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IEEE International Conference on power and power and renewable energy (ICPRE)

作者： Mao Yang Xiangyu Li Zifen Han Yong Sun Xiqiang Chang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Gansu Electric Power Company Gansu China State Grid Jilinsheng Economic And Technological Research Institute Jilin China State Grid Xinjiang Electric Power CO. LTD Xinjiang China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

The intermittent and fluctuating nature of wind energy makes it difficult to accurately predict wind power, leading to low penetration in the wind power grid. To address this problem, this paper designs ultra-short-term multi-step prediction of wind power based on modernTCN and multi-task learning to improve the prediction accuracy. Firstly, modernTCN's ability to have a large receptive field and capture cross-variate timing dependencies is exploited to obtain multivariate timing feature information and establish a multi-step mapping of input features to power. Then it is inputted into the MMoE multi-task learning method, and the prediction results are corrected to obtain the ultra-short-term prediction of wind power using multiple expert networks and gating units. The experimental results show that the method proposed in this paper can effectively improve the ultra-short-term prediction accuracy of wind power, and can provide a favourable reference for the scheduling centre to adjust the power generation plan in real-time response to the power demand.

关键词： renewable energy sources Accuracy Wind energy Wind power generation Predictive models Multitasking Feature extraction Real-time systems Timing Wind forecasting

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ANALYSES OF STEADY-STATE VOLTAGE STABILITY CONSIDERING REACTIVE-VOLTAGE REGULATION COEFFICIENT

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2022年第2期84卷 303-318页

作者： Zhou, Yibo Caokang, Yangyong Zhang, Shi Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Changchun Power Supply Company State Grid Jilin Electric Power Company Limited Changchun130000 China

Based on the local voltage stability index, The sensitivity matrix of load node local voltage stability index to generator node excitation system reactive-voltage regulation coefficient is established. According to the sensitivity information, the reactive-voltage regulation coefficient of each generator is optimized to improve the static voltage stability of the power grid. The analysis results of 39 buses system verify the feasibility and accuracy of the proposed sensitivity matrix. When the reactive-voltage regulation coefficient of the key generator node which has a great impact on the static voltage stability of the load node is adjusted according to the sensitivity index, the static voltage stability of the power system could be improved. This study can contribute to realize the optimal setting of reactive-voltage regulation coefficient of generators in multi-machine system. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Voltage regulators

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Improved active damping control strategy and closed-loop parameter design for LCL grid-connected inverter

Improved active damping control strategy and closed-loop par...

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2021 International Conference on Electrical Engineering and Computer technology, ICEECT 2021

作者： Chen, Qi Liu, Hongbo Hao, Qingxiang Yin, Yikun Li, Yuanhong Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Zaozhuang Power Supply Company State Grid Shandong Electric Power Company Zaozhuang277000 China Changchun Institute of Technology ChangChun130012 China

In this paper, an active damping control strategy based on capacitance and voltage feedback is proposed to solve the resonance problem of three-phase LCL inverter grid-connected system. To solve the problem that the parameters of active damping control strategy are complicated and need to be adjusted repeatedly, a parameter design method is proposed in this paper, which is simple to implement and does not need to be adjusted repeatedly. Finally, the effectiveness of the control strategy and parameter design method is verified by experiments. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Capacitance

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Carbon-oriented Local Integrated energy system Multi-energy Coupling Market Design 5

Carbon-oriented Local Integrated Energy System Multi-energy ...

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5th IEEE Conference on energy Internet and energy system Integration, EI2 2021

作者： Li, Jifeng Li, Jinghua He, Xingtang Luo, Hao Dalian Electric Power Supply Company State Grid Liaoning Electric Power Supply Co. Ltd Dalian China Key Laboratory of the Ministry of Education on Smart Power Grids Tianjin University Tianjin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China

ISBN: (纸本)9781665434256

Under the background that countries all over the world constantly advocate energy conservation and emission reduction and seek to deepen the reform of power systems and introduce new energy trading policies, this study constructed a carbon-oriented local integrated energy system multi-energy coupling market architecture. This construct was aimed at problems that current multi-energy coupling market research has not considered, including multi-energy substitution characteristics and carbon emission factors. First, taking the local integrated energy system as the main physical architecture, a multi-energy coupling market architecture was constructed combining the main market participants of different energy subsystems. Second, a model of the subsystem markets in the energy coupling market, and the joint clearing method were proposed. Finally, the guiding role of the energy coupling market was analyzed by simulation for reasonable pricing and carbon emission reductions of different energy market operators. © 2021 IEEE

关键词： Carbon

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DC Overvoltage Analysis of GFM-controlled Wind Farm Connected via MMC-HVDC system Caused by Receiving-end AC Faults

DC Overvoltage Analysis of GFM-controlled Wind Farm Connecte...

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International Conference on power Electronics and Motion control (IPEMC)

作者： Siying Chen Min Cheng Yingbiao Li Jiawei Yu Yihua Zhu Mingkang Wu Jiabing Hu Jianan Yan State Key Laboratory of Advanced Electromagnetic Technology and School of Electrical and Electronic Engineering Huazhong University of Science and Technology China Yunnan Power Grid China CSG Key Laboratory for Power System Simulation (Electric Power Research Institute China Southern Power Grid) State Key Laboratory of HVDC (Electric Power Research Institute China Southern Power Grid) National Energy Power Grid Technology R&D Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

DC overvoltage occurs when short circuit fault exists at the receiving-end and is harmful to the safety of the system where wind farms are connected to the grid through high-voltage direct current (HVDC) transmission based on the modular multilevel converter (MMC). To address this issue, this paper first analyzed the mechanism of the DC overvoltage and innovatively proposed a strategy in which grid-forming-controlled wind farms are integrated into the AC grid through MMC-HVDC, whose sending-end applies grid-following control and constant DC voltage control. However, secondary DC overvoltage appears during the fault recovery stage and is mainly caused by the saturation of the PI controller of constant active power control. simulations are carried out on a test with MATLAB/Simulink, and results verify the efficacy of the proposed methods in suppressing DC overvoltage that appeared during receiving-end faults and their recovery stage.

关键词： PI control simulation power control Wind farms Robustness Wind turbines Safety

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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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International Conference on power system technology (powerCON)

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

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.

关键词：

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Evaluation of Regulating Capacity of power system Nodes and Transmission Lines

Evaluation of Regulating Capacity of Power System Nodes and ...

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Xiuyu Yang Zekun Fan Almasbek Shakenbek Baoyu Di Chongbi Li Yi Wang Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeasst Electric Power University Jilin China State Grid Xinjiang Electric Power Co. Ltd. State Grid Xinjiang Electric Power Co. Ltd. Electric Power Research Institute Urumqi China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

The large-scale access of renewable energy to the power grid leads to a sharp increase in the demand for power system regulation capacity. In order to solve this problem, this paper explores the mechanism of supply and demand balance of power system regulation capacity, analyzes the transmission characteristics of regulation capacity, and proposes the adequacy index of node regulation capacity and the adequacy index of network transmission regulation capacity. The Garver-6 node system is used to verify the effectiveness and practicability of the proposed method. The example shows that the proposed evaluation method can accurately identify the weak links of regulation ability and clarify the causes of insufficient regulation ability.

关键词： renewable energy sources Supply and demand power transmission lines Evaluation models Regulation Smart grids Planning Artificial intelligence Load flow Capacity planning

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Probabilistic power Flow Calculation of AC/DC Hybrid system Based on Cumulant Method

arXiv

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arXiv 2022年

作者： Sun, Yinfeng Xia, Dapeng Gao, Zichun Wang, Zhenhao Li, Guoqing Lu, Weihua Wu, Xueguang Li, Yang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Global Energy Interconnection Research Institute Beijing102211 China Beijing Key Laboratory of DC Power Grid Technologies and Simulation Beijing102211 China

The operating conditions of the power system have become more complex and changeable. This paper proposes a probabilistic power flow calculation method based on the cumulant method for the voltage sourced converter high voltage direct current (VSC-HVDC) hybrid system containing photovoltaic grid-connected systems. Firstly, the corresponding control mode is set for the converter, including droop control and master-slave control. The unified iterative method is used to calculate the conventional AC/DC power flow. Secondly, on the basis of the probability model of load and photovoltaic output, based on the aforementioned power flow results, use correlation coefficient matrix of this paper will change the relevant sample into independent sample，the cumulants of the load and photovoltaic output are obtained;Then, the probability density function (PDF) and cumulative distribution function (CDF) of state variables are obtained by using Gram-Charlie series expansion method. Finally, the mean value and standard deviation of node voltage and line power are calculated on the modified IEEE 34-bus and IEEE 57-bus transmission systems. The algorithm can reflect the inherent uncertainty of new energy sources, and replace the complex convolution operation, greatly improving the calculation speed and the convergence. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric load flow

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Application of deep reinforcement learning in power system scheduling strategy simulation

Application of deep reinforcement learning in power system s...

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energy, power and Electrical Engineering (EPEE), International Conference on

作者： Binjiang Hu Libin Huang Yufeng Hu Jie Zhang Haiping Guo Yuanhong Lu Zeqi Hong Jingyue Zhang Hui Luo 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 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

With the increasing scale and complexity of power system, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a power system scheduling method using DQN (Deep Q Network) is introduced in this study. This method uses neural network model to learn and optimize scheduling strategy, and has strong adaptability and enhanced global optimization ability. Comparative evaluations with genetic algorithms and particle swarm algorithms on IEEE-118 and SG-126 datasets show that the proposed method has significant advantages in terms of cumulative reward and stable runtime.

关键词： Electrical engineering Runtime Neural networks power system stability Deep reinforcement learning Stability analysis Real-time systems Particle swarm optimization Optimization Genetic algorithms

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Design and Implementation of power system simulation Platform Based on Cloud Computing

Design and Implementation of Power System Simulation Platfor...

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energy, power and Electrical Engineering (EPEE), International Conference on

作者： Yuanhong Lu Haiping Guo Yanjun Zhao Libin Huang Binjiang Hu Hui Luo Jingyue Zhang National Energy Power Grid Technology R&D Centre Guangzhou China 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

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

power system simulation involves simulating the operating states and dynamic processes of power systems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation methods struggle to meet the needs of large-scale, complex power grids due to significant demands for computational resources. Cloud computing, with its high scalability, resource pooling, and on-demand services, is ideally suited for the extensive simulation calculations required by modern power systems. Despite its advantages, the application of cloud computing in power system simulation poses challenges related to data security and privacy, particularly in collaborative simulations involving multiple power entities. This paper presents the design and implementation of a cloud computing-based power system simulation platform. The proposed platform leverages the distributed computing capabilities of cloud computing, integrates federated learning to ensure data privacy, and utilizes advanced power system simulation technologies. This approach significantly enhances simulation efficiency and accuracy while providing data security and privacy protection. The platform offers reliable decision support for power system planning, operation, and control.

关键词： Cloud computing Data privacy Accuracy Federated learning Data security power system simulation power system dynamics power system stability power grids Testing

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