P. Sirisuk

Bio: P. Sirisuk is an academic researcher from Mahanakorn University of Technology. The author has contributed to research in topics: Antenna (radio) & Maximum power point tracking. The author has an hindex of 8, co-authored 37 publications receiving 419 citations.

FPGA Implementation of MPPT Using Variable Step-Size P&O Algorithm for PV Applications

Abstract: This paper describes FPGA implementation of a Maximum Power Point Tracking (MPPT) for Photovoltaic (PV) applications. By slightly modifying the original algorithm, an improved variable step-size P&O algorithm is realized and efficiently implemented using a hard-ware description language (VHDL). Subsequently, the new MPPT algorithm integrated with a solar-powered battery charging system is implemented on the XC2C384 FPGA without external sensor unit requirement. Experimental results with a commercial PV array show that the proposed algorithm outperforms the conventional controller in terms of tracking speed and mitigation of fluctuation output power in steady state operation. The overall system efficiency is well above 96%.

RISC-microcontroller built-in fuzzy logic controller of maximum power point tracking for solar-powered light-flasher applications

Abstract: This paper presents the development of maximum power point tracking (MPPT) using a fuzzy logic controller (FLC). By applying the synthetic fuzzy inference algorithm, the relationship between input and output of FLC can be effectively stored in a memory-limited lookup table (LUT). As a consequence, the controller can be efficiently implemented on a low-cost 16F872 RISC microcontroller. A practical system found in a transportation industry, particularly a solar-powered light-flasher (SPLF) with built in MPPT using FLC, is developed. Simulations with practical parameters show that our proposed MPPT using FLC implemented by LUT outperforms the conventional MPPT controller in terms of tracking speed. Furthermore, experimental results are shown to demonstrate the superiority of the proposed technique.

A novel fuzzy logic control technique tuned by particle swarm optimization for maximum power point tracking for a photovoltaic system using a current-mode boost converter with bifurcation control

Abstract: This paper presents a novel fuzzy logic control technique tuned by particle swarm optimization (PSO-FLC) for maximum power point tracking (MPPT) for a photovoltaic (PV) system. The proposed PV system composes of a current-mode boost converter (CMBC) with bifurcation control. An optimal slope compensation technique is used in the CMBC to keep the system adequately remote from the first bifurcation point in spite of nonlinear characteristics and instabilities of this converter. The proposed PSO technique allows easy and more accurate tuning of FLC compared with the trial-and-error based tuning. Consequently, the proposed PSO-FLC method provides faster tracking of maximum power point (MPP) under varying light intensities and temperature conditions. The proposed MPPT technique is simple and particularly suitable for PV system equipped with CMBC. Experimental results are shown to confirm superiority of the proposed technique comparing with the conventional PVVC technique and the trial-and-error based tuning FLC.

Grid-connected Photovoltaic System with Maximum Power Point Tracking using Self-Organizing Fuzzy Logic Controller

Abstract: This paper presents the design of a controller for the maximum power point tracking of a grid-connected photovoltaic energy conversion system A boost converter is used in the system to deliver the output from the solar array to DC-AC inverter, and feed the power into the AC grid A self-organizing fuzzy logic controller is introduced for the tracking algorithm The duty ratio for the operation of the boost converter is optimally adjusted in such a way that the maximum power point, which normally varies according to the environment, can be achieved We demonstrate via the simulation results that our proposed technique outperforms over the conventional fuzzy logic controller in terms of tracking speed and transient response Furthermore, the algorithm implementation can be done using a look-up table, hence a high-performance, cost-effective real-time maximum power point tracking can be simply realized

A Solar-powered Battery Charger with Neural Network Maximum Power Point Tracking Implemented on a Low-Cost PIC-microcontroller

Abstract: This paper presents the development of a maximum power point tracking algorithm using an artificial neural network for a solar power system. By applying a three layers neural network and some simple activation functions, the maximum power point of a solar array can be efficiently tracked. The tracking algorithm integrated with a solar-powered battery charging system has been successfully implemented on a low-cost PIC16F876 RISC-microcontroller without external sensor unit requirement. The experimental results with a commercial solar array show that the proposed algorithm outperforms the conventional controller in terms of tracking speed and mitigation of fluctuation output power in steady state operation. The overall system efficiency is well above 90%.

Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques

Abstract: 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.

A Variable Step Size INC MPPT Method for PV Systems

Abstract: Maximum power point tracking (MPPT) techniques are employed in photovoltaic (PV) systems to make full utilization of PV array output power which depends on solar irradiation and ambient temperature. Among all the MPPT strategies, the incremental conductance (INC) algorithm is widely used due to the high tracking accuracy at steady state and good adaptability to the rapidly changing atmospheric conditions. In this paper, a modified variable step size INC MPPT algorithm is proposed, which automatically adjusts the step size to track the PV array maximum power point. Compared with the conventional fixed step size method, the proposed approach can effectively improve the MPPT speed and accuracy simultaneously. Furthermore, it is simple and can be easily implemented in digital signal processors. A theoretical analysis and the design principle of the proposed method are provided and its feasibility is also verified by simulation and experimental results.

A Novel Improved Variable Step-Size Incremental-Resistance MPPT Method for PV Systems

Abstract: Maximum power point (MPP) tracking (MPPT) techniques are widely applied in photovoltaic (PV) systems to make PV array generate peak power which depends on solar irradiation. Among all the MPPT strategies, the incremental-conductance (INC) algorithm is widely employed due to easy implementation and high tracking accuracy. In this paper, a novel variable step-size incremental-resistance MPPT algorithm is introduced, which not only has the merits of INC but also automatically adjusts the step size to track the PV array MPP. Compared with the variable step-size INC method, the proposed scheme can greatly improve the MPPT response speed and accuracy at steady state simultaneously. Moreover, it is more suitable for practical operating conditions due to a wider operating range. This paper provides the theoretical analysis and the design principle of the proposed MPPT strategy. Simulation and experimental results verify its feasibility.

A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition

Abstract: This paper presents a review on the state-of-the-art maximum power point tracking (MPPT) techniques for PV power system applications. The main techniques that will be deliberated are the Perturb and Observe, Incremental Conductance and Hill Climbing. The coverage will also encompass their variations and adaptive forms. In addition, the more recent MPPT approaches using soft computing methods such as Fuzzy Logic Control, Artificial Neural Network and Evolutionary Algorithms are included. Whilst the paper provides as thorough treatment of MPPT at normal (uniform) insolation, its focus will be on the applications of the abovementioned techniques during partial shading conditions. It is envisaged that this review work will be a source of valuable information for PV professionals to keep abreast with the latest progress in this area, as well as for new researchers to get started on MPPT.

MPPT techniques for photovoltaic applications

Abstract: 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.