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Computing Optimal Resilience-Oriented Operation of Distribution systems Considering Heterogenous Consumer-Side Microgrids

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IEEE Transactions on Consumer Electronics 2024年

作者： Bai, Ziyi Xu, Da Zhou, Bin Yang, Xiaodong Yang, Hanyu Liu, Ju Hubei University of Technology Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China University of Macau State Key Laboratory of Internet of Things for Smart City Macao999078 China China University of Geosciences School of Automation Wuhan430074 China Hunan University College of Electrical and Information Engineering Changsha410082 China Hefei University of Technology State Key Laboratory of High Efficiency and High Quality Electric Energy Conversion Hefei230009 China Nanjing Tech University College of Electrical Engineering and Control Science Nanjing211816 China SGCC Jingmen Power Supply Company Jingmen448000 China

Mobile battery energy storage systems (MBESs), also called power-to-mobility, have been field-validated as backup generation resources. However, the role of multi-energy coordination towards resilient distribution systems (DSs) against large area disasters is still not yet involved. To cope with such challenges, this paper proposes a computing optimal resilient operation model for post-disaster microgrid-penetrated DS recovery based on the energy-to-mobility approach. In this model, mobile multi-energy storages (MMESs) are invested and routed based on their different transportation mobility, while DS with consumer-side biogas-solar-wind multi-energy microgrids are topologized by network reconfiguration. The coordinated resilient operation of different recovery actions of DS, MMESs, and consumer-side microgrids is a difficult optimization problem as results of its inherent nonconvexities, temporal-spatial mobility and strong multi-energy couplings. The original mixed-integer non-linear programming (MINLP) problem is thus equivalently linearized and reformulated into a mixed-integer linear programming (MILP) for computation performance improvement. The proposed methodology is benchmarked and performed on a modified radial DS with three consumer-side microgrids. Numerical studies demonstrate the effectiveness and superiority of the energy-to-mobility scheme over MBESs on system resilient level and economy. © 1975-2011 IEEE.

关键词： Mixed-integer linear programming

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The existence verification of barrier function with application to synchronous safety and stability

The existence verification of barrier function with applicat...

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第32届中国过程控制会议(CPCC2021)

作者： Zheren Zhu Yi Chai Zhihuan Song Xinmin Zhang IEEE State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University State Key Laboratory of Power Transmission Equipment and System Security and New Technology and School of AutomationChongqing University

This paper mainly discusses the existence of barrier function which can guarantee a dynamic system synchronously safe and ***,scholars will use the terms "if there exists a barrier function" for most related *** this paper,we use a particular case to verify the existence of barrier function and whether it can realize stabilization with guaranteed safety,such as synchronously realizing safety and asymptotic stability,safety and uniform asymptotic stability,safety and exponential stability,and safety and finite-time *** think this paper can help to know the safety under the definitions of barrier functions and realize the safety-and-stability control.

关键词： Existence of barrier function synchronous safety and stability pre-compact forward invariant set and dynamic nonlinear system

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Frequency Security Assessment for Receiving-end system Based on Deep Learning Method

Frequency Security Assessment for Receiving-end System Based...

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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Ma, Changhui Wang, Liang Gai, Chenhao Yang, Dong Zhang, Pengfei Zhang, Hengxu Li, Changgang Electric Power Research Institute State Grid Shandong Electric Power Company Jinan Shandong China Dispatch and Control Center State Grid Shandong Electrical Power Company Jinan Shandong China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan Shandong China State Grid International Development Limited Beijing China

ISBN: (纸本)9781728143033

For hours-ahead assessment of power systems with a high penetration level of renewable generation, a large number of uncertain scenarios should be checked to ensure the frequency security of the system after the severe power disturbance following HVDC blocking. In this situation, the full time-domain simulation is unsuitable as a result of the heavy calculation burden. To fulfill the quick assessment of the frequency security, the online frequency security assessment framework based on deep learning is proposed in this paper. The Deep Belief Network (DBN) method is used to establish the framework. The sample generation method is researched to generate representative samples for the purposed of higher assessment accuracy. A large-scale AC-DC interconnected power grid is adopted to verify the validity of the proposed assessment method. © 2020 IEEE.

关键词： Time domain analysis

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Capacity Allocation of Energy Storage and Synchronous Condenser for Wind-photovoltaic-thermal-storage Combined Transmission system

Capacity Allocation of Energy Storage and Synchronous Conden...

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Sustainable power and Energy Conference (iSPEC)

作者： Zimin Zhu Zhen Liu Qingxi Duan Zhi Xu Bin Sun Hui Mei Xinjiang Electric Power System Whole Process Simulation Key Laboratory Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. Urumqi China School of Electrical Engineering Southeast University Nanjing China

ISBN: (纸本)9781665414401

In order to solve the problems of the consumption of new energy, the coexistence of wind and solar abandonment and insufficient power supply support capacity, as well as the stability of the widespread power grid in northwest China, a method for capacity allocation of energy storage and synchronous condenser for wind-photovoltaic-thermal-storage combined transmission system is proposed. Firstly, based on the complementary characteristics of wind-photovoltaic-thermal-storage, a typical architecture of wind-photovoltaic-thermal-storage combined transmission system is established and analyzed. Secondly, by taking the system equivalent annual revenue consisting of system equivalent annual electricity sales revenue, units investment, operation and maintenance costs, system equivalent annual assessment costs and carbon emission costs, as the objective function, the capacity allocation optimization model of energy storage and synchronous condenser for wind-photovoltaic-thermal-storage combined transmission system is constructed. Finally, case study based on a power grid planning data of a certain area in northwest China in 2025 is carried out to verify that the allocation method can effectively increase system revenue, promote wind and photovoltaic consumption and maintain a stable system voltage.

关键词： Costs power supplies power transmission power system stability Linear programming power grids Stability analysis

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Noise Reduction of Partial Discharge in power Cable Insulation Based on Deep Learning 7

Noise Reduction of Partial Discharge in Power Cable Insulati...

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7th IEEE International Conference on High Voltage Engineering and Application, ICHVE 2020

作者： Bin, Ding Jingwen, Liu Jianning, Chen Yuanxiang, Zhou Xuewei, Wang Jiamin, Ge Xiong'an Power Supply Company State Grid Baoding China Tsinghua University China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing China Xinjiang University Department of Electrical Engineering Urumqi China

ISBN: (纸本)9781728155111

With the rapid development of ultra-high voltage (UHV) transmission technology in China, insulation diagnosis for power equipment has been applied widely to improve the reliability of the giant power system. Partial discharge (PD) detection, with the advantages of high precision and convenient deployment, plays an important role in defect detection, location, and classification. However, the low signal to noise ratio (SNR) of PD signals and poor electromagnetic environment make it difficult to extract useful features from PD signals. To distinguish the PD signals from noise, a noise reduction method based on deep learning is proposed in this paper. With short-time Fourier transform (STFT) technology, time-domain PD signals with various noise were first transformed into time-frequency domain patterns. After preprocessing the raw pattern, a deep convolutional neural network (CNN) was built, trained, and tuned for noise reduction of PD signals. Finally, the noise reduction model was verified and compared with the traditional method based on wavelet analysis. The results demonstrate that noise reduction mothed based on deep learning can restore the PD signals with more than 90% noise reduced. Given the advantage that the convolution kernel could sense both the time-related information and the frequency-related information in a spectrum simultaneously, the DnCNN model performs better than wavelet analysis. The noise reduction model proposed in this paper is based on new generation artificial intelligence, providing a new approach for PD signal restoration, which promotes the reliability of the power system. © 2020 IEEE.

关键词： Partial discharges

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Multi-Stage Expansion Planning for Decarbonizing Thermal Generation Supported Renewable power systems Using Hydrogen and Ammonia Storage

arXiv

引用

arXiv 2023年

作者： Yu, Zhipeng Lin, Jin Liu, Feng Li, Jiarong Chi, Yingtian Song, Yonghua Ren, Zhengwei State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Sichuan Energy Internet Research Institute Tsinghua University Chengdu610213 China Department of Electrical and Computer Engineering University of Macau 999078 China Department of Electrical Engineering Tsinghua University Beijing100087 China

—Large-scale centralized development of wind and solar energy and peer-to-grid transmission of renewable energy source (RES) via high voltage direct current (HVDC) has been regarded as one of the most promising ways to achieve goals of peak carbon and carbon neutrality in China. Traditionally, large-scale thermal generation is needed to economically support the load demand of HVDC with a given profile, which in turn raises concerns about carbon emissions. To address the issues above, hydrogen energy storage system (HESS) and ammonia energy storage system (AESS) are introduced to gradually replace thermal generation, which is represented as a multi-stage expansion planning (MSEP) problem. Specifically, first, HESS and AESS are established in the MSEP model with carbon emission reduction constraints, and yearly data with hourly time resolution are utilized for each stage to well describe the intermittence of RES. Then, a combined Dantzig-Wolfe decomposition (DWD) and column generation (CG) solution approach is proposed to efficiently solve the large-scale MSEP model. Finally, a real-life system in China is studied. The results indicate that HESS and AESS have the potential to handle the intermittence of RES, as well as the monthly imbalance between RES and load demand. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, which finally leads to a LCOE of 0.4324 RMB/kWh. Copyright © 2023, The Authors. All rights reserved.

关键词： Carbon

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Optimal Sizing of Isolated Renewable power systems with Ammonia Synthesis: Model and Solution Approach

arXiv

引用

arXiv 2023年

作者： Yu, Zhipeng Lin, Jin Liu, Feng Li, Jiarong Zhao, Yuxuan Song, Yonghua The State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Sichuan Energy Internet Reasearch Institute Tsinghua University Chengdu610213 China The Department of Electrical and Computer Engineering University of Macau 999078 China The Department of Electrical Engineering Tsinghua University Beijing100087 China

Isolated renewable power to ammonia (IRePtA) has been recognized as a promising way to decarbonize the chemical industry. Optimal sizing of the renewable power system is significant to improve the techno-economic of IRePtA since the investment of power sources exceeds 80% of the total investment. However, multi-timescale electricity, hydrogen, and ammonia storages, minimum power supply for system safety, and the multiyear uncertainty of renewable generation lead to difficulties in planning. To address the issues above, an IGDT-MILFP model is proposed. First, the levelized cost of ammonia (LCOA) is directly formulated as the objective, rendering a mixed integer linear fractional programming (MILFP) problem. Information gap decision theory (IGDT) is utilized to handle the multiyear uncertainty of renewable generation. Second, a combined Charnes-Cooper (C&C) transformation and Branch-and-Bound (B&B) method is proposed to efficiently solve the large-scale IGDT-MILFP model, giving robust and opportunistic planning results. Then, Markov Chain Monte Carlo (MCMC) sampling-based posteriori analysis is leveraged to quantify the long-run performance. Finally, a real-life system in Inner Mongolia, China, is studied. The results indicate that the proposed methods could reduce the computational burden by orders of magnitude for solving a large-scale MILFP problem. Moreover, the proposed IGDT-MILFP model is necessary and accurate to obtain an optimal capacity allocation with the lowest expected LCOA (3610 RMB/t) in long-run simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Ammonia

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Corrigendum to “Enhanced dynamic support strategies of grid-forming-PMSG based on DC-voltage synchronization: Frequency and Q support perspective” [169 (2025) 110745]

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International Journal of Electrical power & Energy systems 2025年

作者： Dejian Yang Tongyu Hu Taiying Zheng Minhui Qian Chaoquan Li Zhijie Cao Gangui Yan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 China College of Electrical Engineering Zhejiang University Hangzhou 310027 China National Key Laboratory of Renewable Energy Grid Connection (China Electric Power Research Institute) Beijing 100192 China

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Contribution-based Dynamic Attention Oversampling for Imbalanced Data

Contribution-based Dynamic Attention Oversampling for Imbala...

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第32届中国过程控制会议(CPCC2021)

作者： Sha He Jing Wu Shaoyuan Li Dan Huang Dongqi Lu Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Taizhou Power Supply Company of State Grid Zhejiang Electric Power Co. Ltd

As the most successful oversampling algorithm,the SMOTE algorithm and its numerous extensions are widely used for imbalanced problem,which is long-standing and challenging for classification ***,the performance of these methods is greatly affected by the data distribution due to the use of local *** this paper,we propose a novel oversampling technique based on global distribution to deal with imbalance *** calculating the classification error,a contribution factor is assigned to each sample with a sampling weight,which can synthesize samples contribute and accurate the classification ***,the dynamic attention is also introduced to help synthetic samples to balance efficiency and *** changes the space we pay attention to by an attention factor as the sample synthesis *** conduct experiments on different data sets and compare our method with other existing over-sampling techniques,which demonstrates that our approach can realize better classification performance.

关键词： oversampling technique imbalanced problem classification dynamic attention

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Testing of Ethernet Function of Domestically-made FPGA Chip and Acquisition Board for the Application of Protective Relaying

Testing of Ethernet Function of Domestically-made FPGA Chip ...

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2021 International Conference on power system Technology, powerCON 2021

作者： Wang, Bin He, Xiaocai Jiang, Yingjie Lv, Xinquan Zhou, Zhimei Feng, Chen Dong, Xinzhou Tsinghua University Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electric Engineering Beijing China Communication Transmission Center Information Telecommunications Company State Grid Shandong Electeic Power Company Jinan China Chip Design Center Beijing Smartchip Microelectronics Technology CO. Ltd Beijing China Smart Shine Microelectronics Technology CO. Ltd Chip Product Department Beijing China

ISBN: (纸本)9781665407373

In order to solve the problem that the core chips of domestic protective relaying devices generally rely on foreign imported chips and realize the localized replacement of FPGAs, this paper designs the verification peripheral circuits of domestic FPGA chip through the analysis of the structure and test schemes design of domestic FPGA, including board-level verification scheme and data flow control verification scheme. The communication test and random test are carried out to the IP core of domestic FPGA MAC controller. From the test results, it can be seen that the loopback data and the transmitted data in the descriptor are consistent, and the tested domestic FPGA can be competent for its role in the application of protective relaying. © 2021 IEEE.

关键词： Field programmable gate arrays (FPGA)

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