检索结果-内蒙古大学图书馆

A Novel DC Fault Ride-Through Coordinated control Strategy for DC Grid with Hybrid MMC

学校读者我要写书评

暂无评论

SSRN 2022年

作者： Jiang, Shouqi Li, Guoqing Wang, Xiaoxue Xin, Yechun Wang, Weiru Wang, Yanxu Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132000 China

DC grid based on hybrid modular multilevel converter (MMC) is an effective means to achieve large-scale renewable energy integration, multi-energy complementarity and friendly grid-connection. Aiming at the problem that the traditional DC fault ride-through (FRT) scheme will cause the interruption of power transmission in the whole network, a novel DC FRT coordinated control strategy is proposed in this paper, which can quickly interrupt the fault current and avoid the MMC exiting operation. Based on the analysis of fault current composition and key influencing factors, for fault line MMC (FLMMC), a negative voltage control strategy adaptive to the change of fault current is proposed, which can improve the current attenuation speed and ensure reliable fault isolation. For non-fault line MMC (NFLMMC), considering the overvoltage and overcurrent risks of FLMMC, the coordinated current-limiting control method and parameter selection principle of NFLMMC is proposed, where the current-limiting performance can be adaptive to the voltage change of DC bus, so as to realize the rapid recovery of DC power grid while restraining fault current. Finally, a four-terminal DC grid real-time digital simulation model is built to verify the validity of the proposed FRT coordinated control strategies. © 2022, The Authors. All rights reserved.

关键词： Voltage control

Real-time object detection method based on improved YOLOv4-tiny

学校读者我要写书评

暂无评论

arXiv

arXiv 2020年

作者： Jiang, Zicong Zhao, Liquan Li, Shuaiyang Jia, Yanfei Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of Electrical and Information Engineering Beihua University Jilin132013 China

The "You only look once v4" (YOLOv4) is one type of object detection methods in deep learning. YOLOv4-tiny is proposed based on YOLOv4 to simple the network structure and reduce parameters, which makes it be suitable for developing on the mobile and embedded devices. To improve the real-time of object detection, a fast object detection method is proposed based on YOLOv4-tiny. It firstly uses two ResBlock-D modules in ResNet-D network instead of two CSPBlock modules in Yolov4-tiny, which reduces the computation complexity. Secondly, it designs an auxiliary residual network block to extract more feature information of object to reduce detection error. In the design of auxiliary network, two consecutive 3x3 convolutions are used to obtain 5x5 receptive fields to extract global features, and channel attention and spatial attention are also used to extract more effective information. In the end, it merges the auxiliary network and backbone network to construct the whole network structure of improved YOLOv4-tiny. simulation results show that the proposed method has faster object detection than YOLOv4-tiny and YOLOv3-tiny, and almost the same mean value of average precision as the YOLOv4-tiny. It is more suitable for real-time object detection, especially for developing on embedded devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Object detection

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

学校读者我要写书评

暂无评论

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

Application Research of Chaotic Binary Particle Swarm Optimization Algorithm in Dynamic Spectrum Allocation

学校读者我要写书评

暂无评论

Journal of Computers (Taiwan) 2020年第4期31卷 288-299页

作者： Teng, Zhi-Jun Xie, Lu-Ying Chen, Hao-Lei Zhang, Hua Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology China Ministry of Education[Northeast Electric Power University China Jilin 132012 China School of Electrical Engineering China Northeast Electric Power University China

Dynamic spectrum allocation (DSA) in cognitive radio system has become a hot topic to solve the spectrum scarcity. Particle swarm optimization (PSO) has shown great flexibility in solving the spectrum allocation problem, and many related studies have been proposed. However, there is still room for improvement in the problem that PSO will have a slow convergence rate in the DSA and the latter particle search is easy to fall into the local optimum. In this paper, a dynamic time-varying spectrum allocation scheme based on chaotic binary particle swarm optimization is proposed. The improved algorithm introduces the idea of chaotic map to optimize the initial population and the optimal position of each generation of particles, and utilizes the global ergodicity of chaotic map to overcome the shortcomings of the algorithm. Based on the graph theory model, a mathematical model of dimensionality reduction spectrum allocation is built to realize DSA for users. The experimental results show that the convergence time cost of the improved algorithm is low, and the higher network rewards can be obtained under different experiments, and the fast and efficient spectrum allocation is realized to satisfy the demands of cognitive radio communication. © 2020 Computer Society of the Republic of China. All rights reserved.

关键词： Cognitive radio

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

学校读者我要写书评

暂无评论

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

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

学校读者我要写书评

暂无评论

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

Short-term power load forecasting method based on CNN-SAEDN-Res

学校读者我要写书评

暂无评论

arXiv

arXiv 2023年

作者： Cui, Yang Zhu, Han Wang, Yijian Zhang, Lu Li, Yang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China

In deep learning, the load data with non-temporal factors are difficult to process by sequence models. This problem results in insufficient precision of the prediction. Therefore, a short-term load forecasting method based on convolutional neural network (CNN), self-attention encoder-decoder network (SAEDN) and resi- dual-refinement (Res) is proposed. In this method, feature extraction module is composed of a two-dimensional convolutional neural network, which is used to mine the local correlation between data and obtain high-dimensional data features. The initial load fore-casting module consists of a self-attention encoder-decoder network and a feedforward neural network (FFN). The module utilizes self-attention mechanisms to encode high-dimensional features. This operation can obtain the global correlation between data. Therefore, the model is able to retain important information based on the coupling relationship between the data in data mixed with non-time series factors. Then, self-attention decoding is per-formed and the feedforward neural network is used to regression initial load. This paper introduces the residual mechanism to build the load optimization module. The module generates residual load values to optimize the initial load. The simulation results show that the proposed load forecasting method has advantages in terms of prediction accuracy and prediction stability. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

Multi-Objective Hybrid energy Storage Optimization Configuration Model for Reducing Thermal power Frequency Modulation Loss

学校读者我要写书评

暂无评论

Multi-Objective Hybrid Energy Storage Optimization Configura...

International Conference on power system technology (powerCON)

作者： JunHui Li ZhenZhuo Zhao ZhiQiang Zhao HaoJun Liu CuiPing Li Zhi Li CaiQi Jia XingXu Zhu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China State Grid Hami Power Supply Company Hami City Xinjiang Uygur Autonomous Region China

The TPU (Thermal power Unit) equipped with HESS (Hybrid energy Storage system) can effectively increase of FM (Frequency Modulation) performance of the unit and decrease the FM loss of the thermal power unit. The difficulty of rational allocation of ES (energy Storage) is how to improve the FM performance of TPU and reduce the life cycle cost of ES. Therefore, the paper establishes a multi-objective hybrid energy storage optimization configuration model aimed at reducing the FM loss of thermal power. Firstly, a double-layer control policy of thermal power-hybrid energy storage is proposed. The first layer is the thermal power-hybrid energy storage AGC instruction allocation strategy based on EMD (Empirical Mode Decomposition). The second layer is a hybrid energy storage control strategy with flywheel ES priority action and lithium battery second response. Then, a multi-objective optimal configuration model considering the difference between life cycle cost and benefit and AGC comprehensive evaluation index Kp is established. It uses the multi-objective PSO (Particle Swarm Optimization) algorithm based on TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) to solve the model, which can avoid contingency of traditional multi-objective PSO in determining optimum solution in the Pareto solution set. Finally, based on the simulation analysis of power plant operation data in North China, the results verify the availability and feasibility of the established model.

关键词：

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

学校读者我要写书评

暂无评论

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

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