Cakar ayam shaping machine

Cakar ayam (Figure 7.1) is one of the Malay traditional cookies that are made from sliced sweet potatoes deep-fried in the coconut candy. In current practice of moulding the cookies, the fried sweet potatoes are molded using traditional manual tools, which are inefficient and less productive for the mass production purposes. “Kuih cakar ayam” associated with the meaning of the idiom means less messy handwriting has a somewhat negative connotation .This cookies may just seem less attractive in shape but still likeable . In fact, this cookie is considered a popular snack even outside the holiday season. The choice of the name of this cookie is more to shape actually resembles former chicken scratches made by the paw the ground while foraging. The value of wisdom, beauty and creativity of the Malays is clearly evident through the Malay cookie. Although it is attacked by the invention of modern cakes that look far more interesting, these cakes will be able to survive a long time until now

Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro- Fuzzy "ANFIS"

International audienceDue to scarcity of fossil fuel and increasing demand of power supply, we are forced to utilize the renewable energy resources. Considering easy availability and vast potential, world has turned to solar photovoltaic energy to meet out its ever increasing energy demand. The mathematical modeling and simulation of the photovoltaic system is implemented in the MAT LAB/Simulink environment and the same thing is tested and validated using Artificial Intelligent (Al) Iike AN FIS. This paper presents Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro- Fuzzy "ANFIS". The PV array has an optimum operating point to generate maximum power at some particular point called maximum power point (MPP). To track this maximum power point and to draw maximum power from PV arrays, MPPT controller is required in a stand-alone PV system. Due to the nonlinearity in the output characteristics of PV array, it is very much essential to track the MPPT of the PV array for varying maximum power point due to the insolation variation. In order to track the MPPT conventional controller like Adaptive Neuro-Fuzzy "ANFIS" and fuzzy logic controller is proposed and simulated. The output of the controller, pulse generated from PWM can switch MOSFET to change the duty cycle of boost DC-DC converter. The result reveals that the maximum power point is tracked satisfactorily for varying insolation condition

Simulation and Implementation of a Modified ANFIS MPPT Technique

The maximum power point tracking (MPPT) algorithms ensure optimal operation of a photovoltaic (PV) system to extract the maximum PV power, regardless of the climatic conditions. This paper exposes the study, design, simulation and implementation of a modified advanced neural fuzzy inference system (ANFIS) MPPT algorithm based on fuzzy data for a PV system. The studied system includes a PV array, a DC/DC buck converter, the ANFIS controller, a proportional-integral (PI) controller, and a load. The simulation and experimental tests are carried out with the MATLAB/Simulink software and LabVIEW, respectively. Moreover, the obtained results are compared with previously published results by incremental conductance (IC) and fuzzy logic (FL) algorithms under different climatic conditions of irradiation and temperature. The results show that the proposed ANFIS algorithm is able to track the maximum power point for varying climatic conditions. Furthermore, the comparison analysis reveals that the PV system using ANFIS algorithm has more efficient and better dynamic response than FL and IC

Global maximum power tracking of PV system under partial shading

The increased usage of electrical energy in the recent times leads to a greater demand. It invites large development in the production of electrical energy from renewable energy sources. It involves more evolving technologies. Out of all energy extraction from solar would be abundant. Photovoltaic (PV) are one such components helps in deriving large amounts of energy, this has become more easiest method due to its economic liabilities and the world has aimed its interest in developing the PV technology, which gives clean energy. This paper objective is to implement various Maximum Power Point Tracking (MPPT) algorithms, mainly Cuckoo Search Algorithm, fuzzy logic control (FLC) and conventional perturb and observe (P&O), incremental conductance (INC) on solar PV systems. These controlled MPPT algorithms helps in driving DC-DC boost converter, which helps to obtain maximum output from the PV Panels/cells/modules/Arrays. The obtained results are compared with each other under several operating conditions. The operating conditions include change in irradiance, change in temperature dynamically, and partial shading on PV panels. The implemented MPPT algorithms require only the PV array voltage and current to control DC-DC converter, which makes them economically feasible and attractive. From the results, it can be observed that Cuckoo search algorithm gives better results under partial shading situations

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on

A Review on Favourable Maximum Power Point Tracking Systems in Solar Energy Application

This paper reviews different types of maximum power point tracking (MPPT) techniques for solar photovoltaic (PV) application. Since the PV output power is known affected by sun radiation and temperature, it is necessary to search for an effective method for extracting maximum amount of power from PV cell/modules. In this study, a total of seven control algorithms were selected, comprising the most popular methods among the established techniques. A comparison in terms of convergence speed, complexity, as well as the basic concept of each method had been carried out for future reference. Based on the accessible simulation results, modified Perturb and Observe (P&O) method had shown its effectiveness for obtaining actual maximum power point while solving major drawbacks of the conventional P&O. This paper also discusses typical solar MPPT system, including the pros and cons of each part of the system

Fuzzy Intelligent Controller for the Maximum Power Point Tracking of a Photovoltaic Module at Varying Atmospheric Conditions

This paper presents the modeling of a photovoltaic (PV) module at varying atmospheric conditions such as irradiation and temperature. It also includes the maximum power point tracking (MPPT) of the PV module using conventional perturb and observe (P&O) method and fuzzy logic controller. For the performance analysis, the simulation of the PV module along with MPPT controller is done by using MATLAB/Simulink software. The voltage, current and power transitions at varying irradiation and temperature conditions is observed using conventional P&O and fuzzy logic based MPPT controllers. Finally the percentage improvement in power tracking time by fuzzy logic controller against the P&O controller has been evaluated Keywords: Photovoltaic Module, MPPT, P&O method, Fuzzy logic Controller, Irradiatio

A Review on Photo Voltaic MPPT Algorithms

A photovoltaic generator exhibits nonlinear voltage-current characteristics and its maximum power point varies with solar radiation and cell temperature. A Dc/Dc power converter is used to match the photovoltaic system to the load and to operate the PV (photo voltaic) cell array at maximum power point. Maximum Power Point Tracking (MPPT) is a process which tracks one maximum power point from PV array input, varying the ratio between the voltage and current delivered to get the most power it can. There are different techniques proposed with lot of algorithms are being used in the MPPT controller to extract the maximum power. It is very difficult for the photo voltaic designers, researchers and academic experts to select a particular MPPT technique for a particular application which requires the background knowledge and comparative features of various MPPT algorithms. This paper will be avaluable source for those who work in the photo voltaic generation, so its objective is to review the main MPPT algorithms in practice and analyzes the merits and demerits with various factors

Photovoltaic Emulation System and Maximum Power Point Tracking Algorithm Under Partial Shading Conditions

In this thesis, a novel photovoltaic (PV) emulator and the state-of-art learning–based real-time hybrid maximum power point tracking (MPPT) algorithms have been presented. Real-time research on PV systems is a challenging task because it requires a precise PV emulator that can faithfully reproduce the nonlinear properties of a PV array. The prime objective of the constructed emulator based on integration of unilluminated solar panels with external current sources is to overcome the constraints such as the need for wide surrounding space, high installation cost, and lack of control over the environmental conditions. In addition, the proposed PV emulator is able to simulate the electrical characteristics of the PV system under uniform irradiation as well as partially shading conditions (PSC). Moreover, the application of MPPT technology in PV systems under PSC conditions is challenging. Under complex environmental conditions, the power-voltage (P-V) characteristic curve of a PV system is likely to contain both local global maximum power points (LMPPs) and global maximum power points (GMPP). The MPPT algorithm applied to a PV system should have minimal steady-state oscillations to reduce power losses while accurately searching for the GMPP. The proposed MPPT algorithms resolved the drawbacks of the conventional MPPT method that have poor transient response, high continuous steady-state oscillation, and inefficient tracking performance of maximum power point voltage in the presence of partial shading. The intended algorithms have been verified using MATLAB/Simulink and the proposed PV emulator by applying comparative analysis with the traditional MPPT algorithms. In addition, the performance of the proposed MPPT algorithms and control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-Time-Interface (RTI) 1007 processor board and DS2004 A/D and CP4002 Digital I/O boards. The results indicate that the algorithm is effective in reducing power losses and faster in tracking the speed of the maximum power point with less oscillation under partial shading conditions. In addition, excellent dynamic characteristics of the proposed emulator have been proven to be an ideal tool for testing PV inverters and various maximum power point tracking (MPPT) algorithms for commercial applications and university studies

Optimization of fuzzy photovoltaic maximum power point tracking controller using chimp algorithm

In this paper, a photovoltaic (PV) fuzzy maximum power point tracking (MPPT) method optimized by the chimp algorithm is presented. The fuzzy logic controller (FLC) of seven triangular membership functions (MFs) is used. The optimization fitness function is composed of transient and steady-state indices under different irradiation and temperature operating conditions. By using MATLAB package, the performance of optimized method is examined and compared with asymmetrical FLC and well-known perturb and observe (P&O) tracking methods at different operating conditions in terms of: transient rising time (tr) and energy yield during 30 s. Moreover, the tracking methods are also compared in terms of the fitness function value. From the comparison of simulation results, a more energy can be harvested by using the proposed optimized tracking method compared to the other methods. Consequently, at the various operating conditions, the proposed method can be used as a more reliable tracking method for PV systems