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

作者： Jinxian Zhang Junbo Zhao Ketian Ye Fei Ding Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Power System Engineering Center National Renewable Energy Laboratory Golden CO USA

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches.

关键词： Voltage measurement Uncertainty Fuses Estimation Gaussian processes system integration Probabilistic logic

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Multi-Objective Sizing Optimization Method of Microgrid Considering Cost and Carbon Emissions

arXiv

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arXiv 2024年

作者： Zhu, Xiang Ruan, Guangchun Geng, Hua Liu, Honghai Bai, Mingfei Peng, Chao The Department of Automation Tsinghua University Beijing10084 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing10084 China MIT BostonMA02139 United States The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical & Electronic Engineering North China Electric Power University Beijing102206 China The School of Automation Engineering University of Electronics and Technology of China Chengdu611731 China

Microgrid serves as a promising solution to integrate and manage distributed renewable energy resources. In this paper, we establish a stochastic multi-objective sizing optimization (SMOSO) model for microgrid planning, which fully captures the battery degradation characteristics and the total carbon emissions. The microgrid operator aims to simultaneously maximize the economic benefits and minimize carbon emissions, and the degradation of the battery energy storage system (BESS) is modeled as a nonlinear function of power throughput. A self-adaptive multi-objective genetic algorithm (SAMOGA) is proposed to solve the SMOSO model, and this algorithm is enhanced by pre-grouped hierarchical selection and self-adaptive probabilities of crossover and mutation. Several case studies are conducted to determine the microgrid size by analyzing Pareto frontiers, and the simulation results validate that the proposed method has superior performance over other algorithms on the solution quality of optimum and diversity. Copyright © 2024, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Inner-approximate Reachability Computation via Zonotopic Boundary Analysis

arXiv

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arXiv 2024年

作者： Ren, Dejin Liang, Zhen Wu, Chenyu Ding, Jianqiang Wu, Taoran Xue, Bai Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China College of Computer Science and Technology National University of Defense Technology Changsha China Department of Electrical Engineering and Automation Aalto University Espoo Finland

Inner-approximate reachability analysis involves calculating subsets of reachable sets, known as inner-approximations. This analysis is crucial in the fields of dynamic systems analysis and control theory as it provides a reliable estimation of the set of states that a system can reach from given initial states at a specific time instant. In this paper, we study the inner-approximate reachability analysis problem based on the set-boundary reachability method for systems modelled by ordinary differential equations, in which the computed inner-approximations are represented with zonotopes. The set-boundary reachability method computes an inner-approximation by excluding states reached from the initial set’s boundary. The effectiveness of this method is highly dependent on the efficient extraction of the exact boundary of the initial set. To address this, we propose methods leveraging boundary and tiling matrices that can efficiently extract and refine the exact boundary of the initial set represented by zonotopes. Additionally, we enhance the exclusion strategy by contracting the outer-approximations in a flexible way, which allows for the computation of less conservative inner-approximations. To evaluate the proposed method, we compare it with state-of-the-art methods against a series of benchmarks. The numerical results demonstrate that our method is not only efficient but also accurate in computing inner-approximations. Copyright © 2024, The Authors. All rights reserved.

关键词： Ordinary differential equations

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A Bargaining Game-Based Peer-to-Peer Trading Optimization Method for Microgrid system on the Island 2

A Bargaining Game-Based Peer-to-Peer Trading Optimization Me...

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2nd IEEE China International Youth Conference on electrical engineering, CIYCEE 2021

作者： Li, Hui Trivedi, Anupam Ren, Zhouyang Chongqing University State Key Laboratory of Power Transmission Equipment System Security and New Technology Chongqing400044 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

ISBN: (纸本)9781665400640

This paper proposes a peer-to-peer trading optimization method for a microgrid (MG) system on the island. A bargaining game is applied to describe the trading and operating strategies for two MGs in the off-grid MG system under the regulation of the government. First, the peer-to-peer trading optimization models for both MGs are developed. The electricity price is negotiated by MGs in an interval limited by the government. The trading power between MGs is optimized coordinately to minimize the net cost of each MG. Second, the presented optimization models are linearized and transformed to solve the Pareto front of trading and operating schemes for both MGs. Finally, the effectiveness of the proposed method is verified in the case studies. A sensitivity analysis of pricing intervals is also implemented to reveal the influence of the government's regulation on the net cost of MG. © 2021 IEEE.

关键词： Sensitivity analysis

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical feature of characteristic curves and convolutional neural network with CBAM modules

arXiv

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arXiv 2023年

作者： Qu, Jiaqi Wei, Lu Sun, Qiang Zareipour, Hamidreza Qian, Zheng School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China School of Electronics and Information Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of PV arrays, and both the dust-affected operating conditions and various diode configurations make the faults more complicated. However, current methods for fault diagnosis based on I-V characteristic curves only utilize partial feature information and often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply it in practice and to accurately identify multiple complex faults with similarities in different blocking diodes configurations of PV arrays under the influence of dust. Therefore, a novel fault diagnosis method for PV arrays considering dust impact is proposed. In the preprocessing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field including I-V and P-V to obtain the transformed graphical feature matrices. Then, in the fault diagnosis stage, the model of convolutional neural network (CNN) with convolutional block attention modules (CBAM) is designed to extract fault differentiation information from the transformed graphical matrices containing full feature information and to classify faults. And different graphical feature transformation methods are compared through simulation cases, and different CNN-based classification methods are also analyzed. The results indicate that the developed method for PV arrays with different blocking diodes configurations under various operating conditions has high fault diagnosis accuracy and reliability. Copyright © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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A two-stage optimization model for floating offshore wind farm layout and control

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Renewable Energy 2025年 253卷

作者： Tao, Siyu Yang, Jisheng Zheng, Gang He, Ruiyang Feijóo-Lorenzo, Andrés E. College of Automation Engineering Nanjing University of Aeronautics and Astronautics No. 29 Jiangjun Road Nanjing211106 China Department of Building Environment and Energy Engineering Hong Kong Polytechnic University No. 102 Pokfulam Road Pok Fu Lam Hong Kong 999077 China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing100084 China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Monash Biomedical Imaging Monash University Clayton VIC3800 Australia School of Engineering Cardiff University CardiffCF243AA United Kingdom Department of Electrical Engineering University of Vigo Vigo36310 Spain

The effective planning of wind turbine (WT) positions in a wind farm (WF) plays a crucial role in capturing wind energy and increasing power generation. Control optimization of WT attitudes can also help reduce wake effects and increase power generation, thereby maximizing the annual electricity production (AEP) of a WF. In this paper, a two-stage optimization model is proposed for planning the stationary layout of floating offshore wind farms (FOWFs), as well as the positions and attitudes of the floating offshore wind turbines (FOWTs) via optimal control. In the first stage, a competitive particle swarm optimizer (CPSO) is employed to generate multiple FOWF layouts. In the second stage, the genetic algorithm (GA) is utilized to optimize the yaw angles and axial induction factors of the FOWTs for operation control. Unlike the existing approaches that address WT layout design and operation control sequentially and separately, the proposed method integrates these aspects to simplify the FOWTs operation and to improve their performances. Additionally, taking the movable characteristics of the FOWTs into consideration, the proposed model incorporates the positional movement of the FOWTs under varying wind conditions, making the power calculations more realistic. Case studies demonstrate that compared with the traditional layout-only optimization, the proposed two-stage optimization model can help increase the AEP of the FOWFs by 4.72 %. © 2025 Elsevier Ltd

关键词： Genetic algorithms

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Guest editorial: Progress on computational techniques for electromagnetic fields and applications

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COMPEL - The International Journal for Computation and Mathematics in electrical and Electronic engineering 2023年第1期42卷 1-1页

作者： Yang, Shiyou Sykulski, Jan Qingxin, Yang Cui, Xiang Department of Electrical Engineering Zhejiang University Hangzhou China Department of Electronics and Computer Science Southampton University Southampton United Kingdom Tianjin Key Laboratory of Advanced Electrical Engineering and Energy Technology Tianjin Polytechnic University Tianjin China State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources Research Center for Electromagnetism and Superconduction Beijing China

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Skin-like cryogel electronics from suppressed-freezing tuned polymer amorphization

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Nature Communications 2023年第1期14卷 1-10页

作者： Zhang, Xiansheng Yan, Hongwei Xu, Chongzhi Dong, Xia Wang, Yu Fu, Aiping Li, Hao Lee, Jin Yong Zhang, Sheng Ni, Jiahua Gao, Min Wang, Jing Yu, Jinpeng Ge, Shuzhi Sam Jin, Ming Liang Wang, Lili Xia, Yanzhi State Key Laboratory of Bio-Fibers and Eco-Textiles College of Textiles and Clothing Qingdao University Qingdao 266071 China Institute for Future Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Qingdao 266071 China College of Materials Science and Engineering Qingdao University Qingdao 266071 China CAS Key Laboratory of Engineering Plastics Institute of Chemistry Chinese Academy of Sciences Beijing 100190 China Department of Chemistry SungKyunKwan University Suwon 16419 South Korea State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou 310027 China College of Biological Science and Medical Engineering Donghua University Shanghai 201620 China Institute of Environmental Engineering ETH Zürich Zürich 8093 Switzerland Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

The sole situation of semi-crystalline structure induced single performance remarkably limits the green cryogels in the application of soft devices due to uncontrolled freezing field. Here, a facile strategy for achieving multifunctionality of cryogels is proposed using total amorphization of polymer. Through precisely lowering the freezing point of precursor solutions with an antifreezing salt, the suppressed growth of ice is achieved, creating an unusually weak and homogenous aggregation of polymer chains upon freezing, thereby realizing the tunable amorphization of polymer and the coexistence of free and hydrogen bonding hydroxyl groups. Such multi-scale microstructures trigger the integrated properties of tissue-like ultrasoftness (Young’s modulus <10 kPa) yet stretchability, high transparency (~92%), self-adhesion, and instantaneous self-healing (<0.3 s) for cryogels, along with superior ionic-conductivity, antifreezing (−58 °C) and water-retention abilities, pushing the development of skin-like cryogel electronics. These concepts open an attractive branch for cryogels that adopt regulated crystallization behavior for on-demand functionalities. © 2023, Springer Nature Limited.

关键词： Gels and hydrogels Polymers

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Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

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Journal of Modern power systems and Clean Energy 2020年第6期8卷 1240-1249页

作者： Ancheng Xue Feiyang Xu Jingsong Xu Joe H.Chow Shuang Leng Tianshu Bi State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China State Grid Ningxia Yinchuan Electric Power Company Yinchuan 750001China the Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Smart grids are increasingly dependent on data with the rapid development of communication and *** one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from *** with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical ***,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)***,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp ***,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line *** obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD ***,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.

关键词： global position system(GPS) GPS spoofing attack(GSA),phasor measurement,pattern recognition,data correction,line parameter

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LSTM Network-Based Method for Flexibility Prediction of Aggregated Electric Vehicles in Smart Grid 5th

LSTM Network-Based Method for Flexibility Prediction of Aggr...

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International Top-Level Forum on engineering Science and Technology Development Strategy and 5th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control, PMF2020

作者： Zhou, Huayanran Zhou, Yihong Zhang, Haijing Hu, Junjie Nordströmd, Lars Yang, Guangya State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Division of Electric Power and Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Center for Electric Power and Energy Department of Electrical Engineering Technical University of Denmark Kongens Lyngby Copenhagen Denmark

ISBN: (纸本)9789811597459

The flexibility of Demand Response (DR) resources in grid operations has become a valuable solution to respond to the several problems brought about by the growth of intermittent renewable generation. However, the flexibility prediction of the DR resources has not yet been fully addressed in the available literature. This paper trained a long short-term memory (LSTM) recurrent neural network to predict the aggregated flexibility of electric vehicles (EVs). The prediction is based on the historical charging behavior of EVs and the DR signal (DS) which is proposed to facilitate prediction and DR management. Both the size and the maintaining time of the aggregated flexibility can be obtained from the prediction results. The accuracy of the flexibility prediction is verified through the simulation of case studies. The simulation results reveal that the size of flexibility changes under different maintaining time. The proposed flexibility prediction method may be of great assistance for DR management as well as the reserve of the gird. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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