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[IEEE 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) - Sukkur, Pakistan (2020.1.29-2020.1.30)] 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) - Maximum Power Extraction from Photovoltaic System using Integral Sliding Mode Control
摘要： In this paper, an Integral Sliding Mode Control (ISMC) is presented to extract maximum power from photovoltaic (PV) system in the presence of uncertainties. The considered SISO system is affected by bounded uncertainty, which is directly effecting desire output of PV system. The main objective of this paper is to design such closed loop control system which can tolerate the uncertainty and make possible the maximum power extraction from PV system. Hence, ISMC is proposed as a robust control mechanism against these uncertainties. The efficiency of the presented concept is demonstrated in detail, using results of numerical simulations.
关键词： PV system,Bounded uncertainty,MPPT,ISMC
更新于2025-09-23 15:21:01
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Performance evaluation of a MPPT controller with model predictive control for a photovoltaic system
摘要： Efficiency has been a major factor in the growth of photovoltaic (PV) systems. Different control techniques have been explored to extract maximum power from PV systems under varying environmental conditions. This paper evaluates the performance of a new improved control technique known as model predictive control (MPC) in power extraction from PV systems. Exploiting the ability of MPC to predict future state of controlled variables, MPC has been implemented for tacking of maximum power point (MPP) of a PV system. Application of MPC for maximum power point tracking (MPPT) has been found to result into faster tracking of MPP under continuously varying atmospheric conditions providing an efficient system. It helps in reducing unwanted oscillations with an increase in tracking speed. A detailed step by step process of designing a model predictive controller has been discussed. Here, MPC has been applied in conjunction with conventional perturb and observe (P&O) method for controlling the dc-dc boost converter switching, harvesting maximum power from a PV array. The results of MPC controller has been compared with two widely used conventional methods of MPPT, viz. incremental conductance method and P&O method. The MPC controller scheme has been designed, implemented and tested in MATLAB/Simulink environment and has also been experimentally validated using a laboratory prototype of a PV system.
关键词： maximum power point tracking (MPPT),prediction model,Model predictive control (MPC),cost function,photovoltaic (PV),renewable energy
更新于2025-09-23 15:21:01
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Maximum Power Point Tracking Technology of Photovoltaic Array under Partial Shading Based On Adaptive Improved Differential Evolution Algorithm
摘要： In the case of partial shading conditions, there will be more than one maximum power point (MPP) in photovoltaic (PV) array. The traditional maximum power point tracking (MPPT) methods are easy to get in the local maximum power point (LMPP) and fail. Based on the standard di?erential evolution (DE) algorithm, the mutation strategy, scaling factor F, and cross factor CR of the algorithm are optimized. Also, the population position variance δ2 is used to prevent falling into LMPP. Finally, the conditions for algorithm termination and restart are set. It is veri?ed by simulation that the method has fast convergence speed, high accuracy, and can adapt well to changes in the external environment. The improved DE algorithm has a great advantage in MPPT.
关键词： photovoltaic array,di?erential evolution algorithm,MPPT,DC-DC converter
更新于2025-09-23 15:21:01
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FPGA-based active disturbance rejection control and maximum power point tracking for a photovoltaic system
摘要： This paper presents a system for tracking the maximum power point (MPP) and output voltage regulation of photovoltaic cells. The system includes two stages of cascading dc/dc converters: the first one is a boost converter used for tracking the MPP using the perturb and observe algorithm. Meanwhile, a buck converter regulates the output voltage employing the active disturbance rejection control based on an extended state observer and the differential flatness property. The hardware architecture was modeled using high-level tools of hardware abstraction and implemented in a FPGA Artix-7 made by Xilinx. Finally, the performance of the proposed system is shown through a series of experiments that consisted of changing the irradiance and temperature conditions and changes in the system parameters.
关键词： PV system,MPPT,active disturbance rejection control,perturb and observe
更新于2025-09-23 15:21:01
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[IEEE 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Karachi, Pakistan (2020.3.26-2020.3.27)] 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Soft Computing Technique based Nonlinear Sliding Mode Control for Stand-Alone Photovoltaic System
摘要： Energy production capability of a photovoltaic (PV) system is extensively depends upon the ambient temperature (T) and solar irradiance (Ee). In order to adapt the ever increasing interest in energy, the PV array must be operated at the maximum power point (MPP). However, due to varying climatic conditions, there is a low energy ef?ciency problem. In this research article, a robust and ef?cient nonlinear sliding mode control (SMC) based maximum power point tracking (MPPT) technique is designed to extract maximum power from the PV array. This study uses arti?cial feed-forward neural network (AFNN) to generate the reference voltage for MPPT using non-inverting DC-DC Buck-Boost converter. Asymptotically convergence is ensures using Lyapunov stability criteria. The MATLAB/SIMULINK platform is used to design, simulate and test the performance of the proposed technique. To further validate the proposed control technique in terms of ef?ciency, tracking speed and robustness, results are compared with the non-linear backstepping (B) technique under continuous conditions of environment, faults and parametric uncertainties.
关键词： Buck-Boost converter,Neural Network,MPPT,Photovoltaic,SMC
更新于2025-09-23 15:21:01
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[IEEE 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Karachi, Pakistan (2020.3.26-2020.3.27)] 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Artificial Intelligence based Nonlinear Integral Back-stepping Control Approach for MPPT of Photovoltaic System
摘要： The energy demand of the world has been intensively increased since last two decades. The need of energy is forcing the think tanks of the developed countries to move towards the alternative energy resources. Solar energy is the most suitable solution to overcome the energy crises. In this regard, this article presents the nonlinear integral back-stepping (IB) control approach for maximum power extraction of stand-alone photovoltaic (PV) system. The proposed control strategy gives robustness against constantly varying conditions of environment. Non-inverting case of buck-boost DC-DC converter is used as interface between load and PV array. Radial basis function neural network (RBFNN) is generated the reference (Vref ) under different climatic conditions for the tracking of the developed control scheme. IB control technique is also checked under faulty conditions. The Simulations are preformed in the environment of MATLAB/Simulink. Moreover, the proposed technique results are compared with perturb and observe (P&O) maximum power point tracking (MPPT) technique.
关键词： Neural network,MPPT,Solar energy,IB
更新于2025-09-23 15:21:01
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Comparative Analysis of Intelligent Controller Based MPPT for Photovoltaic System with Super Lift Boost Converter
摘要： In recent years, the electrical energy demand increases gradually and the power generation does not meet the demand due to lack of fossil fuel and environmental issues. The only solution is to use renewable energy sources for generating electricity and meet the consumers demand. In this paper, photovoltaic power system analyses their performance under various weather conditions. The objective of this paper is comparing the different intelligent controllers such as Fuzzy, ANFIS and Hybrid Fuzzy & Firefly Algorithm (HFFA) for Maximum Power Point Tracking (MPPT) of 100 Watts PV system using a Super Lift Boost Converter (SLBC). The proposed intelligent controller is designed and simulated in MATLAB environment under various weather conditions. The simulation results have been analyzed and the performance of the proposed model evaluated with changing irradiation conditions. Finally, the performance of Hybrid Fuzzy and firefly based MPPT has been suggested as the optimum controller for the photovoltaic system.
关键词： photovoltaic,ANFIS,Fuzzy Logic,MPPT,MATLAB,HFFA,super-lift boost converter
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Data-integrity Checks and Balances in Monitoring of a Solar PV System
摘要： This paper proposes to perform certain integrity checks and balances to omit the wrong data in the monitoring of a solar PV plant. Further, these checks and balances are segregated into three types: basic, specific, and pattern checks. The former is performed on the data collected from all the types of sensors. However, the second check is performed on the data collected from the specific instruments. These checks are specific to the site, instrument, parameter, etc. The third check verifies the shape of profiles between the data of different sections of the PV system. For the data-inclusion/deletion purpose, the parameters of PV plant are segregated into a triangle-hierarchy of highest-least priority. Some of the proposed checks are performed on the raw data collected from a grid-tied 271 kW PV plant and 6.4 kW test PV plant. The results have indeed identified some of the bad data and validated the proposed checks.
关键词： photovoltaic (PV),PV plant health monitoring,data quality,data integrity,PV plant data,maximum power point tracking (MPPT)
更新于2025-09-23 15:21:01
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[IEEE 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Karachi, Pakistan (2020.3.26-2020.3.27)] 2020 International Conference on Emerging Trends in Smart Technologies (ICETST) - Terminal Sliding Mode Nonlinear Control Strategy for MPPT Application of Photovoltaic System
摘要： The electricity generation from the photovoltaic (PV) system has been considered as an alternative energy resource to the fossil fuels since last decade. Solar energy is the most abundantly available renewable resource on earth. However, source to load conversion efficiency of PV system is low but installation cost is appreciable. In order to achieve maximum power, the system must be operated at maximum power point (MPP). Maximum power point tracking (MPPT) is very essential in the process of maximum power extraction of the PV system. This research article presents the terminal sliding mode control (TSMC) nonlinear MPPT control paradigm for stand-alone PV system using buck-boost converter. Radial basis function neural network (RBF NN) is generated the reference for the proposed TSMC in controller. The simulations are performed in MATLAB/Simulink. To evaluate the developed controller performance, TSMC is tested under varying conditions of environment and resistive load with fault and uncertainty. Moreover, proposed nonlinear TSMC MPPT control technique is compared with the conventional techniques such as proportional integral derivative (PID) and perturb and observe (P&O). The finite time stability analysis is explained via Lyapunov function.
关键词： TSMC,Finite time stability,Buck-Boost converter,MPPT,RBF NN
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) - Kuala Lumpur, Malaysia (2019.8.27-2019.8.29)] 2019 IEEE International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) - Power Electronic Interface for Low Voltage DC Link Using Photovoltaic Cells with ANN based MPPT
摘要： The aim of this paper is to design and develop low voltage direct current system within building structures to cater to low power load demands like LED lights, BLDC fans, desktops computers etc. The intended system comprises of a solar panel, a buck converter, a battery and a boost converter. The output of boost converter will be 48 V direct current which can cater to loads below 1 kw. The buck converter regulates the output of solar panel to constant voltage, which is stored in a battery and boosted to 48 V direct current as per household requirements. The proposed system will simplify the transmission and distribution of energy by ensuring direct current supply to appliances which are devised to run on the same. This will rule out the need for rectifier within household appliances, thereby reducing their size and cost. The future scope of this project lies in the fact that the entire system can be integrated into a module which can be used in inaccessible and rural areas by dint of a solar panel that will serve as source and the output of module will be 48V which can be directly used for household purposes. The concept of artificial neural network is incorporated for maximum power point tracking, maintaining constant output voltage.
关键词： MPPT,Low Voltage DC,ANN
更新于2025-09-23 15:21:01