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2021 IEEE Sustainable power and energy Conference, iSPEC 2021

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

ISBN: (纸本)9781665414395

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. © 2021 IEEE.

关键词： Visualization

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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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An Optimal Scheduling Method for Shared energy Storage Based on Wind power Uncertainty

An Optimal Scheduling Method for Shared Energy Storage Based...

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power Science and technology (ICPST), IEEE International Conference on

作者： Baoju Li Zezhong Liu Jiyue Fu Junhui Li Xiaobiao Fu Xingxu Zhu Yao Wang Cuiping Li Power Dispatching and Control Center State Grid Jilin Electric Power Co. Ltd Chang Chun Ji Lin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education(Northeast Electric Power University) Ji Lin Ji Lin China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

In order to improve the utilization of energy storage, to explore the value of energy storage utilization, and to study the utilization of energy storage. In this paper, a shared energy storage optimization scheduling method based on wind power uncertainty is proposed. Firstly, the scenario generation method of Latin hypercubic sampling and Cholesky decomposition is used to quantify the wind power output, and the uncertainty output is converted into deterministic output; then the economic operation is taken as the optimal scheduling objective, and environmental benefits such as carbon capture and grid constraints are considered to carry out the optimized scheduling of shared energy storage; finally, the validity of the method is verified through the scheduling of the 6-node arithmetic example system, and the utilization of the energy storage is analyzed. Finally, the effectiveness of the method is verified by scheduling in a 6-node arithmetic system, and energy storage utilization is analyzed.

关键词： Uncertainty Thermal decomposition Optimal scheduling Wind power generation Hypercubes Thermal analysis Scenario generation

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Generation method of anti-misoperation locking logic rules for substations based on typical wiring

Generation method of anti-misoperation locking logic rules f...

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IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Jingxiang Zhang Hui Zou Hewei Hou Junhui Li Rongrong Ji Kaiyuan Duan Cuiping Li Xingxu Zhu Extra-High Voltage Branch Company of State Grid Zhejiang Electric Power Co. Ltd Hangzhou China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

At present, substations usually use electrical blocking facilities to achieve the function of anti-fault blocking, but new stations and new reconstruction and expansion stations have the problem of low efficiency in the compilation and review of anti-fault blocking logic rules, and also need a lot of manual debugging and checking time. In this paper, based on the typical substation wiring and anti-false blocking logic rules, the typical substation wiring library and the corresponding blocking logic library are constructed; then, the graphic editing module and graphic analysis module are constructed by combining the substation modelling method with the topology and other technologies. Finally, the automatic generation of anti-error latching logic rules is realised, which solves the problems of low efficiency and lack of reliability in the writing and checking of the corresponding substation anti-misoperation locking logic rules.

关键词： Wiring Graphics Substations Reviews Debugging system integration Libraries Topology Logic Reliability

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Learning-Based Model Predictive Secondary Frequency control of Pv-Ess-Ev Microgrid

SSRN

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SSRN 2024年

作者： Zhong, Cheng Zhao, Hailong Liu, Yudong Liu, Chuang Key Laboratory of Modern Power System Simulation and Control &Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Province Jilin132012 China Northeast Electric Power University College of Electrical Engineering Jilin Province Jilin132012 China

Microgrids comprising photovoltaic (PV), energy-storage systems and electric vehicles have received increasing attention. However, the increase in renewable energy sources, such as PVs, will introduce uncertainty factors to the frequency response, resulting in frequency fluctuations that can reduce power quality. Hence, we propose an outstanding learning-based control approach that combines a model of physical principles with a Gaussian Process (GP) learning approach. The learning model corrects the physical principles model and estimates its uncertainty. simulations are performed by comparing the proposed controller with conventional model-predictive controllers. The results indicate that the learning-based controller proposed can adjust the frequency with less overshooting and a lower root mean square error compared to the conventional MPC control method. © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Zoning Voltage Coordination control Method for High Proportion Distributed Photovoltaic power in Distribution Network

Zoning Voltage Coordination Control Method for High Proporti...

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energy Engineering and power systems (EEPS), International Conference on

作者： Bing Xue Yanfeng Ge Chuang Li Niankang Guo Chenglian Ma Dawei Huang State Grid Yingkou Power Supply Company State Grid Liaoning Electric Power Co. LTD Yingkou Liaoning China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

The high penetration of distributed photovoltaic generation into distribution networks has become a major development trend in the future. However, the intermittency and random fluctuations of distributed photovoltaic output have exacerbated voltage violation and fluctuation issues in distribution networks. To address this problem, a distribution network zoning voltage coordination control strategy is proposed. In terms of zoning, voltage sensitivity index information obtained from daily power flow calculations is utilized to analyse and express the impact variation of photovoltaic generation on the voltage of each node. Based on the threshold requirements of voltage variation indices, the zoning of nodes is determined. In terms of zoning voltage coordination control, a strategy of voltage sensitivity control within the partition is adopted, pairing nodes within each partition and utilizing the active and reactive regulation capabilities of photovoltaic generation to control all over-limit voltage within normal range. Furthermore, through the interval distributed voltage coordination control strategy, the interval state variables are equivalenced, and based on the SADMM algorithm, the dynamic reactive power compensation amount between adjacent partitions is optimized to achieve the optimization and suppression of network-wide voltage fluctuations. Taking the IEEE 33-node system as an example, a case study was conducted to verify the effectiveness and feasibility of the proposed strategy in practical applications.

关键词： Photovoltaic systems Reactive power Fluctuations Voltage fluctuations Sensitivity Distribution networks Regulation Indexes Voltage control Optimization

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Optimal Allocation Strategy of Frequency Modulation power for Multiple energy Storage systems Considering Dual Constraints of Frequency Modulation Cost and Frequency Modulation Capability

Optimal Allocation Strategy of Frequency Modulation Power fo...

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power Science and technology (ICPST), IEEE International Conference on

作者： Yongming Peng Wenbo Si Haiji Zhao Changlin Lv Chengzhe Liu Fei Xu Ling Hao Junhui Li Northeast Branch of State Grid Corporation of China Shenyang China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Key Laboratory of Power System and Power Generation Equipment Control and Simulation (Tsinghua University) Beijing China

Aiming at the power allocation problem of multiple energy storage power stations distributed at different locations in the regional power grid participating in frequency modulation services, a frequency modulation power optimization allocation strategy for multiple energy storage systems considering the dual constraints of frequency modulation cost and frequency modulation capability is proposed. Firstly, a multi-objective optimization allocation model for frequency modulation power is constructed with the minimum frequency modulation cost and minimum deviation of the state of charge (SOC) for energy storage power plants. Secondly, using Pareto based multi-objective genetic algorithm (MOGA) to solve the model, introduce adaptive weight coefficients and fuzzy membership functions for each objective function regarding the frequency regulation demand of the power grid and the deviation of the SOC of energy storage stations, construct a comprehensive satisfaction function to make decisions on the most advantageous points on the Pareto frontier, in order to obtain the optimal output of each energy storage station that can adapt to the frequency regulation requirements of the power grid. Finally, simulation analysis was conducted on the proposed strategy in this article, and the results showed that: The proposed strategy not only enhances the frequency regulation economy of the regional power grid, but also helps to restore the SOC of the energy storage power station.

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Research on Aggregation Model of Wind Farm Based on SSO Complex Torque Coefficient Analysis 3

Research on Aggregation Model of Wind Farm Based on SSO Comp...

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2020 3rd International Symposium on power Electronics and control Engineering, ISPECE 2020

作者： Xunwen, Su Hanqing, Cui Yuming, Pei Dongni, Zhang Pengyu, An Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China School of Electrical and Control Engineering Heilongjiang University of Science and Technology Harbin Heilongjiang China

In order to study the influence of the clustering aggregation of doubly-fed wind turbines (DFIG) in the wind-fire bundling system on the system subsynchronous oscillation (SSO), the expression of the DFIG output active power on the electrical damping De of thermal power units is first derived. Then the wind-thermal bundling system is built based on the IEEE first bench mark, and the wind farm is aggregated to several groups according to the rated power. The complex torque coefficient method is used to analyze the two cases of the same running state of the wind turbine and the difference of wind speed between the turbine and verified by time-domain simulation. The results show that the difference in wind speed within the DFIG groups has little effect on the system oscillation frequency before and after the aggregation of the wind farm, but there may be a slight error in the electrical damping coefficient before and after the aggregation,but the error does not affect the trend and analysis of damping characteristics of system. When studying the influencing factors of wind-fire bundling system SSOthe aggregated model can be uesd to improve simulation efficiency. © Published under licence by IOP Publishing Ltd.

关键词： Wind turbines

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Critical link identification of power system vulnerability based on modified graph attention network

arXiv

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arXiv 2024年

作者： Wang, Changgang Wang, Xianwei Cao, Yu Li, Yang Lü, Qi Zhang, Yaoxin Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Northeast Electric Power University Jilin132012 China State Grid Tianjin Electric Power Company Tianjin300010 China

As the power grid expands and the proportion of renewable energy increases, the uncertainty and randomness of the power grid have increased, posing a threat to the security of system operation. It becomes crucial to identify the crucial links in the power grid to ensure its reliability during operation. Addressing the issues of slow identification speed and difficulty in meeting the actual operational requirements of traditional methods for identifying crucial links in the power grid, this paper proposes a method based on the Modified Graph Attention Network (MGAT) algorithm for identifying crucial link in the power grid. Firstly, combining complex network theory with actual power grid operational data, an evaluation index set is established. Subsequently, the MGAT is utilized to explore the mapping relationships between various indicators during power grid operation and the crucial links, forming a model for crucial link identification. Considering the requirements of training accuracy and efficiency, the original data is preprocessed to optimize the model. Next, through simulation, the original dataset is obtained for training, validation, and testing of the identification model. Finally, the proposed model is applied to an improved IEEE 30-node system and a real power grid. The results indicate the feasibility of the proposed method, with accuracy and speed surpassing traditional methods, demonstrating its practical engineering value. © 2024, CC BY-NC-ND.

关键词： Smart power grids

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Ultra-Short-Term Wind power Interval Prediction Based on Fluctuating Process Partitioning and Quantile Regression Forest

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FRONTIERS IN energy RESEARCH 2022年 10卷

作者： Sun, Yong Huang, Yutong Yang, Mao Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Jilin Electric Power Company Ltd. Changchun China

As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current interval prediction methods are still incomplete in terms of tapping into the physical variability of wind power, especially for the specific time scale of the ultra-short term. This paper therefore proposes a new framework for interval forecasting of ultra-short-term wind power that incorporates the power fluctuation process. Firstly, a fluctuating process of wind power series is defined and a Kalman-SOM method for clustering the fluctuating processes of wind power is constructed. Secondly, a quantile regression forest interval prediction model is constructed for multiple fluctuation processes for ultra-short-term time scales. Finally, the effectiveness of the overall framework is validated at a wind farm in Jilin Province, China. Compared with the traditional interval prediction method. The interval bandwidth is reduced by 0.86% on average, and the interval coverage is increased by 1.4% on average. The results demonstrate the effectiveness and feasibility of the method in this paper.

关键词： wind power ultra-short-term prediction self-organizing map fluctuation quantile regression forest

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