The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.

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Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques

The energy utilization efficiency of commercial photovoltaic (PV) pumping systems can be significantly improved by employing simple perturb and observe (P&O) maximum power point tracking algorithms. Two such P&O implementation techniques, reference voltage perturbation and direct duty ratio perturbation, are commonly utilized in the literature but no clear criteria for the suitable choice of method or algorithm parameters have been presented. This paper presents a detailed theoretical and experimental comparison of the two P&O implementation techniques on the basis of system stability, performance characteristics, and energy utilization for standalone PV pumping systems. The influence of algorithm parameters on system behavior is investigated and the various advantages and drawbacks of each technique are identified for different weather conditions. Practical results obtained using a 1080-Wp PV array connected to a 1-kW permanent magnet dc motor-centrifugal pump set show very good agreement with the theoretical analysis and numerical simulations.

Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications

The photovoltaic (PV) system is one of the renewable energies that attract the attention of researchers in the recent decades. The PV generators exhibit nonlinear I–V and P–V characteristics. The maximum power produced varies with both irradiance and temperature. Since the conversion efficiency of PV arrays is very low, it requires maximum power point tracking (MPPT) control techniques. The maximum power point tracking (MPPT) is the automatic control algorithm to adjust the power interfaces and achieve the greatest possible power harvest, during moment to moment variations of light level, shading, temperature, and photovoltaic module characteristics. The purpose of the MPPT is to adjust the solar operating voltage close to the MPP under changing atmospheric conditions. It has become an essential component to evaluate the design performance of PV power systems. This investigation aims to assess different MPPT techniques, provide background knowledge, implementation topology, grid interconnection of PV and solar microinverter requirements presented in the literature, doing depth comparisons between them with a brief discussion. The MPPT merits, demerits and classification, which can be used as a reference for future research related to optimizing the solar power generation, are also discussed. Conventional methods are easy to implement but they suffer from oscillations at MPP and tracking speed is less due to fixed perturb step. Intelligent methods are efficient; oscillations are lesser at MPP in steady state and tracked quickly in comparison to conventional methods.

MPPT techniques for photovoltaic applications

The application of soft computing methods for MPPT of PV system: A technological and status review

Fuzzy logic is used to define a new quantity called the battery working state (BWS), which is based on both battery terminal voltage and state of charge (SOC), to overcome the problem of battery over-discharge and associated damage resulting from inaccurate estimates of the SOC. The BWS is used by a fuzzy logic energy-management system of a plug-in series hybrid electric vehicle (HEV) to make a decision on the power split between the battery and the engine, based on the BWS and vehicle power demand, while controlling the engine to work in its fuel economic region. The fuzzy logic management system was tested in real time using an HEV simulation test bench with a real battery in the loop. Simulation results are presented to demonstrate the performance of the proposed fuzzy logic energy-management system under different driving conditions and battery SOCs. The results indicate that the fuzzy logic energy-management system using the BWS was effective in ensuring that the engine operates in the vicinity of its maximum fuel efficiency region while preventing the battery from over-discharging.

Energy and Battery Management of a Plug-In Series Hybrid Electric Vehicle Using Fuzzy Logic

The paper presents a simulation study and an experimental implementation of a fuzzy logic controller (FLC) for Cuk converter in a stand alone photovoltaic (PV) energy scheme. DC-DC converters are used to convert the unregulated DC input into a regulated DC output at a desired voltage level. A FL algorithm is selected and used to control the PV nonlinear system. The control objective for Cuk converter is to move the operating point of the PV system to its peak power point. A system that consists of a PV generator, converter, AC PWM inverter and load models is simulated, analyzed, and experimentally implemented. The simulated system with FLC is investigated at different solar insolation levels. The fixed structure FLC shows a robust performance when applied on a wide operating range of the proposed converter and AC PWM inverter.

Fuzzy logic implementation for photovoltaic maximum power tracking

In this paper, Switched Reluctance Motor (SRM) for electric vehicle (EV) is designed using finite element method (FEM). The static torque of SRM is estimated with the magnetic field analysis. The temperature rise with time of SRM is estimated with the heat transfer analysis. First, the static torque and temperature rise with time of 600W SRM for sample machine are measured in the experiment, and they are compared with the calculated results using FEM under the same conditions. The validity of magnetic field analysis and heat transfer analysis is verified by the comparisons. Then, the 60 [kW] SRM for EV, which has the output characteristics equal to 1500 [cc] gasoline engine, is designed with the magnetic field analysis and heat transfer analysis.

Design Using Finite Element Analysis of Switched Reluctance Motor for Electric Vehicle

In this paper, a Switched Reluctance Motor (SRM) employed in an electric vehicle (EV) is designed using the finite element method (FEM). The static torque of the SRM is estimated through magnetic field analysis. The SRM temperature rise over operation time is estimated through heat transfer analysis. First, static torque and temperature rise over the time of 600W SRM is included in the experiment set, and are compared with the calculated results using the FEM under the same conditions. The validity of the magnetic field analysis and heat transfer analysis is verified by the comparisons. In addition, a 60 [㎾] SRM employed in an EV, whose output characteristics are equal to a 1500 [cc] gasoline engine, is designed under magnetic field analysis and heat transfer analysis.

Design Using Finite Element Analysis of a Switched Reluctance Motor for Electric Vehicle

The paper presents a simulation study and an experimental implementation of a fuzzy logic controller (FLC) for a Cu/spl circ/k converter in a stand alone photovoltaic (PV) energy scheme. DC-DC power converters are used to convert the unregulated DC input into a regulated DC output at a desired voltage level. An FLC algorithm is selected and used to control the nonlinear PV power system. The control objective for the Cu/spl circ/k converter is to move the operating point of the PV system to its peak power point. A system that consists of PV generator, converter, AC PWM inverter and load models is simulated, analyzed and experimentally implemented. The simulated system with FLC is investigated at different solar insolation levels. The fixed structure FLC shows a robust performance when applied on a wide operating range of the proposed converter, and AC PWM inverter.

This paper presents requirements, detailed analysis, and operation of six converter types used with 3- phase 6/4 switched reluctance motor (SRM). These converters are R-dump, C-dump, C-dump with freewheeling transistor, asymmetric, series, and parallel type. The simulation results are made by MATLAB/SIMULINK package. The paper also introduced why the asymmetric bridge converter type is the best one especially for high speeds.

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Maged N. F. Nashed

Papers

Fuzzy logic implementation for photovoltaic maximum power tracking

Design Using Finite Element Analysis of Switched Reluctance Motor for Electric Vehicle

Design Using Finite Element Analysis of a Switched Reluctance Motor for Electric Vehicle

Fuzzy logic implementation for photovoltaic maximum power tracking

Studying Different Types of Power Converters Fed Switched Reluctance Motor