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A composite SCUC decision-making method considering source-network-load collaborative optimization in typhoon disasters

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Dianli Xitong Baohu yu Kongzhi/power System protection and control 2025年第10期53卷 33-44页

作者： Yang, Nan Chan, Xuezhen Zhang, Zhi Xu, Dan Hao, Juncong Wang, Jinxin Huang, Yuehua Zhang, Lei Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station China Three Gorges University Yichang443002 China State Grid Corporation of China Beijing100031 China China Electric Power Research Institute Beijing100192 China

With the increasing frequency of typhoon disasters due to global climate change, the failure rates of power equipment have risen significantly, posing a serious threat to the safe and reliable operation of power grids. To enhance the resilience of power systems, a composite security-constrained unit commitment (SCUC) decision-making method when there are typhoon disasters is proposed, incorporating source-network-load collaborative optimization. First, based on historical typhoon data and the Rankine wind farm model, wind turbine output and line fault models are constructed. Then a set of uncertainty scenarios for fault decisions is created using the state sampling method. Next, separate decision models for SCUC, load shedding, and line restoration are developed for different response strategies. A robust optimization approach is employed to address the uncertainty of line faults, and is introduced as a virtual "typhoon disaster" agent in a multi-agent game framework, where each of the above decision models serves as an agent. Finally, an iterative search method is applied to solve the model. Simulation results demonstrate that the proposed approach can minimize load shedding while ensuring economic operation of the system, thereby improving the resilience of the power system during typhoon disasters. © 2025 power System protection and control Press. All rights reserved.

关键词： Electric power transmission networks

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power coordinated strategy of vehicle-to-microgrid integrated hybrid AC/DC microgrids considering electric vehicles as flexible energy storage

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Sustainable Energy, grids and Networks 2025年 43卷

作者： Wang, Hao Yan, Jiawei Kang, Boyang School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Jiaozuo China Jiaozuo Power Supply Company State Grid Henan Electric Power Company Jiaozuo China

Increasing adoption of electric vehicles (EVs) entrance to hybrid ac/dc microgrids (HMGs) would provide flexible energy storage sources (FESSs) to perform vehicle-to-microgrid (V2MG) operation. However, especially in islanded mode, the state of charge (SOC) of traditional energy storage unit (ESU) approaching the critical value of charge/discharge would inevitably lead to unreliable power supply. To solve this problem, a power coordinated strategy of V2MG integrated HMGs considering EVs as FESSs is proposed in this paper. First, a joint energy storage sources (JESSs) dynamic grouping method is presented for traditional ESU and scaled electric vehicle groups (EVGs) within HMGs containing multiple subgrids, which divides ESU and EVGs into panels and sets at the same time scale. Then, the operation modes and conditions of HMGs are classified according to the power surplus/deficient state of each subgrid. Further, this paper designs response priority based on real-time grouping of JESSs to balance the SOC of ESU and formulates power coordination control strategies for abnormal SOC of ESU and subgrid power overlimit, among which the FESSs provide auxiliary service for system power regulation. Finally, the results of the simulation analysis show that the proposed strategy can achieve coordinated regulation of traditional ESU and EV as FESSs in islanded microgrids, reducing the system's dependence on traditional ESU and improving the power supply reliability of microgrid systems. © 2025 Elsevier Ltd

关键词： Hybrid vehicles

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Circulating current suppression in the modular interleaved parallel active front-end of energy storage converters

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Dianli Xitong Baohu yu Kongzhi/power System protection and control 2025年第10期53卷 78-86页

作者： Zhang, Guopeng Hua, Sen Liu, Bo Zheng, Zheng Tao, Haijun Li, Changzhi School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454003 China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Jiaozuo454003 China Queshan County Power Supply Company State Grid Henan Electric Power Company Zhumadian463200 China

To address the zero-sequence circulating current issue caused by modular interleaved parallel connections in active front-ends of energy storage converters connected in parallel on both AC and DC sides, an improved circulating current suppression strategy based on a deadbeat algorithm is proposed. First, the effect of interleaved modulation among parallel modules on circulating current is analyzed. Second, a mathematical model of the system is established in the three-phase stationary coordinate system, along with an equivalent circuit of circulating current in the interleaved parallel system. Then, a circulating current controller is designed, where the control algorithm derives the zero-vector modulation parameters for each module by calculating the magnitude of the circulating current. Next, the zero vectors in the space vector pulse width modulation (SVPWM) process of the respective modules are adjusted to suppress the circulating current. Finally, experimental results verify that the proposed method can effectively suppress circulating current and achieve current sharing control, improving system efficiency by 2.1%. © 2025 power System protection and control Press. All rights reserved.

关键词： Electric power system protection

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method 26

Path Planning for Distribution Network Robots with Adaptive ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Zhang, Baichao Chen, Xin Chen, Jinge Li, Jinbin Wang, Xiaokai Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan430077 China

ISBN: (纸本)9798331521950

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. Simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications. © 2025 IEEE.

关键词： Motion planning

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Fault diagnosis method for ship power-system DC–DC converter using augmented WPD and multi-branch CNN-BiLSTM network

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Journal of the Franklin Institute 2025年第9期362卷

作者： Ren, Yuanjie Zhang, Lanyong Shi, Peng Peng, Huimin College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China School of Electrical and Mechanical Engineering The University of Adelaide SA5000 Australia State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Jiangsu Nanjing211106 China

Direct current (DC) –DC converters are indispensable energy conversion devices in medium-voltage DC power systems of ships. Herein, the fault diagnosis problem of bidirectional DC–DC converters is investigated. Considering that the fault diagnosis of bidirectional DC–DC converters requires the effective combination of information from multiple diagnostic signals and differences in characteristic data in different time scales, a parallel stacking of multiple branches based on enhanced wavelet packet decomposition technology is proposed as a hybrid model of a convolutional neural network and bidirectional long short-term memory network. First, a multi-input method is used to extract effective features in the sequence data. Second, a multi-model fusion processing framework is used to perform fault diagnosis analysis on the DC–DC converter. Finally, the squeeze and excitation attention mechanism is used to weight all types of fault features and adaptively obtain them. The important weights of the classification feature maps learned by different branches generate fault classification results. Experimental results reveal that the proposed method can extract highly discriminative features from raw data and exhibits robustness in noisy environments. © 2025 The Franklin Institute

关键词： Convolutional neural networks

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Bayesian Network Based Imprecise Probability Estimation Method for Wind power Ramp Events

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Journal of Modern power Systems and Clean Energy 2021年第6期9卷 1510-1519页

作者： Yuanchun Zhao Wenli Zhu Ming Yang Mengxia Wang Key Laboratory of Power System Intelligent Dispatch and Control Shandong University State Grid Jinan Power Company

Although wind power ramp events(WPREs)are relatively scarce,they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity *** this paper,an imprecise conditional probability estimation method for WPREs is proposed based on the Bayesian network(BN)*** method uses the maximum weight spanning tree(MWST)and greedy search(GS)to build a BN that has the highest fitting degree with the observed ***,an extended imprecise Dirichlet model(IDM)is developed to estimate the parameters of the BN,which quantificationally reflect the ambiguous dependencies among the random ramp event and various meteorological *** BN is then applied to predict the interval probability of each possible ramp state under the given meteorological conditions,which is expected to cover the target probability at a specified confidence *** proposed method can quantify the uncertainty of the probabilistic ramp event ***,by using the extracted dependencies and Bayesian rules,the method can simplify the conditional probability estimation and perform reliable prediction even with scarce *** results on a real wind farm with three-year operation data illustrate the effectiveness of the proposed method.

关键词： Bayesian network(BN) conditional probability imprecise Dirichlet model(IDM) imprecise probability wind power ramp events

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Review on Optimization of Nuclear power Development:A Cyber-Physical-Social System in Energy Perspective

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Journal of Modern power Systems and Clean Energy 2022年第3期10卷 547-561页

作者： Xinxin Yang Bin Cai Yusheng Xue School of Electrical Engineering Southeast UniversityNanjingChina State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChina State Key Laboratory of Smart Grid Protection and Operation Control NanjingChina

Nuclear power development is a complex issue spanning cyber,physical,and social systems that is essential to achieving energy security and climate *** the ongoing worldwide trend towards carbon neutrality,the positioning of nuclear power in energy mix should be *** paper aims to present a systematic review of current research on optimization of nuclear power *** concept of cyber-physical-social system in energy(CPSSE)is adopted,which provides a suitable perspective and enables the review of relevant studies to achieve some novel *** on the CPSSE,firstly,a research framework is established and the main research elements in optimization are identified,followed by a proposed conceptual risk-based optimization ***,current studies are analyzed and classified into four categories according to the research *** status quo and limitations are *** is found that the research results of nuclear-specific issues have not been well integrated into the optimization of nuclear *** a relatively reliable power supply,nuclear power is capable of maintaining power and electricity adequacy of the whole system,especially in the case of power shortage caused by long-period low output of renewable energy or extreme external *** superiority should not be ignored in the *** critical factors that should be further considered include disruptive technologies,nuclear safety,energy policies,and stakeholder ***,suggestions are given for future research.

关键词： Carbon emission carbon neutrality cyber-physical-social system in energy(CPSSE) comprehensive evaluation dynamic interactive hybrid simulation energy transition multi-objective optimization

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Decision Support System for Adaptive Restoration control of Distribution System

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Journal of Modern power Systems and Clean Energy 2022年第5期10卷 1256-1273页

作者： Lili Hao Yusheng Xue Ze Li Haohao Wang Qun Xu School of Electrical Engineering and Control Science Nanjing Tech UniversityNanjing 211816China State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChina State Key Laboratory of Smart Grid Protection and Operation Control NanjingChina State Grid Qingdao Power Supply Company QingdaoChina

Aiming at the high-dimensional uncertainties of restoration process, an optimization model for distribution system restoration control is proposed considering expected restoration benefits, expected restoration costs, and security risks of the overall restoration scheme. In the proposed model, the effect of security control on restoration process is actively analyzed considering the security control costs of preventive, emergency, and correction controls. A two-layer decision support framework for distribution system restoration decision support system(DRDSS) is also designed. The upper layer of the proposed framework generates the pre-adjustment schemes of operation mode for energized power grid by load transfer and selects the optimal pre-adjustment scheme and the corresponding partitioning scheme based on the partition adjustment results of each pre-adjustment scheme. In addition, it optimizes the spatial-temporal decision-making of the inter-partition connectivity. For each partition, the lower layer of the proposed framework pre-selects the units and loads to be restored according to the pre-evaluated restoration income, generates the table of alternative restoration scheme for coping with uncertain events through simulation and deduction, and evaluates the risk and benefit of each *** the uncertain events in the actual restoration process, the current restoration scheme can be adaptively switched to a sub-optimal scheme or re-optimized if necessary. Meanwhile, the proposed framework provides an information interaction interface for collaborative restoration with the related transmission system. A 123-node test system is built to evaluate the effectiveness and adaptability of the proposed model and framework.

关键词： Distribution system restoration pre-adjustment of operation mode load transfer dynamic partitioning risk and benefit security control

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method

Path Planning for Distribution Network Robots with Adaptive ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Baichao Zhang Xin Chen Jinge Chen Jinbin Li Xiaokai Wang Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan P. R. China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan P. R. China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

关键词： Electric potential Adaptation models Force Distribution networks Simulated annealing Manipulators Path planning Planning Collision avoidance Robots

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Pathway Planning of Nuclear power Development Incorporating Assessment of Nuclear Event Risk

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 500-513页

作者： Xinxin Yang Yusheng Xue Bin Cai School of Electrical Engineering Southeast UniversityNanjingChinaand they are also with State Grid Electric Power Research Institute(NARI Group Corporation)NanjingChina State Key Laboratory of Smart Grid Protection and Operation Control NanjingChina State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChina

The nuclear event risk(NER)is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development(NPD)to assess the benefits and risks of developing nuclear power more *** paper aims to explore the impact of nuclear events on NPD pathway *** influence of nuclear events is quantified as a monetary risk component,and an optimization model that incorporates the NER in the objective function is *** optimize the pathway of NPD in the lowcarbon transition course of power supply structure evolution,a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway(CEP);moreover,a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction(CER)component,and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies.A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway *** method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.

关键词： Low-carbon transition power supply structure evolution nuclear power development(NPD) quantitative analysis nuclear event risk evaluation

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