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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun Ram Machlev Qianchao Wang Juri Belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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Enhancing Autonomy Capability in Regional power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

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energy Engineering 2024年第9期121卷 2449-2477页

作者： Jie Ma Tong Zhao Yuanzhao Hao Wenwen Qin Haozheng Yu Mingxuan Du Yuanhong Liu Liang Zhang Shixia Mu Cuiping Li Junhui Li Planning and Assessment Center Department State Grid Henan Economic Research InstituteZhengzhou450000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Development Planning Department State Grid Henan Electric Power CompanyZhengzhou450000China Innovation Development Research Center State Grid Shanghai Energy Internet Research Institute Co.Ltd.Shanghai201210China State Grid Simulation Center China Electric Power Research Institute Co.Ltd.Beijing100192China

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power *** a novel power system model,the fundamental concept of Regional Autonomous power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of ***,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for ***,a regional energy Storage(ES)configuration strategy is *** strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES ***,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy *** final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on *** proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluct

关键词： Regional autonomous power grid distributed generation distributed energy storage regional planning strategy evaluation index

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Fault Diagnosis Method for DC Distribution Networks Based on Semitensor Product Bayesian Networks

Fault Diagnosis Method for DC Distribution Networks Based on...

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International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： He Wang Shiqiang Li Huanan Yu Jing Bian Bo Wei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

As distributed generators and new loads spread, grid operations have grown more complex, transitioning from AC to hybrid AC/DC and pure DC distribution grids [1] .

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Optimization Method of Shared energy Storage Configuration on Source-Grid-Load Side of power system

Optimization Method of Shared Energy Storage Configuration o...

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2023 International Conference on power system technology, powerCon 2023

作者： Li, Cuiping Liu, Yang Zhang, Tianxun Zhao, Zhiqiang Liu, Haojun Zhu, Xingxu Li, Zhi An, Chenyu Li, Junhui Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China Beijing Technology and Business University Beijing China State Grid Hami Power Supply Company Xinjiang Uygur Autonomous Region Hami Hami839000 China

ISBN: (纸本)9798350300222

With the rise of the application of sharing economy in various fields of power system, As a typical application of shared economy in the field of energy storage, the optimal allocation of shared energy storage on the source-network-load side has been a great topic. The problem dealt with in this paper is the configuration result of the source-grid-load energy storage system under the same control strategy. This paper designs an optimization method for the source-network-load side configuration of generalized shared energy storage in regional power grid: Firstly, according to the extensional usage scenario and demand of energy storage, the alternative set of shared energy storage configuration is constructed. Secondly, based on the profit model of shared energy storage, a power system source-network-load optimization scheduling strategy is proposed. Finally, a numerical example is carried out to prove the feasibility and efficacy of the suggested method. © 2023 IEEE.

关键词： Profitability

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Fault Location Method for Dc Distribution Network Based on Compressed Sensing Group Sparse Representation

SSRN

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SSRN 2024年

作者： Wang, He Liu, Yiqi Li, Shiqiang Yu, Huanan Bian, Jing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Ministry of Education Jilin Province Jilin132012 China

The common faults in a direct current (DC) distribution network consist of pole-to-pole faults and pole-to-ground faults. Under conditions of sparse configuration of measurement devices, existing fault location methods are unable to simultaneously locate pole-to-ground faults and pole-to-pole faults, and issues such as indistinct fault characteristics under the influence of transition resistance and noise are encountered. In response to these challenges, a fault location method for DC distribution networks is proposed based on compressed sensing group sparse representation. Firstly, the pole-to-mode transformation is utilized to convert the positive and negative pole electrical quantities of the DC distribution network into zero-mode and one-mode electrical quantities. Equivalent circuits for pole-to-ground faults and pole-to-pole faults are established separately, enhancing the fault characteristics corresponding to the two different short circuit faults. Secondly, the obtained impedance matrices for zero-mode and one-mode are constructed into a group sparse dictionary. By utilizing compressed sensing group sparse representation, the sparse current vector of high-frequency mode quantities is obtained, enabling the correct identification of fault types and accurate location of fault sections. Finally, a simulation model of the DC distribution network is built on the PSCAD platform to validate the effectiveness of the proposed fault location method. © 2024, The Authors. All rights reserved.

关键词： Electric power distribution

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Emergency Direct Current power Support for High-Percentage renewable energy systems Based on Deep Reinforcement Learning

SSRN

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SSRN 2024年

作者： Sun, Zhenglong Zhuang, Junzhi Chao, Pan Chao, Jiang Cai, Guowei The Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

As a low-cost emergency frequency control method, emergency direct current power support (EPS) is crucial for frequency stabilization of alternating current (AC)–direct current (DC) hybrid systems. In the context of highly integrated renewable energy sources, the uncertainty of AC-DC hybrid systems increases and the inertia decreases during the transition process, and the existing EPS methods face prominent adaptation and mismatch problems in meeting the frequency restoration requirements. To fill this gap, this study proposes a deep reinforcement learning (DRL)-based EPS frequency control method. The EPS decision is transformed into a Markov decision process (MDP) and solved using the proximal policy optimization (PPO) algorithm. This paper designs a DRL reward function for EPS while taking into account the EPS line overload and phase change failure problems. In order to solve the contradiction between limited observation and global safety, this paper designs a data characterization method based on mechanism fusion. Meanwhile, this paper develops an open-source power system simulation platform with DRL control function by using Python and the power system simulation software DIgSILENT/powerFactory to realize the EPS frequency stabilization decision based on DRL control. Through a case study of the IEEE 39-bus system and a real power system in Northwest China, it is verified that the proposed DRL-based EPS agent is able to quickly, accurately, and securely restore the frequency and reduce the frequency oscillations while considering the security constraints. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

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energy 2025年 328卷

作者： Yang, Mao Jiang, Renxian Yu, Xinnan Wang, Bo Su, Xin Ma, Chenglian The Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing100912 China

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively. © 2025 Elsevier Ltd

关键词： Iterative methods

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Peak shaving and power allocation strategies for optimizing lifespan and reducing energy loss in BESS

Peak shaving and power allocation strategies for optimizing ...

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4th energy Conversion and Economics Annual Forum (ECE Forum 2024)

作者： Gan Guo Junhui Li Gang Mu Gangui Yan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 People's Republic of China

ISBN: (数字)9781837242924

To manage the challenge of optimizing energy efficiency, an optimization strategy for power allocation in battery clusters is proposed to reduce energy loss in Battery energy Storage systems (BESS). Meanwhile, an improved peak shaving strategy is also proposed, aiming to increase the utilization of energy storage during the peak shaving process and reduce the ineffective utilization hours of energy storage, thereby extending the lifespan of the storage system. Furthermore, based on real-system data, a Simulink/Simscape model is developed to simulate component losses. Under a peak shaving scenario, the effectiveness of the strategy is demonstrated: it reduces the daily operational loss by 3.84% and improves energy round-trip efficiency by 0.4%.

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Effect of Positive Temperature Coefficient Materials on the AC Breakdown Strength and Dielectric Properties of Epoxy Composites 4th

Effect of Positive Temperature Coefficient Materials on the ...

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4th International Symposium on Insulation and Discharge Computation for power Equipment, IDCOMPU 2023

作者： Teng, Chenyuan Li, Shuo Zhou, Yuanxiang Zhang, Ling Zhang, Yunxiao Huang, Meng College of Information Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819974122

In operation, the negative temperature coefficient (NTC) electrical resistivity characteristics of polymeric insulating materials causes DC electric field distortion within power equipment insulation and lead to the failure. The doping of positive temperature coefficient (PTC) ceramic particles can suppress the NTC characteristics of the composites, but the electrical properties under AC voltages are unrevealed. In this paper, epoxy composites (0–20 wt%) doped with polydopamine-coated PTC particles were prepared, whose AC breakdown strength and dielectric properties were tested. The results shows that the decrease of AC dielectric strength is smaller than that under DC voltages after the doping PTC particles, and the coating of polydopamine can enhance the AC dielectric strength. As the doping content increases, the dielectric constant and tanδ of the epoxy composites increases, and the maximum increase of dielectric loss power is about 2% of the loss power caused by the current-carrying conductor. The research provides a theoretical basis for the optimization of the insulating performance of the equipment under the AC-DC composite voltages. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Epoxy resins

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Unbalanced Strategy of Vehicle-to-Grid on Evolution Game

Unbalanced Strategy of Vehicle-to-Grid on Evolution Game

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Annual Conference of Industrial Electronics Society

作者： Xinling Li Yuzhi Zhou Libin Tian Hongwei Li Wei Zhang Hongpeng Liu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

The utilization of vehicle-to-grid (V2G) technology is an environmentally friendly approach to achieve the transition towards low-carbon energy systems. However, it is still unknown what impact the V2G policy will have on the charging market of electric vehicles (EVs) and whether it is competitive with other electricity sales strategies. Aiming at the above problems, the electricity price model of EVs in electricity market including V2G strategy is established. Firstly, a 2–3 unbalanced strategy evolutionary game (2–3 USEG) model integrating vehicle-network interaction is proposed. The asymptotically stable equilibrium points of asymmetric evolutionary games for two groups with unbalanced game strategies are obtained. Multiple game strategies between the power grid enterprises (PGE) and New power supply entities (NPSE) are studied Besides, the corresponding asymptotic stability conditions are given by the Lyapunov stability criterion. Finally, the simulation proves that the ample implemented V2G strategy not only has strong competitiveness, but also enables the charging electricity price market of electric vehicles to have the “virtual high” electricity price adjustment ability.

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