial support characteristics and frequency support capability of the grid-forming storage are analyzed. Based on this, the optimization objectives of the microgrid are clarified, and the constraints such as power balance, equipment operation, system inertia, and reserve capacity are formed. Combined with the nonlinear optimization problem solver of the Optimization Toolbox, an optimization scheduling strategy considering the support capability of the grid-forming energy storage proposed. In order to test the effectiveness of the proposed strategy, the joint probability distribution function of wind and solar power generation is constructed by using the kernel density estimation method the Copula function, and the typical scenarios of new energy are formed based on the K-means clustering. The analysis is carried out under the typical scenarios, and results show that the proposed method can give full play to the support capability of the grid-forming energy storage and effectively improve the level of new energy consumption.

Data-Driven Analysis and Control of Power System Security and Stability

Voltage Control Based on Multi-Agent Safe Deep Reinforcement Learning

Yi ZENG, Yi ZHOU, Jixiang LU, Liangcai ZHOU, Ningkai TANG, Hong LI

2025, 58(2):  111-117.  DOI: 10.11930/j.issn.1004-9649.202404047

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To address issues of voltage limit violations and fluctuations caused by the high penetration of distributed photovoltaic (PV) systems in the distribution network, a voltage control method based on multi-agent safe deep reinforcement learning is proposed. The voltage control with PV is modeled as a decentralized partially observable Markov decision process. A safety layer is introduced in the deep policy network for agent design, while the voltage barrier function based on traditional optimization model voltage constraints is used in defining the agent reward function. Testing results on the IEEE 33-bus system demonstrate that the proposed method can generate voltage control strategies that meet safety constraints under high photovoltaic penetration scenarios, and it can be used to assist dispatchers in making real-time decisions online.

Digital Simulation Test Method for Multiple Scenarios Relay Protection

Qingquan LIU, Peng YANG, Tiecheng LI, Xianzhi WANG, Minghao WEN

2025, 58(2):  118-125.  DOI: 10.11930/j.issn.1004-9649.202405131

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The massive access of new energy has brought adaptability problems to relay protection. This paper proposes a digital simulation testing method for relay protection in multiple scenarios which can provide effective technical support for the performance evaluation of relay protection. From the perspective of the time sequence cooperation logic of relay protection devices, the cooperation relationship between protection devices, and the dimension of multi-scenario testing, this paper proposes the design and simulation method of relay protection simulation modules. The proposed method can meet the simulation requirements of various relay protection, and has passed the simulation test.

Prediction of Large-Scale Renewable Energy Access under Steady State of Electric Power System

Mingrun TANG, Ruoyang LI, Muran LIU, Xiaoyu CHENG, Yao LIU, Shuxia YANG

2025, 58(2):  126-132.  DOI: 10.11930/j.issn.1004-9649.202405113

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The large-scale increase in renewable energy generation and the superposition of various uncertainties have posed severe challenges to power systems. This paper studies representative energy sources, analyzes the factors affecting the large-scale integration of renewable energy under power system stability conditions, screens key factors based on grey correlation analysis and XGBoost, and constructs a prediction model for the large-scale integration of renewable energy. The proposed model is verified by a regional power system. The results show that the proposed is feasible and can provide a reference for the reasonable and effective power planning of new power systems.

New Solution for Photovoltaic Station Collector Line Protection Based on Comprehensive Harmonic Drive

Jiandong WO, Wulue PAN, Yuehui LI, Jiayi WU

2025, 58(2):  133-139.  DOI: 10.11930/j.issn.1004-9649.202404055

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A new protection scheme for the collection line of photovoltaic power station based on comprehensive harmonic drive is proposed. Firstly, the harmonic sources and characteristics of the collection line fault in photovoltaic power station are analyzed, and the current harmonics are obtained by fiber optical current transformer (FOCT), and the harmonic characteristic weight is calculated based on the nondominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) to improve the comprehensive harmonic characteristic of fault current. At the time, the high-order harmonic start-up criterion and the comprehensive harmonic action criterion are constructed. The simulation study is carried out for different fault conditions, and the effectiveness of proposed method is verified.

Power System

Robust Optimization of Hosting Capacity of Distributed Photovoltaics in Distribution Network Considering Adjustable Characteristics of 5G Base Station

Tong SUN, Shenxi ZHANG, Yi CAO, Jiachen CAO, Haozhong CHENG

2025, 58(2):  140-146.  DOI: 10.11930/j.issn.1004-9649.202403032

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With distributed photovoltaics access massively, which is characterized by stochasticity and volatility, has posed new technical challenges to the safe and reliable operation of the distribution network. To evaluate and improve the hosting capacity of distributed photovoltaics in distribution network, the article proposed a robust optimization method for the hosting capacity of distributed photovoltaics in the distribution network, which considers adjustable characteristics of 5G base stations. Firstly, a 5G base station adjustable characteristics model is constructed, which considers the communication load migration and the dynamic power backup of the energy storage. Secondly, a robust optimization model of the maximum hosting capacity of distributed photovoltaics in the distribution network with 5G base stations is established. Then, the model is solved using an increasingly tight linear cut algorithm combined with a column-and-constraint generation algorithm. Finally, the effectiveness of the model is verified on an improved IEEE 33-node distribution network, and the effects of source-load uncertainty, 5G base station communication load migration, and dynamic energy storage backup on the maximum access capacity of distributed photovoltaics in distribution network are analyzed.

A New Method for Fault Line Selection of Photovoltaic Power Station Collection Lines Based on TEO Energy

Ran ZHENG, Jiayi WU, Haoliang DU, Wulue PAN

2025, 58(2):  147-153.  DOI: 10.11930/j.issn.1004-9649.202404081

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Carrying out rapid fault selection of PV power station collection lines is of great significance to ensure the stable operation of the system. A fault method for PV power station collection lines based on the zero-sequence current gradient Teager energy operator (TEO) is proposed. The zero-sequence current sequence model of the collection line for single-phase ground fault is established, and the distribution law of the zero-sequence current and voltage as well as the output characteristics of PV power supply during the fault period are analyzed. The TEO is used to calculate the energy value of the zero-sequence current gradient, and the threshold is based on the difference in energy values between the fault line and the non-fault line measurement points. A fault selection criterion is proposed, and a PV power station line model is built. Simulation verification shows that the proposed method has good selection effect under different fault positions, grounding resistances, unit outputs, and noise interference scenarios.

Multi-energy Optimal Scheduling of Industrial Parks Considering Green Certificate - Carbon Trading Mechanism and Hydrogen Compressed Natural Gas

Wenjun XU, Gang MA, Yunting YAO, Yuxiang MENG, Weikang LI

2025, 58(2):  154-163.  DOI: 10.11930/j.issn.1004-9649.202405087

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As the main body of high energy consumption and high emissions, the industrial park is of great significance for China to cope with climate change and achieve sustainable economic and social development in low-carbon transformation. This paper proposes a multi-energy optimal scheduling model for industrial parks considering the green certificate-carbon trading mechanism and hydrogen compressed natural gas (HCNG). Firstly, a joint operation model of P2G-CCPP-HCNG is established for the park. Then, the trading rules of the low-carbon market are perfected through introducing the ladder carbon-green certificate trading interaction mechanism. Secondly, an incentive demand response model considering production quality and energy-use comfort is established. Finally, the MATLAB is used to solve the minimum total daily cost of the park, and eight scenarios are set up to verify the proposed model. The results of case study show that the proposed optimal operation method can effectively reduce the carbon emissions of the park, improve the wind and PV power consumption rate, and fully tap the demand response capability to promote the sustainable green development of the industrial parks.

Distributed Low-Carbon Economic Dispatch for Integrated Energy System Based on Homomorphic Encryption

Jingcheng HU, Yunhao FAN, Tong ZHU, Zhenping CHEN

2025, 58(2):  164-175.  DOI: 10.11930/j.issn.1004-9649.202404069

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To address the privacy leakage problem in the distributed scheduling process of the integrated energy system (IES), a fully consensus low-carbon economic dispatching method based on homomorphic encryption is proposed with consideration of the power-constrained characteristics of the distributed scheduling nodes. Firstly, based on the power analysis of supply units and energy-use loads in the system, a dispatching model of energy system with comprehensive economic and low-carbon performance is established, and a fully-distributed consensus low-carbon economic dispatching algorithm is proposed by introducing the supply-demand mismatch state estimation variables. And then, the homomorphic cryptography is used to design the state exchange strategy to ensure that the nodes safely exchange information with neighbors without disclosing their private data. Also, the homomorphic cryptography technology allows operations to be performed directly on the ciphertext and ensures that the decrypted results are consistent with the direct computation results of the plaintext, thus ensuring the accuracy of the low-carbon economic scheduling. Finally, the effectiveness of the proposed scheduling algorithm is verified using numerical simulation.

CGAN-Based Load Scenario Generation under Typhoon Weather

Pingping LUO, Ao SHENG, Jikeng LIN, Zhongyue WANG, Qiben LI, Ping ZHOU

2025, 58(2):  176-185.  DOI: 10.11930/j.issn.1004-9649.202405076

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The violent fluctuation of power load level under typhoon weather threatens the power balance of power grid. Therefore, load scenario generation under typhoon weather conditions has attracted increasing attention from power supply companies. A load scenario generation algorithm based on conditional generative adversarial network (CGAN) model for typhoon weather is proposed. Firstly, considering the fact that the typhoon samples have the characteristics of scattered landing locations, different duration periods and different grades, a load sample classification and label setting method for typhoon weather is proposed. Then, a sample expansion strategy based on conditional probability is proposed to expand the sample set to solve the problem of scarce load samples under typhoon weather. Finally, in order to further improve the actual effectiveness of the sample set, based on the idea of migration training, the load samples under normal weather are firstly used to train the CGAN, and then the typhoon sample sets are applied to train CGAN. After the model training is completed, the corresponding load scenarios can be quickly generated by inputting random noise and typhoon labels. The effectiveness and advancement of the proposed model and algorithm are verified by data set from a practical power system.

Capacity Prediction Model of Lithium-Ion Batteries Based on Transfer Entropy and JS-BP Neural Network

Xiaozhong WU, Lihua XIAO, Chao TONG, Xiangyang XIA, Ling YUAN, Xing GAN, Zhiwen JIANG, Xiangyuan HUANG

2025, 58(2):  186-192, 215.  DOI: 10.11930/j.issn.1004-9649.202310039

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Accurately predicting the available capacity of lithium-ion batteries is critical to ensuring the safe operation of energy storage systems. Therefore, this paper proposes a method for predicting the capacity of lithium-ion batteries in energy storage systems based on transfer entropy and JS-BP neural networks. Based on an analysis of the information entropy of relevant parameters of the energy storage batteries, the health factors that have a significant impact on the available capacity of batteries are selected, and a prediction model for the available capacity of batteries is established by combining the selected healthy factors with the JS-BP neural network. Finally, a comprehensive analysis is carried out based on the aging datasets from NASA and the battery aging experimental platform, and the results show that the proposed method has a high prediction accuracy of battery capacity, and the error indicators MAE and RMSE are at a low level, which verifies the accuracy of the model.

Distributed Coordination Optimization for Economic Operation of the Multi-Microgrid System Based on Improved Linearization ADMM

Kun HUANG, Ming FU, Jiaxiang ZHAI, Haochen HUA

2025, 58(2):  193-202.  DOI: 10.11930/j.issn.1004-9649.202308028

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Traditional centralized optimization strategies for multi microgrid systems have the problem of long computational time, while the distributed optimization strategies can effectively reduce the solving time. However, the efficiency of distributed optimization algorithms represented by the alternating direction method of multipliers (ADMM) depends on the difficulty of solving the Lagrangian augmented function of the objective function, making it difficult to apply to complex multi microgrid systems. Therefore, this article proposes a distributed coordination optimization scheme for multi-microgrid systems based on the inexact generalized alternating direction method of multipliers with defined proximate terms (IGADMM-IPT). Firstly, a hierarchical optimization architecture for the multi-microgrid system and a dynamic model for each adjustable device are constructed. Then, based on the difference between renewable energy output and load demand, and the adjustable equipment output thresholds, the shared power generation and energy storage capacity of each microgrid are determined. And then, based on the lowest operating cost of the multi-microgrid system, a global shared objective function is constructed, and the optimization problem is iteratively solved using IGADMM-IPT. Finally, simulation is conducted in a scenario where eight microgrids and a group of directly connected devices are interconnected through a common bus. The results show that using IGADMM-IPT to obtain the lowest operating cost optimization solution for the multi-microgrid system within one day requires 21.38% less time than ADMM.

Visualized Estimation of Composite Insulator Pollution Status of Transmission Line Based on Reflective Multispectral Imaging

Ming REN, Qianyu LI, Changjie XIA, Ming DONG

2025, 58(2):  203-215.  DOI: 10.11930/j.issn.1004-9649.202311070

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The timely and accurate online estimation for composite insulators of transmission lines can effectively prevent pollution flashover accidents. A visualized estimation method of composite insulator pollution status of transmission line was proposed in this paper. Firstly, a semi-automatic registration method for multisource reflective spectral images was constructed by combining image registration algorithm and target area selection, which solved the inherent image registration problem of multi-lens camera. Secondly, model pre-training was conducted through shooting artificial contaminated samples using the low cost, lightweight, and high imaging quality multi-lens multispectral imaging equipment, and further transfer training was conducted through real natural contaminated samples to construct a pollution grade diagnosis model of composite insulation material surfaces. Finally, the actual pollution status of transmission line composite insulators was measured and analyzed under different shooting conditions using the unmanned aerial vehicle platform. The results indicate that the pollution grade classification accuracy for artificial and natural contaminated samples is 95.3% and 87.8%, respectively, and the pollution grade classification accuracy for actual transmission line composite insulators can reach up to 90% with pollution distribution area clearly displayed. The feasibility of transmission line insulator pollution grade estimation and pollution distribution visualization diagnosis based on reflective multispectral imaging technology is verified, which can provide a new technique for status inspection and maintenance decision of transmission line insulators.

Two-Layer MPC Virtual Inertia Control Strategy for Small-Scale Variable-Speed Pumped Storage Unit with Full-Size Converter

Changhao XU, Weidong GUAN, Yue WANG, Jinshuai ZHANG, Peng WANG, Ning ZHOU, Bowen SHANG

2025, 58(2):  216-226.  DOI: 10.11930/j.issn.1004-9649.202311005

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The development of miniature variable-speed pumped storage on the distribution side is conducive to enhancing the ability of the distribution network to accomodate renewable energies in a more environmentally friendly way. In this paper, a two-layer model predictive control (MPC) virtual inertia control strategy for variable-speed pumped storage unit with full-size converter is proposed. The strategy contains a standard-layer MPC and an auxiliary-layer MPC. The standard-layer MPC generates minimized frequency deviation signals based on a determined system prediction model and passes them to the auxiliary-layer MPC, which considers the stochastic nature of the PV generation with the goal of tracking the frequency deviation predicted by the standard-layer MPC and generates both the power and the guide vane control signals. The simulation of a test system containing a pumped storage unit with full-size converter shows that the proposed control strategy has good frequency-regulating performance, which is helpful to enhancing the PV accomodation capability of the distribution networks.