In this paper the maximum power point tracking (MPPT) algorithms for wind energy systems are reviewed. As the amounts of power produced in wind power plants is changing due to the instantaneous changing nature of the wind, it is desirable to determine the one optimal generator speed that ensures maximum energy yield. Thus, it is important to include a controller that can track the maximum peak regardless of wind speed. Categorizing the MPPT algorithms can be done regarding whether it has used sensors or not, as well as according to the techniques used to locate the peak value. The performance of different MPPT algorithms is compared on the basis of ability to achieve the maximum energy yield and various speed responses. According to available simulation results in the literature, in cases through which the flexibility and simplicity in implementations is considered, the perturbation and observation (P&O) method is preferred, but difficulties in determining the optimum step-size are the restrictions of this method. Due to its simplicity, the best MPPT method for wind energy systems has found to be the optimal torque control (OTC).

This paper presents the output voltage control and execution of a novel non-isolated high step-up (NIHS) DC-DC converter connected to a solar photovoltaic (PV) based DC microgrid system. The proposed converter provides a high output voltage conversion ratio over smaller duty cycles, small inductors, low cost, and high efficiency to enhance the level of the generated voltages of PV. Also, to overcome the drawback of PV, the detailed operation of maximum power point tracking (MPPT) for the novel boost DC-DC converter topology is presented. A control algorithm, modified perturb and observe (MP&O), is put forward to assure that the maximum power is extracted from PV at any environmental condition. It regulates the output voltage of the PV system to the desired DC bus voltage. This technique is compared with the Incremental Conductance (INC) and conventional P&O algorithm in terms of their computational complexity and oscillations near maximum power point (MPP) using MATLAB & Simulink. The focus is on the continuous conduction mode of the proposed converter. To demonstrate the effectiveness of the proposed converter, operation modes, and technical analysis are conducted. Also, the experimental results of a 200 W-12V/120V, 25 kHz prototype are given and discussed to justify the suggested converter.

Photovoltaic (PV) panel produces electricity depending on a variety of characteristics, including the PV module model, design specifications, and ambient circumstances such as temperature and sun irradiation. To analyze and model the effect of these factors on PV performance, a PV model is significant to be studied and modeled in advance. It is desirable to be compatible with the real-physical behavior of the PV panel. This paper presents mathematical modeling, design, and simulation of the three-diode model (3DM) MPPT controller instead of using conventional single/double diode PV models. The proposed PV model is analyzed, verified, and simulated at various temperature and irradiance levels. Furthermore, Particle Swarm Optimization (PSO) as a multi-objective algorithm is used for the Maximum Power Point Tracking MPPT controller to enhance the performance of the module and PV array system. A DC/DC boost converter is combined with the proposed 3DM model and connected through a resistive load. Results show that adopting PSObased MPPT improves the performance of the PV panel compared to the traditional MPPT and verified the theoretical background.

To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems.

The electrical energy produced by photovoltaic (PV) process is inexhaustible, developable everywhere and clean. Whatever the conditions, it is desirable to extract the biggest amount of power from the solar panel. This is achieved with the use of a Maximum Power Point Tracking (MPPT) algorithm. Fluctuations in weather conditions (irradiation and temperature) strongly degrade the performance of the photovoltaic module's energy conversion and therefore all the power cannot be transferred to the load. The objective is to study and compare different approaches of MPPT algorithms to evaluate the power extracted under the standard test conditions and varying weather conditions. Results of the performance with all these algorithms are compared under different operating conditions. The results show that the Fuzzy Logic Controller (FLC) is the fastest in terms of stabilization and is followed respectively by Fractional Short-Circuit Current (FSCC), Fractional Open-Circuit Voltage (FOCV), Perturb and Observe (P&O), Incremental Conductance (INC) and Hill Climbing (HC) algorithms. The FLC also gives the best results in extracting, followed by P&O INC, HC, FSCC and FOCV algorithms.