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SSRN 2024年

作者： Yang, Dongfeng Wang, Xi Sun, Yong Yang, Jingying Liu, Xiaojun Jiang, Chao Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Jilin Electric Power Co. Ltd Changchun130000 China

The high percentage of renewable energy sources presents unprecedented challenges to the flexibility of power systems, and planning for the system's flexibility resources has become a necessary research area. Thus, this study constructs a flexibility quota mechanism and a two-stage model for the optimal configuration of multi-energy system coupling equipment to satisfy the growing demand for flexibility in city-level electricity-gas-heat-storage coupling systems. First, it examines the relationship between supply and demand for system flexibility, leading to the design of a flexibility quota mechanism. Subsequently, the power supply method for communication base stations shifts from direct networking to a hydrogen fuel cell supply. This flexibility quota mechanism encourages communication operators to actively engage in flexibility quota trading. Simultaneously, the safety constraints of heterogeneous energy-[A1] flow subsystems are considered while conducting comprehensive capacity planning for the coupling equipment of a multi-energy system. Finally, an optimisation strategy is proposed under the established capacity planning scheme for determining the siting and capacity of energy storage plants to address the potential transmission blockage risk in the power network. The case analysis utilised the IEEE 14-node grid-7-node gas network-8-node heat network test system, demonstrating that the constructed model enhances the system economy and mitigates transmission blockage risk, while enhancing the flexibility adjustment capability of the city-level multi-energy coupled system. © 2024, The Authors. All rights reserved.

关键词： Electric power transmission networks

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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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Optimised Configuration of Multi-energy systems Considering the Adjusting Capacity of Communication Base Stations and Risk of Network Congestion

SSRN

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SSRN 2024年

The high percentage of renewable energy sources presents unprecedented challenges to the flexibility of power systems, and planning for the system's flexibility resources has become a necessary research area. Thus, this study constructs a flexibility quota mechanism and a two-stage model for the optimal configuration of multi-energy system coupling equipment to satisfy the growing demand for flexibility in city-level electricity-gas-heat-storage coupling systems. First, it examines the relationship between supply and demand for system flexibility, leading to the design of a flexibility quota mechanism. Subsequently, the power supply method for communication base stations shifts from direct networking to a hydrogen fuel cell supply. This flexibility quota mechanism encourages communication operators to actively engage in flexibility quota trading. Simultaneously, the safety constraints of heterogeneous energy-flow subsystems are considered while conducting comprehensive capacity planning for the coupling equipment of a multi-energy system. Finally, an optimisation strategy is proposed under the established capacity planning scheme for determining the siting and capacity of energy storage plants to address the potential transmission blockage risk in the power network. The case analysis utilised the IEEE 14-node grid-7-node gas network-8-node heat network test system, demonstrating that the constructed model enhances the system economy and mitigates transmission blockage risk, while enhancing the flexibility adjustment capability of the city-level multi-energy coupled system. © 2024, The Authors. All rights reserved.

关键词： Electric power transmission networks

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Optimised Configuration of Multi-energy systems Considering the Adjusting Capacity of Communication Base Stations and Risk of Network Congestion

SSRN

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SSRN 2024年

作者： Yang, Dongfeng Wang, Xi Sun, Yong Yang, Jingying Liu, Xiaojun Jiang, Chao Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Jilin Electric Power Co. Ltd Changchun130000 China

The high percentage of renewable energy sources presents unprecedented challenges to the flexibility of power systems, and planning for flexibility resources has become a necessary research area. Thus, this study constructs a flexibility quota mechanism and a two-stage model for the optimal configuration of multi-energy system coupling equipment to satisfy the growing demand for flexibility in city-level electricity-gas-heat-storage coupling systems. First, it examines the relationship between supply and demand for system flexibility, leading to the design of a flexibility quota mechanism. Subsequently, the power supply method for communication base stations shifts from networking to a hydrogen-fuel-cell supply. This mechanism encourages communication operators to actively engage in flexibility quota trading. Simultaneously, the safety constraints of heterogeneous energy-flow-subsystems are considered while conducting comprehensive capacity planning for the coupling equipment of a multi-energy system. Finally, an optimisation strategy is proposed under the established capacity planning scheme for determining the siting and capacity of energy-storage-plants to address the potential transmission blockage risk in the power network. The case analysis utilised the IEEE 14-node grid-7-node gas network-8-node heat network test system, demonstrating that the constructed model enhances the system economy and mitigates transmission blockage risk, while enhancing the flexibility adjustment capability of multi-energy coupled system. © 2024, The Authors. All rights reserved.

关键词： Electric power transmission networks

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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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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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A New energy power Grid Expansion Planning technology Considering Optimal Economy 3

A New Energy Power Grid Expansion Planning Technology Consid...

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3rd International Conference on Green energy, Environment and Sustainable Development, GEESD 2022

作者： Song, Xinfu Xin, Chaoshan Yu, Jin Yu, Zhiyong Shen, Danhua Ma, Junliang State Grid Xinjiang Electric and Technological Research Institute Xinjiang Wulumuqi830000 China Beijing Guantao Law Firm Beijing China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin Jilin132012 China

ISBN: (纸本)9781643683126

This paper examines the path of new energy development in China against the backdrop of carbon maximum and carbon neutralization, and studies the risk of large scale new energy power transmission. In order to solve the complex uncertainty challenges of renewables power and power grid expansion planning, this paper studies and proposes an optimal economic planning model, which includes the thermal power generation start-up and shutdown expenses during the operation, the hydro power generation expenses of surplus water of reservoir, and the curtail penalty cost of new energy output power, the investment of new planning lines. The model has also considered the constraints of balance for power generation and load consumption, the power change rate, and operation, which are calculated based on the time-series operation simulation of new energy power system. Based on the functions, the process of power grid planning technology has been proposed. The planning model proposed in this paper can consider the new energy power characteristics of generation, realize the optimal planning of different power grid schemes. According to the case study findings, the new transmission line can relieve the pressure of local new energy transmission, while also improving power flow distribution as well as the rate of new energy utilization. © 2022 The authors and IOS Press.

关键词： Expansion

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Optimal Scheduling of Pumped Storage power Station with Double-Fed Variable Speed Unit Based on Reservoir Regional Operation Strategy

Optimal Scheduling of Pumped Storage Power Station with Doub...

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Communications technology and Computer Science (ACCTCS), Asia-Pacific Conference on

作者： Yuhan Ma Yining An Xiaohui Ge Bo Zhao State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou Zhejiang China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin Jilin China

ISBN: (数字)9798350359985

ISBN: (纸本)9798350359992

The conventional pumping unit lacks the ability to continuously adjust input power during pumping operations, and exhibits poor adaptability when integrating new energy sources into the grid. In this study, we propose a novel “domain operation” strategy that allocates resources based on real-time reservoir conditions across all levels of hydropower stations, while optimizing operations through the implementation of doubly fed units.

关键词： Computer science Fluctuations Costs Hydroelectric power generation Optimal scheduling Wind power generation Reservoirs

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Fault Detection Method for Insulators Using Improved YOLOv4

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第4期7卷 818-834页

作者： Zhao, Li-Quan Jiang, Zi-Cong Teng, Zi-Ming Jia, Yan-Fei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University 168 Changchun Road Jilin132012 China Graduate school of Information Science and Electrical Engineering Kyushu University Fukuoka819-0395 Japan College of information and communication Jilin University Changchun130012 China School of Electrical and Information Engineering Beihua University Jilin132013 China

A defective insulator detection method based on improved You Only Look Once version 4 (YOLOv4) is proposed to improve the precision of defective insulator detection. This method designs a dual-branch attention block by simulating the attention process of the human eye, and introduces it into the backbone of YOLOv4 to extract richer information on defective insulator features. To make the output feature map of shallow layer network fuse more different scale features, a path aggregation network has been designed. To improve detection accuracy, the spatial pyramid pooling has been replaced by atrous spatial pyramid pooling. A dynamic non-maximum suppression method is proposed to improve defective insulator detection accuracy. It employs an adaptive threshold control strategy and weighted operation to full use of the predicted box. We compare our method with defective insulator detection methods based on YOLO and R-CNN. Our simulation results show that the proposed method is more accurate than defective insulator detection methods based on YOLO, and has a faster detection speed than methods based on R-CNN. Compared with the defective insulator detection method based on R-CNN that has the highest mean average precision, the mean average precision of the proposed method is lower, but its detection speed is faster. Compared with YOLOv4, its detection speed is slower, but the mean average precision is higher. The proposed method strikes a satisfactory tradeoff between detection speed and mean average precision. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Object detection

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Ultrashort-Term power Prediction of Distributed Photovoltaic Based on Variational Mode Decomposition and Channel Attention Mechanism

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energy Engineering 2025年第6期122卷 2155-2175页

作者： Zhebin Sun Wei Wang Mingxuan Du Tao Liang Yang Liu Hailong Fan Cuiping Li Xingxu Zhu Junhui Li Intelligent Distribution Network Department Inner Mongolia Electric Power Economics and Technology Research InstituteHohhot010020China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Production Technology Department Inner Mongolia Power(Group)Co.Ltd.Hohhot010010China

Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power *** paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition(VMD)and Channel Attention ***,Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical ***,the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition(VMD).Finally,the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM *** this model,the convolutional neural network(CNN)and channel attention mechanism dynamically adjust the weights while capturing the spatial features of the input data to improve the discriminative ability of key *** extracted data is then fed into the bidirectional long short-term memory network(BiLSTM)to capture the time-series features,and the final output is the prediction *** verification is conducted using a dataset from a distributed photovoltaic power station in the Northwest region of *** results show that compared with other prediction methods,the method proposed in this paper has a higher prediction accuracy,which helps to improve the proportion of distributed PV access to the grid,and can guarantee the safe and stable operation of the power grid.

关键词： Distributed photovoltaic power channel attention mechanism convolutional neural network bidirectional long short-term memory network

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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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