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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

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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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Real-time Optimal energy Management of Combined Cooling, Heating and power systems Based on Knowledge conlusion

Real-time Optimal Energy Management of Combined Cooling, Hea...

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China International Electrical and energy Conference (CIEEC)

作者： Chunjiang He Yijian Wang Yang Xu Yang Cui State Key Laboratory of Power Grid Security and Energy Conservation China Electric Power Research Institute Beijing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin

Combined Cooling, Heating and power(CCHP) system is an important way to improve the efficiency of energy utilization and wind power consumption. In this case, increasing the operational flexibility of CCHP systems can help increase renewable energy consumption and reduce carbon emissions. So, it is necessary to provide real-time optimal energy management(OEM) for CCHP systems. In this paper. Firstly, a new training method is proposed for the LightGBM to improve the accuracy of real-time wind power prediction. In addition, to solve the nonlinear OEM of CCHP in real-time, a novel deep reinforcement learning algorithm-Soft Actor-Critic, is used in this paper. By combining the mechanism of CCHP with the reward function through knowledge fusion, the non-convex models can be translated into Markov Decision Processes(MDP), and then according to the Bellman optimal equation, the real-time optimized operation of the CCHP system is realized. Finally, the effectiveness of the proposed policy is verified by the actual operation data of a CCHP system in Northwest China.

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Coupling Analysis and Protection Design of Substation Grounding Grid and Surrounding Metal Pipe Grid

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Procedia Computer Science 2023年 228卷 1262-1269页

作者： Tao Wang Haojie Yuan Xuan Zheng Mengqing Song Chenglian Ma Shandong Electric Power Engineering Consulting Institute Co. Ltd. Jinan China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology (Ministry of Education) Northeast Electric Power University Jilin China

When the substation grounding grid and part of the underground metal pipe grid are close to each other, the two produce resistive coupling, and the current of the transmission line will flow through the grounding body and through the soil to the buried pipe grid, which may break through the anti-corrosion layer of the pipe grid, and may burn the body of the pipe grid in serious cases; the underground metal pipe grid will also have an impact on the parameters of the grounding grid. To this end, this paper is based on the numerical calculation method of field-path coupling, combined with the actual situation of substation, using CDEGS and ETAP software to simulate and analyze the current dissipation process when a short-circuit fault occurs in the substation after the ground grid is put into operation under multi-layer soil environment, and to study the influence of resistive coupling between the grounding grid and the surrounding metal pipe grid during an industrial frequency grounding short circuit. Optimize the structure of the grounding system so that the contact voltage across and step voltage is lower than the safety limit to protect the personal safety in the station; at the same time, take certain protective measures to slow down the corrosion of the pipe grid.

关键词： Grounding Grid Metallic Pipe Grid Field Circuit Coupling Ground Potential Rise Resistive Coupling

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Probabilistic prediction of short term wind power considering temporal and spatial dependence of prediction error

Probabilistic prediction of short term wind power considerin...

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作者： Yong Sun Zhenyuan Li Chaoyu Shi Baoju Li Mao Yang State Grid Jilin Electric Power Supply Company Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University)

The short-term probabilistic prediction of wind power has the characteristics of spatial dependence and time-series *** the two characteristics at the same time can improve the prediction level. In this paper, a probabilistic short-term wind power prediction model considering the temporal and spatial dependence of prediction error is proposed. Considering the coupling relationship between the two properties, the NWP(Numerical Weather Prediction) wind speed point prediction error in the historical period is hierarchical clustering, and the empirical distribution model is used to fit the probability distribution of the error under different wind conditions;the cumulative empirical distribution probability value corresponding to the NWP wind speed at the time to be predicted is bootstrap sampling;under the given confidence level, the possible wind speed at each time point to be predicted in the short term is calculated The power fluctuation range of the generator. The test results show that this method can ensure the statistical significance and fitting stability of the sub sample set at the same time, and improve the classification accuracy of the days to be predicted. Compared with considering a single property, the result of probability prediction performs better on multiple evaluation indexes.

关键词： Probabilistic prediction of short term wind power considering temporal and spatial dependence of prediction error

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Analysis of the Impact of Newly Built Grounding Grid on the Original Grounding Grid Based on the Method of Moments

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Procedia Computer Science 2023年 228卷 185-194页

作者： Letian Wang Zhen Liu Mengqing Song Xuan Zheng Chenglian Ma Shandong Electric Power Engineering Consulting Institute Co. Ltd. Jinan China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China

On the basis of the method of moments, the resistive coupling effect between the newly built grounding network. When the horizontal distance between two grounding networks of a substation changes, this original grounding network of a certain substation is analyzed. And establish corresponding soil models based on actual engineering soil resistivity data. Use the grounding grid analysis function of CDEGS software and powerstation software simulation software to simulate and calculate some parameters of the new and old grounding grids. The analysis parameters mainly include the grounding resistance, step voltage, and contact voltage of the grounding grid system. And the obtained parameter indicators are compared and analyzed with safety limits to determine the safety performance of the newly built grounding grid system in the substation. And the impact on the grounding performance of the original grounding network of the substation. Provide certain theoretical data support for the actual promotion of substation grounding network engineering.

关键词： Method of Moment Resistive Coupling Grounding Grid CDEGS powerstation

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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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Visualization of CNN Transient Voltage Classification Based on Feature Recognition and Enhancement

Visualization of CNN Transient Voltage Classification Based ...

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Sustainable power and energy Conference (iSPEC)

作者： Zhendong Li Yutian Liu Jun An Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781665414401

The deep learning algorithm represented by CNN has achieved remarkable results in complex feature extraction, classification and regression. Since the CNN adopts an end-to-end training process, the carrier of acquisition knowledge is a high-dimensional non-linear function, which is hard to understand by humans. Therefore, it is difficult to be widely used in online decision-making engineering scenarios such as the fast assessment of power system transient voltage stability. In this paper, the key input elements extracted by CNN are identified by Grad-CAM, and the key features captured by CNN in the assessment process are enhanced based on AM, so as to finally obtain the visual expression of key areas and variables of the original input data. Besides, a sample construction method based on single line diagram is proposed to improve the visualization effect of Grad-CAM and AM. Simulation results and analyses of IEEE 39bus test system demonstrates the effectiveness of the proposed method.

关键词： Training Visualization Simulation Data visualization Voltage power system stability Feature extraction

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Short-term Optimized Operation of Multi-energy power System Based on Complementary Characteristics of power Sources

Short-term Optimized Operation of Multi-energy Power System ...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Xiao, Bai Zheng, Jia Yan, Gangui Shi, Yonggang Jiao, Mingxi Wang, Yao Dong, Ling Wang, Maochun Yang, Hongzhi Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Tonghua Power Supply Company State Grid Jilin Electric Power Co. Ltd. Tonghua China Changchun Power Supply Company State Grid Jilin Electric Power Co. Ltd. Changchun China State Grid Qinghai Electric Power Company Xining China

ISBN: (纸本)9781728135205

Aiming at the problem that uncertain power sources bring fluctuation to power system and cause lots of wind and photovoltaic curtailment, a short-term optimized operation method of multi-energy power system based on complementary characteristics of power sources is presented. The complementary mechanism of multi-energy power system is established. Based on the complementary mechanism, mathematical models of complementary objectives and complementary demands are established. Define renewable energy complementary power source. To minimize complementary demands, the capacity matching ratio of hydropower in renewable energy complementary power source is determined. According to the complementary objectives, a hierarchical optimal operation strategy for multi-energy power system is proposed. Particle swarm optimization is used to solve the optimization objective function. Taking a provincial power grid in northwest China as an example, the results show that the strategy makes full use of the complementarity of power sources and has the benefit of energy saving. © 2019 IEEE.

关键词： energy conservation

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Configuration Ratio of Grid-Following/Forming control for High-Penetration renewable energy Integrated System Containing Electric Vehicle

Configuration Ratio of Grid-Following/Forming Control for Hi...

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IEEE Conference on Vehicle power and Propulsion (VPPC)

作者： Mengqi Zhao Puyu Wang Tianming Gu Dejian Yang Gangui Yan Fang Shi School of Automation Nanjing University of Science and Technology Nanjing China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China

The charge-discharge between distributed generations and electric vehicles (EVs) will be an important component of the future development of EVs. In this paper, the optimal configuration ratio (CR) of grid-following/forming (GFL/GFM) control for high-penetration renewable energy integrated system containing EV is investigated: (1) The mathematical models for the grid-connected inverter and GFL/GFM control are elaborated, and five simulation cases with different CRs [CR: (100%, 75%, 50%, 25%, 0%)] are simulated in PSCAD/EMTDC. (2) The optimal CR is obtained through the comparative analysis of simulation results of different CRs under load disturbance /single phase-to-ground fault/island operation mode with corresponding evaluation indicators.

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