Wind power is the most reliable and developed renewable energy source over past decades. With the rapid penetration of the wind generators in the power system grid, it is very essential to utilize the maximum available power from the wind and to operate the wind turbine (WT) at its maximal energy conversion output. For this, the wind energy conversion system (WECS) has to track or operate at the maximum power point (MPP). A decent variety of publication report on various maximum power point tracking (MPPT) algorithms for a WECS. However, making a choice on an exact MPPT algorithm for a particular case require sufficient proficiency because each algorithm has its own merits and demerits. For this reason, an appropriate review of those algorithms is essential. However, only a few attempts have been made in this concern. In this paper, different available MPPT algorithms are described for extracting maximum power which are classified according to the power measurement i.e. direct or indirect power controller. Merits, demerits and comprehensive comparison of the different MPPT algorithms also highlighted in the terms of complexity, wind speed requirement, prior training, speed responses, etc. and also the ability to acquire the maximal energy output. This paper serves as a proper reference for future MPPT users in selecting appropriate MPPT algorithm for their requirement.

A review of conventional and advanced MPPT algorithms for wind energy systems

Maximum power point tracking for photovoltaic using incremental conductance method

This paper discusses maximum power point tracking (MPPT) methods of PV system for normal and partial shading conditions (PSC). The selected MPPT methods were classified as artificial intelligent, hybrid, and other MPPT methods. The comparison of researches on MPPT methods under normal condition and PSC reveals that researchers have concentrated more on shading conditions since the last few years mainly due to the need of power output and efficiency improvements. It is believed that the information contained in this piece of work will be of great use for the researchers in the field under consideration.

A review on maximum power point tracking for photovoltaic systems with and without shading conditions

Solar energy, at the present time is considered as an important source in electricity generation. Electricity from the solar energy can be generated using solar photovoltaic (PV) modules. The maximization of solar power extracted from a PV module is of special concern as its efficiency is very low. The output power of a PV module is highly dependent on the geographical location and weather conditions such as solar irradiation, shading and temperature. To obtain maximum power from PV module, photovoltaic power system usually requires maximum power point tracking (MPPT) controller. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) based maximum power point tracker for PV module has been presented. To extract maximum power, a DC–DC boost converter is connected between the PV module and the load. The duty cycle of DC–DC boost converter is modified with the help of the ANFIS reference model, so that maximum power is transferred to load. Due to the complexity of the tracker mechanism and non-linear nature of photovoltaic system, the artificial intelligence based technique, especially the ANFIS method, is used in this paper. In order to observe the maximum available power of PV module, the ANFIS reference model directly takes in operating temperature and irradiance level as input. The response of proposed ANFIS based control system shows accuracy and fast response. The simulation result reveals that the maximum power point is tracked satisfactorily for varying irradiance and temperature of PV module. Simulation results are provided to validate the concept.

Modeling of solar PV module and maximum power point tracking using ANFIS

https://cyberleninka.org/article/n/940175.pdf

Advanced Fuzzy MPPT Controller for a Stand-alone PV System☆

https://cyberleninka.org/article/n/1147441.pdf

MPPT with Inc.Cond method using conventional interleaved boost converter

This paper presents an improved particle swarm optimization (PSO) based maximum power point tracking (MPPT) strategy. Modeling of the PV cell and effect of the partially shaded condition (PSC) on the P_V characteristics are investigated. Typical PSO algorithm is modified to provide a better convergence and faster performance. A novel strategy is also proposed for reinitialization to reduce tracking time and power fluctuations in case of cloudy sky. The performance of the proposed system under uniform insolation, PSC and rapid fluctuation of the insolation is evaluated by MATLAB 2010B.

S. Mohsen Mirhassani

Papers

MPPT with Inc.Cond method using conventional interleaved boost converter

An improved PSO based MPPT approach to cope with partially shaded condition