- 标题
- 摘要
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- 实验方案
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A Lipschitz Optimization Based MPPT Algorithm for Photovoltaic System under Partial Shading Condition
摘要： The power–voltage curve of a photovoltaic (PV) array shows multiple power peaks under partially shading conditions (PSCs). Hence, conventional maximum power point tracking (MPPT) algorithms can not guarantee the maximum power output of the PV array. In this study, a novel Lipschitz optimization (LIPO) MPPT algorithm, which is effective under PSCs, is proposed and analyzed. Its tracking speed is very fast and tracking efficiency is above 98%. The characteristics of a PV array under PSCs are first analyzed and then the working principle of the proposed LIPO MPPT algorithm is explained. In order to validate the performance of the proposed algorithm, two popular MPPT algorithms, i.e., the modified particle swarm optimization (M-PSO) algorithm and the modified firefly optimization (M-firefly) algorithm, are chosen to compare with it. All three algorithms are fulfilled and compared with each other through both simulations and experiments and the results show that the proposed MPPT algorithm has good performance.
关键词： Global maximum power point (GMPP),maximum power point tracking (MPPT),Lipschitz optimization (LIPO),partially shaded condition (PSC)
更新于2025-09-11 14:15:04
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Improved Restricted Control Set Model Predictive Control (iRCS-MPC) Based Maximum Power Point Tracking of Photovoltaic Module
摘要： This paper presents a robust two stage maximum power point tracking (MPPT) system of the photovoltaic (PV) module using an improved restricted control set model predictive control (iRCS-MPC) technique. The suggested work is improved in two aspects; a revision in conventional P&O algorithm is made by employing three distinct step sizes for different conditions, and an improvement in conventional MPC algorithm. The improved MPC algorithm is based on the single step prediction horizon that provides less computational load and swift tracking of maximum power point (MPP) by applying the control pulses directly to the converter switch. The computer aided experimental results for various environmental scenarios revealed that compared with the conventional method (conventional P&O + MPC), for the PV power and inductor current, the undershoot and overshoot is decreased to 68% and 35% respectively under stiff environmental conditions. In addition, the settling time needed to reach a stable state is significantly reduced in the proposed system. The viability of the solution suggested is verified in MATLAB/Simulink and by hardware experimentation.
关键词： maximum power point tracking (MPPT),photovoltaic systems,MPC,Boost converter,dc-dc power conversion,model predictive control (RCS-MPC)
更新于2025-09-11 14:15:04
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[IEEE 2019 IEEE 10th International Symposium on Power Electronics for Distributed Generation Systems (PEDG) - Xi'an, China (2019.6.3-2019.6.6)] 2019 IEEE 10th International Symposium on Power Electronics for Distributed Generation Systems (PEDG) - The application of cascade power electronic transformer in large-scale photovoltaic power generation system
摘要： In this paper, a high frequency isolated photovoltaic dc side connection system based on dual active bridge (DAB) converter with multiple photovoltaic arrays with parallel input and cascade output is proposed. The power transmission capacity of DAB converter is analyzed, its phase-shifting control strategy is designed, and a 300kW/3kV photovoltaic power generation system model is built in MATLAB/Simulink for simulation. The simulation results verify the feasibility of the system structure and the effectiveness of the proposed control strategy.
关键词： maximum power point tracking (MPPT),PV array,photovoltaic power generation,dual active bridge (DAB)
更新于2025-09-11 14:15:04
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[IEEE 2019 Chinese Control And Decision Conference (CCDC) - Nanchang, China (2019.6.3-2019.6.5)] 2019 Chinese Control And Decision Conference (CCDC) - Event-triggered Dual-mode Control of Maximum Power Point Tracking for Photovoltaic Arrays
摘要： Photovoltaic power generation systems will switch between two situations: uniform illumination and local shadow. For maximum power point tracking (MPPT), the conventional strategy is often ef?cient in only one situation. But for both situations with switching, there face problems such that the tracking time may be too long or it may fall into the local maximum power point (LMPP). Aiming at these problems, in this paper, an event-triggered dual-mode control technology is proposed, which enables the system to work with high ef?ciency and high precision under both uniform illumination and local shadow. Under the uniform illumination, the maximum power point is tracked by the perturbation method (P&O), while in a local shaded environment, the current ?owing through the bypass diode acts as a trigger signal which enables Particle Swarm Optimization (PSO) to track the Global Maximum Power Point (GMPP). The simulation experiment by Matlab shows that in both the uniform illumination and local shadow, the algorithm of event-triggered dual-mode control is ef?cient in MPPT and has a fast and smooth transition between P&O and PSO, overcoming the problems of conventional strategy.
关键词： Event-triggered Dual-mode control,Photovoltaic power generation,Maximum power point tracking
更新于2025-09-11 14:15:04
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[IEEE 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Baltimore, MD, USA (2019.9.29-2019.10.3)] 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - A CMOS-Based Energy Harvesting Approach for Laterally-Arrayed Multi-Bandgap Concentrated Photovoltaic Systems
摘要： This paper presents an energy harvesting approach for a concentrated photovoltaics (CPV) system based on cell-block-level integrated CMOS converters. The CPV system, built upon the Laterally-Arrayed Multi-Bandgap (LAMB) cell structure, is a potentially higher-efficiency and lower-cost alternative to traditional tandem-based systems. The cells within a sub-module block are connected for approximate voltage matching, and a CMOS-based multi-input single-output converter harvests and combines the energy while performing maximum power point tracking (MPPT) locally. First, a comparison of modeled performances achievable with traditional tandem CPV and LAMB CPV with a MISO converter is presented using day-long outdoor measured solar spectrum. The model predicts on average >19% more energy can be extracted from LAMB modules on a typical day. Then, a prototype miniaturized MISO dc-dc converter operating at 10MHz is developed in a 130nm CMOS process. For 45-160mW power levels, the prototype converter achieves >92% nominal and >95% peak efficiency in a small form factor designed to fit within available space in a LAMB PV cell block. The results demonstrate the potential of the LAMB CPV architecture for enhanced solar energy capture.
关键词： energy harvesting,maximum power point tracking,concentrated photovoltaic systems,CMOS,MISO dc-dc converter,DC-DC power converters
更新于2025-09-11 14:15:04
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An Improved Particle Swarm Optimization Algorithm Suitable for Photovoltaic Power Tracking Under Partial Shading Conditions
摘要： The partial shading of a photovoltaic array repeatedly occurs in the natural environment, which can cause a failure of a conventional maximum power point tracking (MPPT) algorithm. In this paper, the convergence conditions of the standard particle swarm optimization (PSO) algorithm are deduced by the functional analysis, and then the influence of the random variables and inertia factor of the algorithm on the trajectory in the particle swarm optimization is analyzed. Based on the analysis results, an improved particle swarm optimization (IPSO) algorithm, which adopts both global and local modes to locate the maximum power point, is proposed. Compared to the standard PSO algorithm, in the improved PSO algorithm, many random and interfered variables are removed, and the structure is optimized significantly. The proposed algorithm is first simulated in MATLAB to ensure its capability. The feasibility of the approach is validated through physical implementation and experimentation. Results demonstrate that the proposed algorithm has the capability to track the global maximum power point within 3.3 s with an accuracy of 99%. Compared with five recently developed Global MPPT algorithms, the proposed IPSO algorithm achieved better performance in the maximum power tracking in the partial shading conditions.
关键词： partial shade,particle swarm optimization,Maximum power point tracking,photovoltaic array
更新于2025-09-11 14:15:04
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[IEEE 2019 54th International Universities Power Engineering Conference (UPEC) - Bucharest, Romania (2019.9.3-2019.9.6)] 2019 54th International Universities Power Engineering Conference (UPEC) - Design of an intelligent MPPT based on ANN using a real photovoltaic system data
摘要： Maximum power point tracking (MPPT) methods are a fundamental part in photovoltaic (PV) system design for increasing the generated power of a PV array. Whilst several methods have been introduced, the artificial neural network (ANN) is an attractive method for MPPT due to its less oscillation and fast response. However, accurate training data is a big challenge to design an optimized ANN-MPPT technique. In this paper, an ANN-MPPT technique based on a large experimental training data is proposed to avoid the system from having a high training error. Those data are collected during one year from experimental tests of a PV system installed at Brunel University, London, United Kingdom. The irradiation and temperature of weather conditions are selected as the input, and the available power at MPP from the PV system as the output of the ANN model. To assess the performance, the Perturb and Observe (P&O) and the proposed ANN-MPPT methods are simulated using a MATLAB/Simulink model for the PV system. The results show that the proposed ANN method accurately tracks the optimal maximum power point and avoids the phenomenon of drift problem, whilst achieving a higher output power when compared with P&O-MPPT method.
关键词： photovoltaic (PV),Perturb and Observe (P&O),Artificial Neural Network (ANN),Maximum power point tracking (MPPT)
更新于2025-09-11 14:15:04
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[IEEE 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET) - Kottayam, India (2018.12.21-2018.12.22)] 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET) - Performance Analysis of Solar Photovoltaic System with Fuzzy Based Variable Step Size MPPT Algorithm Using Matlab /Simulink
摘要： In the recent decades, Photovoltaic (PV) power generation has become one of the primary power source due to the advantages such as less maintenance and environmental benefits. Moreover, the generation source is ultimately free and abundant. However, the major barriers related to PV power generation are low power conversion efficiency, high cost of PV modules and nonlinearity in output power. Because of low power conversion efficiency, PV systems should work always at its Maximum Power Point (MPP). A power conditioning unit with Maximum Power Point Tracking (MPPT) technique is employed in the PV systems to harvest maximum power. The main function of MPPT is to detect the MPP for the given conditions and operate the system at that point. In this paper Fuzzy Logic Controller (FLC) based variable step size MPPT for a standalone solar PV system is presented. Solar PV system with Fuzzy based MPPT controller in Matlab /Simulink. The performance of proposed variable step size fuzzy MPPT algorithm is studied for different input conditions and analyzed in terms of performance parameters such as tracking speed, steady state oscillations, response under variations in irradiance and temparature, average output power and output power ripple. The results are compared with Variable Step Size Incremental Conductance (VSS InC) MPPT algorithm and conventional InC based PV system.
关键词： Solar Photovoltaic (SPV),Fuzzy Logic Control (FLC),MATLAB/Simulink,Simulation,Variable Step Size Incremental Conductance (VSS InC),Maximum Power Point Tracking (MPPT)
更新于2025-09-11 14:15:04
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[IEEE 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - Gramado, Brazil (2019.9.15-2019.9.18)] 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - An Adaptive Perturb and Observe Method with Clustering for Photovoltaic Module with Smart Bypass Diode under Partial Shading
摘要： The photovoltaic maximum power point tracking using perturb and observe method has a fixed step size, where a small step size has a slower time response and more accurate steady-state, while a large step size is the opposite. This work proposes an adaptive step size, proportional to the difference between actual and previous power sample, providing a fast time response and reducing the oscillations at steady-state. The oscillations are smaller with adaptive step size, but they are not annulled and the method presents loss by power oscillations. The clustering is used to eliminate this loss, setting the result of the simple average of the last five voltage samples. The enhanced method has been tested on a 72-cell photovoltaic module with a smart bypass diode per cell under partial shading. Modeling and simulation have been implemented using MATLAB/Simulink. The proposal obtained a faster time response and elimination of oscillations at steady-state.
关键词： Smart Bypass Diode,Adaptive Perturb and Observe with Clustering,Maximum Power Point Tracking,Photovoltaic Solar Module,Partial Shading
更新于2025-09-11 14:15:04
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Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning
摘要： The maximum power point tracking (MPPT) technique is often used in photovoltaic (PV) systems to extract the maximum power in various environmental conditions. The perturbation and observation (P&O) method is one of the most well-known MPPT methods; however, it may face problems of large oscillations around maximum power point (MPP) or low-tracking efficiency. In this paper, two reinforcement learning-based maximum power point tracking (RL MPPT) methods are proposed by the use of the Q-learning algorithm. One constructs the Q-table and the other adopts the Q-network. These two proposed methods do not require the information of an actual PV module in advance and can track the MPP through offline training in two phases, the learning phase and the tracking phase. From the experimental results, both the reinforcement learning-based Q-table maximum power point tracking (RL-QT MPPT) and the reinforcement learning-based Q-network maximum power point tracking (RL-QN MPPT) methods have smaller ripples and faster tracking speeds when compared with the P&O method. In addition, for these two proposed methods, the RL-QT MPPT method performs with smaller oscillation and the RL-QN MPPT method achieves higher average power.
关键词： photovoltaic (PV) system,Q-learning,reinforcement learning,maximum power point tracking (MPPT),Q-network
更新于2025-09-11 14:15:04