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Green Energy and Resources 2024年第2期2卷

作者： Wang, Xinyu Li, Zibin Luo, Xiaoyuan Zhang, Yu Guan, Xinping School of Electrical and Control Engineering Yanshan University Qinhuangdao 066003 China Intelligent Electric Power Grid Key Laboratory of Sichuan Province Sichuan Chengdu 610095 China School of Electrical Engineering Korea University Seoul 02841 South Korea School of Electronic and Electric Engineering Shanghai Jiaotong University Shanghai 200240 China

With the increasingly severe problem of air pollution and energy crisis, new energy power generation technology in ship has quickly become the focus of attention. Compared with traditional ships, hybrid shipboard microgrid systems can achieve pollution-free, renewable and high use value. However, the integration of electricity-gas-heat in hybrid energy shipboard microgrid system also poses challenges to current optimization methods. Therefore, this paper develops a bi-level optimization dispatch model for hybrid shipboard microgrid system based on multi-objective particle swarm optimization algorithm. Taking the diesel generators, photovoltaic generation system, energy storage system (ESS) and thermal energy storage equipment into account, a hybrid shipboard microgrid system model considering electricity-gas-heat coupling is constructed. Based on this, a bi-level optimization dispatch model is established to reduce total cost, GHG (GHG) emissions and lifespan loss of ESS. The upper-level model achieves the optimization dispatch of power generation equipment and loads;a lower-level optimization model with the goal of reducing the lifespan loss of ESS is constructed. The improved multi-objective and single-objective particle swarm optimization algorithms are introduced to find the optimal dispatch solutions for bi-level optimization dispatch model. Finally, simulation results show that the proposed optimization method can not only reduce the cost and GHG emissions by 8.7% and 10.9%, but also improve the cycle life of ESS by 9.2%. © 2024 The Author(s)

关键词： Energy storage system GHG emissions Particle swarm optimization

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Rationally designed In3+ doping in Li3V2(PO4)3/C cathodes for enhanced kinetics and cycling stability

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Electrochimica Acta 2025年 531卷

作者： Wang, Bangqian He, Jianjun Zhu, Congcong Huang, Bangcai Chen, Haijun Guo, Shan Wu, Fuzhong Liu, Guanghui Deng, Yong Dai, Xinyi Guizhou Province University Key Laboratory of High Performance Battery Materials College of Materials and Metallurgy Guizhou University Guiyang550025 China Power Dispatching and Control Center of China Southern Power Grid Guangzhou510530 China

The monoclinic Li3V2(PO4)3 cathode demonstrates significant promise for high-performance lithium-ion batteries (LIBs) technologies, primarily due to its outstanding energy density and enhanced safety performance. However, its practical application was hindered by inherent limitations, particularly, intrinsically restricted electron mobility and pronounced capacity fading during cycling at voltages exceeding 4.6 V. To overcome these challenges, this study employs a facile sol-gel method to synthesize carbon-coated Li3V2(PO4)3 materials while introducing In3+ substitution for partial V3+ sites. Electrochemical evaluations substantiate that the optimal In3+ doping level of Li3V2(PO4)3 (LVP/C-In0.09) exhibits significantly enhanced performance. Specifically, the LVP/C-In0.09 sample delivers remarkable capability, sustaining 131.4 mAh g−1 at 10 C while maintaining 88.4 % of initial capacity after 500 cycles, surpassing the undoped LVP/C sample (initial capacity: 106.5 mAh g−1;retention: 75.7 %). XRD analysis indicates that incorporating In3+ effectively broadens Li+ diffusion channels. XAFS characterization reveals that the unit cell expansion is attributed to an increased V-V interatomic distance. Additionally, the controlled In3+ doping effectively decreases the electrochemical resistance while substantially improving Li+ diffusion kinetics. This study proposes a potential strategy to boost the practical application of Li3V2(PO4)3 in LIBs. © 2025

关键词： Lithium-ion batteries

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A robust line parameter identification method based on LSTM and modified SCADA Data 4

A robust line parameter identification method based on LSTM ...

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4th IEEE Conference on Energy Internet and Energy System Integration, EI2 2020

作者： Que, Lingyan Yang, Liqiang Qian, Haifeng Shen, Jianqiang Zhang, Lei Xu, Feiyang Ma, Jing Chen, Chao Xue, Ancheng State Grid Zhejiang Electric Power Company Limited Electric Power Dispatching Control Center Hangzhou China Huzhou Power Supply Company State Grid Zhejiang Electric Power Company Limited Huzhou China North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source Beijing China

ISBN: (纸本)9781728196060

Transmission line parameters are the basis of power system calculation, and their accuracy directly affects the safe and stable operation of the system. At the same time, with the improvement of computing power and the rapid growth of the amount of power grid operation data, deep learning has developed rapidly and applied in power systems. However, there is little research on line parameter identification combined with deep learning. Therefore, from the perspective of line model and deep learning, combined with median estimation and modified Supervisory control And Data Acquisition (SCADA) data based on line model, this paper proposes a robust method for parameter identification of transmission line based on Long Short-Term Memory (LSTM) and modified SCADA data. Speciffically, the overall process of the line parameter identification method based on LSTM is given first. Then the settings of the proposed method are introduced in detail. Combined with the line model, a modified input data based on the SCADA data is constructed, and a multi-case training set considering different operating conditions and different line parameters is established. According to a large number of tests, the optimized parameter configuration of the LSTM is given. Finally, the median estimation is used to give the parameter identification results. Case studies in simulated and measured data verify the effectiveness and robustness of the proposed method. © 2020 IEEE.

关键词： Electric lines

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Feature Selection Method for Non-intrusive Load Monitoring with Balanced Redundancy and Relevancy

Feature Selection Method for Non-intrusive Load Monitoring w...

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2020 IEEE/IAS Industrial and Commercial power System Asia, I and CPS Asia 2020

作者： Bao, Sheng Zhang, Li Li, Wensheng Sun, Donglei Zhang, Boyi Han, Xueshan Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China Economic Technology Research Institute State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9781728143033

Non-intrusive load monitoring(NILM) has become a key technology in the power Internet of Things and an important information source of load characteristics analysis. Whether the selected features are appropriate determines the effectiveness of load identification in NILM. In order to reduce redundance and improve relevance of the selected features, a feature selection method which integrates mutual information and Relief-F algorithm is proposed. Based on the analysis of the power consumption characteristics of various electrical appliances, the prospective components of the initial feature set for NILM is discussed. From the perspective of balancing redundancy and relevancy, the redundant features are removed by using mutual information algorithm, the relevance of the features are sorted by using Relief-F algorithm, and then the optimal feature subset is obtained. A k-NN identification algorithm is applied to test the effectiveness of the feature selection methods. The simulation results show that the proposed method is superior to other filter feature selection methods in robustness and universality, and can significantly improve the identification accuracy. © 2020 IEEE.

关键词： Redundancy

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Operation Risks Analysis and Stability control System Optimization for the Junction Area of Multiple HVDC Sending System

Operation Risks Analysis and Stability Control System Optimi...

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International Conference on power System Technology (powerCON)

作者： Yukun Zhu Yihua Zhu Dongxu Chang Jiawei Yu Shengnan Li Yong Chen State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China Electric Power Research Institute Yunan Power Grid Co Ltd Kunming China

ISBN: (纸本)9781665407380

The successive commissioning of HVDC projects has enabled many substations or areas to connect with multiple sending ends of HVDC simultaneously, forming a junction area of multiple HVDC sending system. The operation risks in these areas have also changed accordingly. This paper focuses on the safe and stable operation of the junction area of multiple HVDC sending system, analyzing the current operation risks of the junction area and the adaptability of the regional stability control strategies at first. Then, an optimization scheme including regional stability control strategy design and structure configuration for the junction area is put forward, whose feasibility is verified through the stability control system of Huangping area, which is a typical junction area located in the sending ends of Jinguan-Guizhong and Xinsong-Dongfang HVDC. The Successful application in Huangping area also proves that the stability control system optamization scheme for junction area of multiple HVDC sending system proposed in this paper has good completeness and scalability, that is of great significance to the design for the stability control system of similar junction area.

关键词： Substations HVDC transmission Systems operation Scalability power system stability control systems Stability analysis

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Research on Automatic Construction and Correlation Method of Virtual and Real Loops in UHV DC control and Protection System

Research on Automatic Construction and Correlation Method of...

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Sustainable power and Energy Conference (iSPEC)

作者： Yuanhong Lu Qi Guo Zhijiang Liu Shuyong Li Haiping Guo Guanming Zeng State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&D Centre Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid CSG Key Laboratory for Power System Simulation Electric Power Research Institute Guangzhou China

ISBN: (纸本)9781665414401

At present, in the research on virtual and real loops of control and protection systems, scholars at home and abroad are mainly focusing on the field of AC digital substations, and there is less research on the virtual and real loops of UHV DC control and protection systems. Aiming at this problem, this paper proposes an automatic construction and correlation method for virtual and real loops of UHV DC control and protection system. This method automatically constructs the real circuit by analyzing the design drawings and the optical cable inventory, analyzing the DC visualization program to automatically construct the virtual circuit, and then automatically correlates the virtual and real circuits based on the graph depth traversal algorithm. The practical application in UHV DC engineering shows that this method can help relevant personnel complete the automatic construction and correlation of virtual and real loops, and improve the convenience of operation and maintenance of the UHV DC control and protection system.

关键词： Visualization Correlation Substations Optical design Conferences Focusing Maintenance engineering

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Adjustment Oriented Electricity Tariff Recommendation Based on Typical Customers

Adjustment Oriented Electricity Tariff Recommendation Based ...

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2020 IEEE/IAS Industrial and Commercial power System Asia, I and CPS Asia 2020

作者： Xu, Guangda Liang, Jun Sun, Donglei Zhang, Li Li, Xueliang Han, Xueshan Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China Economic Technology Research Institute State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143033

Tariff recommendation is an important marketing means for retailers in electricity market. Based on the power consumption data acquired by the advanced metering infrastructure, tariff recommendation can not only match customers with appropriate tariff but also guide customers to adjust power consumption strategy. In this paper, an adjustment oriented electricity tariff recommendation method based on typical customers is proposed. Fuzzy clustering algorithm is applied to power consumption data of appliances to extract the consumption feature of each kind of appliance. Then the decision tree is constructed, which correlate the class features of appliances with clusters of customers. Pre-pruning decision tree is deployed together with use of depth-first search to exclude meaningless nodes of the decision tree, so that the typical customer set is determined. The tariff recommendation model is constructed aiming at minimum electricity bill, which credits to optimize benchmark strategy of power consumption for typical customers. The model is solved by particle swarm optimization. Simulations show that the proposed method enables customers to understand the adjustment signal revealed by the tariff, and results in electricity bill reduction due to participating in demand response as retailers expected. © 2020 IEEE.

关键词： Decision trees

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Defect Analysis of power System Secondary Equipment Based on Cluster Analysis and Association Rule

Defect Analysis of Power System Secondary Equipment Based on...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Maoran Zheng Jinshuang Mu Zhanjun Gao Zhaohui Chen Jiang Yu Zhenghong Li China Southern Power Grid Co Ltd. Guangzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

In order to effectively improve the operation level of secondary equipment in the power system, based on the historical defect data of the secondary equipment, this paper takes the mining of the correlation between the secondary equipment defect data as the starting point, it proposes a method that combines cluster analysis and association analysis. First, this paper analyzes the basic ideas of cluster analysis and association analysis, then establishes the defect analysis model of the secondary equipment of this method. In the model, it uses cluster analysis to classify defect data firstly, clustering related defect data into a cluster, then uses association rules for further defect analysis. The result shows, this method can quickly and effectively dig out the correlation between defect data, able to further analyze the family defects of secondary equipment, it can provide certain guidance for equipment maintenance and daily operation.

关键词： Electrical engineering Analytical models Correlation Automation Clustering algorithms Maintenance engineering Data processing

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Distributed Online Optimization for Charging and Discharging of Plug-in Electric Vehicles

Distributed Online Optimization for Charging and Discharging...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Haiming Xiong Ming Chi Zhi-Wei Liu Dandan Hu Liang-Liang Zhu Cheng Jiang Jun-Ping Gui Yao Rao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China School of Management South-Central University for Nationalities Wuhan China Nari Group Corporation State Grid Electric Power Research Institute Nanjing China State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Company Limited Wuhan China

The increasing number of uncoordinated charging and discharging for plug-in electric vehicles (PEVs) poses new challenges to the operation of the distribution network. We introduce a dynamic price mechanism so that charging at peak load will lead to an increase in cost. Then, a distributed online charging and discharging scheduling scheme for PEVs based on the dynamic price mechanism is proposed, considering the minimization of charging cost and battery degradation cost. Unlike most of the existing studies that require the future information of PEVs to schedule charging, the proposed algorithm can solve the scheduling problem for PEVs by taking advantage of a distributed alternating direction method of multipliers (ADMM). Simulation results demonstrate the effectiveness and correctness of the proposed scheduling scheme.

关键词： Plug-in electric vehicles Schedules Costs Heuristic algorithms Simulation Dynamic scheduling Minimization

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power System Small-signal Stability Assessment Model Based on Residual Graph Convolutional Networks

Power System Small-signal Stability Assessment Model Based o...

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作者： Yinsheng Su Mengxuan Guo Haicheng Yao Lin Guan Jiyu Huang Siting Zhu Zhi Zhong Department of Power System Operation China Southern Power Grid School of Electric Power South China University of Technology Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System

Small-signal stability(SSA) is important to power system security.A data-driven approach is established for rapid prediction of the power system oscillation *** key of the approach is the Graph Convolution Networks(GCN) with residual mechanism,which works to aggregate features from high-dimension steady-state operation information and is denoted as ResGCN(RESidual GCN) in the *** residual mechanism helps to overcome the network degradation *** the oscillation frequency and damping ratio of multiple modes can be predicted by the proposed *** performance of the proposed scheme as well as its adaptability to the power system topological changes is verified on the IEEE 39 Bus system.

关键词： Small-signal Stability Graph Deep Learning Graph Convolution Networks(GCN),Residual mechanism

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