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FaultMonitoring Strategy for pv system Based on I-V Feature Library

Energy Engineering 2024年第3期121卷 643-660页

作者： Huaxing Zhao Yanbo Che Gang Wen Yijing Chen School of Electrical and Information Engineering Tianjin UniversityTianjin300000China State Grid Shuozhou Electric Power Supply Company Shuozhou036000China China Huaneng Clean Energy Research lnstitute Technology Co. Ltd.Beijing102209China

Long-term use in challenging natural conditions is possible for photovoltaic modules,which are extremely prone to failure.Failure to diagnose and address faults in Photovoltaic(pv)power systems in a timely manner can cause permanent damage to pv modules and,in more serious cases,fires.Therefore,research into photovoltaic module defect detection techniques is crucial for the growth of the photovoltaic sector as well as for maintaining national economic prosperity and ensuring public safety.Considering the drawbacks of the current real-time and historical data-based methods for monitoring distributed pv systems,this paper proposes a method for monitoring pv systems at the module or string level that can be achieved by monitoring only electrical signals.The approach doesn’t need a lot of tests to get the operational data of pv modules beforehand and only requires theoretical feature libraries of pv modules through panel parameter calculations.The present operating conditions and the open-circuit and short-circuit faults can be precisely identified by comparing the observed open-circuit voltage and short-circuit current with the corresponding data in the theoretical feature library.After that,by comparing the measured maximum power point voltage and current with the corresponding data in the theoretical feature library through the threshold method,aging and shadowing faults can be accurately determined.Experimental testing was done to see whether the suggested method was effective.The results show that the proposed technique is able to diagnose open-circuit faults,short-circuit faults,aging faults,and shadowing faults with shadow occlusion above 20%.

关键词： pv system lambert W function threshold method

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Feedback linearization based control for weak grid connected pv system under normal and abnormal conditions

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Frontiers in Energy 2020年第2期14卷 400-409页

作者： Rahul SHARMA Sathans SUHAG Department ofElectrical Engineering NITKurukshetra 136119India

This paper proposes a control strategy for interface of distributed energy sources into the weak grid system with a focus on the energy and ancillary services.A novel controller has been designed and implemented to tackle the challenges of coupling terms in the LCL filter,the transient behavior under sudden changes,and the voltage support under fault condition using the feedback linearization technique.The controller proposed has been implemented on the pv system connected with the weak grid using the LCL filter and the performance of the controller has been verified using Matlab/Simulink through simulation under different conditions.The results of the controller proposed have been compared with the conventional PI dual loop controller.The simulation results obtained demonstrate the effectiveness and simplicity of the controller design strategy.

关键词： pv system grid interface feedback linearization inverter LCL filter

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Design of a P-&-O algorithm based MPPT charge controller for a stand-alone 200W pv system

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Protection and Control of Modern Power systems 2018年第1期3卷 268-275页

作者： Salman Salman Xin AI Zhouyang WU State Key Laboratory of Alternate Electrical Power system with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China

Solar cells convert sun light into electricity,but have the major drawbacks of high initial cost,low photo-conversion efficiency and intermittency.The current-voltage characteristics of the solar cells depend on solar insolation level and temperature,which lead to the variation of the maximum power point(MPP).Herein,to improve photovoltaic(pv)system efficiency,and increase the lifetime of the battery,a microcontroller-based battery charge controller with maximum power point tracker(MPPT)is designed for harvesting the maximum power available from the pv system under given insolation and temperature conditions.Among different MPPT techniques,perturb and observe(P&O)technique gives excellent results and thus is used.This work involves the design of MPPT charge controller using DC/DC buck converter and microcontroller.A prototype MPPT charge controller is tested with a 200 W pv panel and lead acid battery.The results show that the designed MPPT controller improves the efficiency of the pv panel when compared to conventional charge controllers.

关键词： pv system Maximum power point tracker(MPPT) Perturb and observe(P&O)technique Charge controller Microcontroller

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Performance Analysis of a Rooftop Hybrid Connected Solar pv system

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Energy Engineering 2022年第4期119卷 1729-1744页

作者： Hasan Falih Ahmed J.Hamed Abdul Hadi N.Khalifa Engineering Technical College Middle Technical UniversityBaghdad10074Iraq

In the present work,a 5-kW hybrid pv solar system was installed on the roof of a house in Diyala,Iraq(33.77°N,45.14°E elevation 44 m).The system consists of two strings,where each string consists of nine polycrystalline pv modules with 355 Wp in series,and the two strings are in parallel.The energy storage system(ESS)consists of two parallel strings,each with four 12 V and 150 Ah tubular deep cycle batteries in series.A hybrid inverter of 5 kW rated power was operated in different modes.The results showed that May’s monthly energy consumption was about 822.9 and 1085 kWh,respectively.The percentage distribution of the DC energy produced was about 1%system energy losses,27.9%was used to charge the ESS,34.3%was used to feed the grid,and the remaining 37.64%was used to share the load.The energy percentage sharing the load was 16.67%from ESS,33.33%from the pv system,and 50%purchased.The average daily reference,array,and final yields were 6.07,4.327,and 3.991 h/day,respectively.The average array and load efficiencies were 12.3%and 92.24%,with the performance ratio at 65.4%.

关键词： Solar energy pv system final yield photovoltaic installations performance ratio hybrid pv system

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Fault Identification and Islanding in DC Grid Connected pv system

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Circuits and systems 2016年第10期7卷 2904-2915页

作者： M. Mano Raja Paul R. Mahalakshmi Murugesan Karuppasamypandiyan Ananthan Bhuvanesh Rajendran Jai Ganesh Department of EEE Nehru Institute of Engineering & Technology Coimbatore India Department of EEE Kumaraguru College of Technology Coimbatore India Department of EEE Kalasalingam University Krishnankoil India Department of EEE Mepco Schlenk Engineering College Sivakasi India Department of EEE K. Ramakrishnan College of Technology Tiruchirapalli India

Nowadays, the DC distribution system has been suggested, as a replacement for the AC power distribution system with electric propulsion. This idea signifies a fresh approach of issuing energy for low-voltage installations. It can be used for any electrical application up to 20 MW and works at a nominal voltage of 1000 V DC. The DC distribution system is just an extension of the multiple DC links that previously available in all propulsion and thruster drives, which typically comprise more than 80% of the electrical power consumption on electric propulsion vessels. A fault detection and islanding scheme for DC grid connected pv system is presented in this paper. Unlike traditional ac distribution systems, protection has been challenging for dc systems. The goals of this paper are to classify and detect the fault in the pv system as well as DC grid and to isolate the faulted section so that the system keeps operating without disabling the entire system. The results show the measured values of power at pv panel and DC grid side under different fault condition, which indicates the type of fault that occurs in the system.

关键词： pv system DC Grid Fault Identification Islanding

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Hybrid MPPT approach using Cuckoo Search and Grey Wolf Optimizer for pv systems under variant operating conditions

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Global Energy Interconnection 2022年第6期5卷 627-644页

作者： Jinan Abdulhasan Salim Baraa M.Albaker Muwafaq Shyaa Alwan M.Hasanuzzaman College of Engineering Al-Iraqia UniversitySaba’a Abkar CompexBaghdadIraq Higher Institution Centre of Excellence(HICoE) UM Power Energy Dedicated Advanced Centre(UMPEDAC)Level 4Wisma R&DUniversity of MalayaJalan Pantai Baharu59990 Kuala LumpurMalaysia

Photovoltaic(pv)systems are adversely affected by partial shading and non-uniform conditions.Meanwhile,the addition of a bypass shunt diode to each pv module prevents hotspots.It also produces numerous peaks in the pv array’s power-voltage characteristics,thereby trapping conventional maximum power point tracking(MPPT)methods in local peaks.Swarm optimization approaches can be used to address this issue.However,these strategies have an unreasonably long convergence time.The Grey Wolf Optimizer(GWO)is a fast and more dependable optimization algorithm.This renders it a good option for MPPT of pv systems operating in varying partial shading.The conventional GWO method involves a long conversion time,large steady-state oscillations,and a high failure rate.This work attempts to address these issues by combining Cuckoo Search(CS)with the GWO algorithm to improve the MPPT performance.The results of this approach are compared with those of conventional MPPT according to GWO and MPPT methods based on perturb and observe(P&O).A comparative analysis reveals that under non-uniform operating conditions,the hybrid GWO CS(GWOCS)approach presented in this article outperforms the GWO and P&O approaches.

关键词： Cuckoo Search GWO MPPT Hybrid MPPT pv system Luo DC-DC converter

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A Survey of the Researches on Grid-Connected Solar Power Generation systems and Power Forecasting Methods Based on Ground-Based Cloud Atlas

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Energy Engineering 2023年第2期120卷 385-408页

作者： Xing Deng Feipeng Da Haijian Shao Xia Wang School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212003China School of Information Science and Technology Nantong UniversityNantong226019China

Photovoltaic power generating is one of the primary methods of utilizing solar energy resources,with large-scale photovoltaic grid-connected power generation being the most efficient way to fully utilize solar energy.In order to provide reference strategies for pertinent researchers as well as potential implementation,this paper tries to provide a survey investigation and technical analysis of machine learning-related approaches,statistical approaches and optimization techniques for solar power generation and forecasting.Deep learning-related methods,in particular,can theoretically handle arbitrary nonlinear transformations through proper model structural design,such as hidden layer topology optimization and objective function analysis to save information that can increase forecasting accuracy while filtering out irrelevant or less affected data for forecasting.The research’s results indicate that RBFNN-AG performed the best when applying the predetermined number of days,with an NRMSE value of 4.65%.RBFNN-AG performs better than sophisticated models like DenseNet(5.69%),SLFN-ELM(5.95%),and ANN-k-means-linear regression correction(6.11%).Additionally,scenario application and pv system investment techniques are provided to evaluate the current condition of new energy development and market trends both domestically and internationally.

关键词： Photovoltaic power generating deep learning pv system

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An Efficient Honey Badger Optimization Based Solar MPPT Under Partial Shading Conditions

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Intelligent Automation & Soft Computing 2023年第2期35卷 1311-1322页

作者： N.Rajeswari S.Venkatanarayanan Department of Electrical and Electronics Engineering Sri Ràaja Raajan College of Engineering and TechnologySivagangaTamilnadu630301India Department of Electrical and Electronics Engineering K.L.N.College of EngineeringSivagangaiTamilnadu630612India

Due to the enormous utilization of solar energy,the photovoltaic(pv)system is used.The pv system is functioned based on a maximum power point(MPP).Due to the climatic change,the Partial shading conditions have occurred under non-uniform irradiance conditions.In the pv system,the global maximum power point(GMPP)is complex to track in the P-V curve due to the Partial shad-ing.Therefore,several tracking processes are performed using various methods like perturb and observe(P&O),hill climbing(HC),incremental conductance(INC),Fuzzy Logic,Whale Optimization Algorithm(WOA),Grey Wolf Optimi-zation(GWO)and Flying Squirrel Search Optimization(FSSO)etc.Though,the MPPT is not so efﬁcient when the partial shading is increased.To increase the efﬁciency and convergences in MMPT,the Honey Badger optimization(HBO)algorithm is presented.This HBO model is motivated by the excellent foraging behaviour of honey badgers.This HBO model is used to achieve the best solution in GMPP tracking and speed convergence.The HBO methodology is also com-pared with prior P&O,WOA and FSSO methods using MATLAB.Therefore,the experiment shows that the HBO method is performed a higher tracking than all prior methods.

关键词： pv system gmpp tracking convergence honey badger optimization digging and honey phase

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Smart-Grid Monitoring using IoT with Modified Lagranges Key Based Data Transmission

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Intelligent Automation & Soft Computing 2023年第3期35卷 2875-2892页

作者： C.K.Morarji N.Sathish Kumar Department of Electronics and Communication Engineering Rohini College of Engineering and TechnologyKanyakumariTamilnadu629401India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering CollegeCoimbatoreTamilnadu641022India

One of the recent advancements in the electrical power systems is the smart-grid technology.For the effective functioning of the smart grid,the process like monitoring and controlling have to be given importance.In this paper,the Wireless Sensor Network(WSN)is utilized for tracking the power in smart grid applications.The smart grid is used to produce the electricity and it is connected with the sensor to transmit or receive the data.The data is transmitted quickly by using the Probabilistic Neural Network(PNN),which aids in identifying the shortest path of the nodes.While transmitting the data from the smart grid to the(Internet of Things)IoT web page,it is secured by introducing the secret keys between the neighbouring nodes through the process of key-management.In this method,the combination of Lagrange’s theorem and the Location Based Key(LBK)management is used for better security performance.This approach deli-vers optimal performance in terms of security,throughput,packet loss and delay,which are comparatively better than the existing methods.

关键词： WSN smart grid Lagrange LBK PNN pv system IoT SCADA

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Hybrid Optimized PI Controller Design for Grid Tied pv Based Electric Vehicle

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Intelligent Automation & Soft Computing 2023年第5期36卷 1523-1545页

作者： J.Aran Glenn Srinivasan Alavandar Department of Electrical and Electronics Engineering AMET Deemed to be UniversityChennaiTamil NaduIndia Department of Electrical and Electronics Engineering Agni College of TechnologyChennaiTamil NaduIndia

Nowadays,researchers are becoming increasingly concerned about developing a highly efﬁcient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change.The introduction of Electric Vehicles(EVs)solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulﬁlled by the installation and expansion of solar-powered Photovoltaic(pv)systems.Hence,this paper focuses on designing an effective pv based EV charging system that aids in stepping towards the achievement of a pollution free future.For overcoming the inherent intermittency associated with pv,a novel DC-DC converter is designed by integrating both Trans Z-source con-verter and Luo converter,which offers remarkable beneﬁts of high conversion range,lesser voltage stress and excellent efﬁciency.A novel robust Lion Grey Wolf Optimized Proportional Integral(LGWO-PI)controller is designed for sig-niﬁcantly strengthening the operation of the integrated converter in terms of peak overshoot,Total Harmonic Distortion(THD)and settling time.A 3’Voltage Source Inverter(VSI)is employed to convert the stable DC output from the pv sys-tem to AC,which is then used for driving the Brushless Direct Current Motor(BLDC)motor of EV.The speed of the BLDC is regulated using a PI controller.The BLDC motor gets the power supply from the grid during the unavailability of pv based power supply.The grid is integrated with the designed EV charging system through a 1’VSI and the process of grid voltage synchronization is carried out with the application of PI controller.The simulation for evaluating the operation of the presented EV charging system is done using MATLAB and the attained out-comes have validated that this introduced methodology delivers enhanced perfor-mance with optimal efﬁciency of 97.6%and lesser THD of 2.1%.

关键词： pv system trans Z-source based luo converter LGWO-PI controller BLDC motor PI controller single phase VSI three phase VSI

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