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reliability Assessment of a Cyber Physical Microgrid System in Island Mode

CSEE Journal of Power and Energy Systems 2019年第1期5卷 46-55页

作者： Jing Guo Wenxia Liu furqan r.syed Jianhua Zhang State Key Laboratory of Alternate Electrical Power System with renewable Energy Sources North China Electric Power UniversityBeijing 102206China GCL New Energy Suzhou 215000China

As cyber physical systems,microgrids(MGs),with distributed generations and energy management systems,can improve the reliability of power supply for customers in *** quantify the reliability of isolated MGs,a cyber-physical assessment model is *** this model,the circuit breakers and distributed energy resources are treated as the coupling elements between the cyber system and physical system,where the circuit breakers are uniquely modelled by using the Markov process theory based on the indirect interdependencies between cyber physical *** the cyber system,the reliability model of communication networks is formulated based on the link connectivity evaluation *** the physical system,a system state generating method is presented to account for the optimal operation strategy,which considers the influence of the optimization strategy on the failure consequence *** the proposed cyber and physical reliability models,the sequential Monte Carlo(SMC)simulation method is adopted to assess the reliability of islanded *** are carried out on a test system,and results verify the feasibility and effectiveness of proposed assessment ***,one application of the proposed method is on the parameter setting of the cyber system,in terms of enhancing MGs reliability.

关键词： Cyber physical system island mode microgrid reliability assessment sequential Monte Carlo

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Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-rNN Approach

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Computers, Materials & Continua 2024年第4期79卷 1497-1519页

作者： syeda Shamaila Zareen Guangmin Sun Mahwish Kundi syed furqan Qadri Salman Qadri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Computer Science International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland research Center for Data Hub and Security Zhejiang LabHangzhou311121China Computer Science Department MNS University of AgricultureMultan59220Pakistan

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and recurrent Neural Network (CNN-rNN) model with a resNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained resNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

关键词： Skin cancer classification deep learning Convolutional Neural Network(CNN) rNN resNet-50

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Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

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Tsinghua Science and Technology 2018年第3期23卷 254-265页

作者： syed furqan rafique Jianhua Zhang Muhammad Hanan Waseem Aslam Atiq Ur rehman Zmarrak Wali Khan Department of Electricaland Electronics Engineering North China ElectricPower University Beijing 102206 China.

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

关键词： microgrid economic optimization generation forecast load forecast energy management system fuzzy prediction interval heuristic optimization

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Model design and structure research for integration system of energy, information and transportation networks based on ANP-fuzzy comprehensive evaluation

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Global Energy Interconnection 2018年第2期1卷 137-144页

作者： Tianjing Wu Shaohua Liu Ming Ni Yong Zhao Pei Shen syed furqan rafique NArI Group Corporation Global Energy Interconnection Development Cooperation Organization National University of Sciences and Technology Pakistan

For lack of deep research on model, system structure and top-level design, the integrated system concept of energy, information and transportation networks fails to provide effective guidance for transferring the theory to practice. In this paper, with dispatching of energy flow and information flow as a focus, clean energy of wind power and solar power as carrier, battery charging & swapping station as medium and all kinds of transportation flows as entity, a five-in-one threenetwork integrated system model is built by full use of technologies of Internet of Vehicles(IOV) and Internet of things(IOT) to promote the innovative concept of three-network integration into practice, and provide a reference for future researches.

关键词： Three-network integration Global Energy Interconnection Internet of Vehicles ANP-fuzzy comprehensive evaluation Information Communication Technology

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Improved ANN Based Impedance Estimator for Phase to Ground Faults in UHV Transmission Line

Improved ANN Based Impedance Estimator for Phase to Ground F...

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作者： syed furqan rafique（舍耶特）华北电力大学

学位级别：硕士

The high speed protection of power system for transmission and primary distribution networks are the most important issue in the selective tripping of the power plant. In order to solve this problem high speed automatic reclosure is continuously in development with state of the art technology used. The economic and technical advantages of distance protection are considerably large enough because the main advantage of it is that the range of the fault detection in the line is not depends on the changes in the source impedance.The main factors that effects the effectiveness of the traditional distance relaying schemes in single line to ground, double line to ground and specially in simultaneous open conductor fault are the variation in fault resistance, power flow direction as well as magnitude. In this thesis, the work is presented that will discuss about the aforementioned problems of conventional distance relaying methods in doubly fed transmission system. An accurate digital distance relaying scheme integrated with artificial neural network impedance estimator is developed using the conventional method impedance after removal of the error impedance from it using modified scheme. The modified scheme is immune to the variation in fault location for under reach and overreach problem caused by sequence current components. A series of test conducted on a800kV,400km transmission line for single phase to ground faults as well as simultaneous open conductor fault in PSCAD/EMTP and Matlab/Simulink. Finally comparison has been done with the conventional methods in order to check the accuracy and robustness of the proposed scheme which is found to be97%.

关键词： Doubly fed transmission line ground distance relay high resistancefault simultaneous open conductor and ground fault single-line-to-ground fault NegativeZero sequence current Artificial neural network

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