A Study on the Fuzzy-Logic-Based Solar Power MPPT Algorithms Using Different Fuzzy Input Variables

[[abstract]]Maximum power point tracking (MPPT) is one of the key functions of the solar power management system in solar energy deployment. This paper investigates the design of fuzzy-logic-based solar power MPPT algorithms using different fuzzy input variables. Six fuzzy MPPT algorithms, based on different input variables, were considered in this study, namely (i) slope (of solar power-versus-solar voltage) and changes of the slope; (ii) slope and variation of the power; (iii) variation of power and variation of voltage; (iv) variation of power and variation of current; (v) sum of conductance and increment of the conductance; and (vi) sum of angles of arctangent of the conductance and arctangent of increment of the conductance. Algorithms (i)–(iv) have two input variables each while algorithms (v) and (vi) use a single input variable. The fuzzy logic MPPT function is deployed using a buck-boost power converter. This paper presents the details of the determinations, considerations of the fuzzy rules, as well as advantages and disadvantages of each MPPT algorithm based upon photovoltaic (PV) cell properties. The range of the input variable of Algorithm (vi) is finite and the maximum power point condition is well defined in steady condition and, therefore, it can be used for multipurpose controller design. Computer simulations are conducted to verify the design.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]CH

A SIMSCAPE based design of a dual maximum power point tracker of a stand-alone photovoltaic system

This paper presents the simulation of a dual maximum power point tracker (dual-MPPT) and attempt to get the global maximum power point GMPP under partial shading conditions for a solar photovoltaic module using MATLAB SIMSCAPE. Traditional single MPP trackers are less efficient than dual MPP trackers and have greater sensitivity to partial shading. By using dual MPP trackers, one can get several features such as the possibility of connecting two arrays with different string sizes or different solar azimuths or tilts within high efficiency. This paper focuses on making the photovoltaic system work at maximum possible power under partial shading condition by using dual MPP trackers to achieve the convergence toward the global maximum power point GMPP

Fuzzy Logic Based MPPT for Grid Connected PV Systems

The ever growing demand of power for socio-economic development, the conventional energysources have almost become obsolete for nurturing this demand, thus opening new avenues toharness power from the non-conventional sources effectively and efficiently. Photovoltaic isone of the prospective solutions for this crisis. But, the efficiency is dependent oncontinuously varying various factors such as irradiance, cell temperature, dust, sunlight'sspectral density. Photovoltaic is a non-conventional and environment friendly techniquewhich has various challenges to overcome. Since the cost of installation systems is more,tapping maximum energy from an installed system is a technical and economical challenge

Optimizing of the installed capacity of hybrid renewable energy with a modified MPPT model

The lack of wind speed capacity and the emission of photons from sunlight are the problem in a hybrid system of photovoltaic (PV) panels and wind turbines. To overcome this shortcoming, the incremental conductance (IC) algorithm is applied that could control the converter work cycle and the switching of the buck boost therefore maximum efficiency of maximum power point tracking (MPPT) is reached. The operation of the PV-wind hybrid system, consisting of a 100 W PV array device and a 400 W wind subsystem, 12 V/100 Ah battery energy storage and LED, the PV-wind system requires a hybrid controller for battery charging and usage and load lamp and it’s conducted in experimental setup. The experimental has shown that an average increase in power generated was 38.8% compared to a single system of PV panels or a single wind turbine sub-system. Therefore, the potential opportunities for increasing power production in the tropics wheather could be carried out and applied with this model

Implementasi Maximum Power Point Tracking pada Photovoltaic Berbasis P&O-Fuzzy

Maximum Power Point Tracking (MPPT) technology is an alternative solution to improve efficiency of solar cells (photovoltaic). The main part of MPPT technology is DC-DC converter circuit and control algorithm. This paper proposes a control algorithm Perturbation and Observe (P&O)-Fuzzy on MPPT, which can improve the efficiency of solar cells, and simultaneously comparing the control algorithms P&O and P&O-Fuzzy. Synchronous buck converter is used to reduce the voltage of solar cells. The buck converter is controlled using P&O and P&O-Fuzzy algorithms. These algorithms use two inputs; change of power and change of voltage, produced by the solar cell. MPPT technology has been tested using solar cells with a capacity of 50 Watt as a source of electrical energy, battery 12V/45aH as energy storage, and resistor as load. The test results indicate that the P&O algorithm has an efficiency of 86% with rise time (tr) and steady state time (ts) at 0.45 seconds, while the P&O-Fuzzy algorithm has an efficiency of 89% with rise time (tr) and steady state time (ts) at 0.3 seconds

Hybrid Improved Differential Evolution and Splinebased Jaya for Photovoltaic MPPT Technique

Some Soft Computing algorithms to solve themaximum power point tracking (MPPT) method problem ofthe photovoltaic system under partially shaded conditions willstop tracking Global Maxima and produce reference voltage orthe best duty-cycle if the difference between the worst and thebest candidate solution is smaller than the specified threshold.A large threshold value will produce fast converging, but theaccuracy value will be low, and vice versa, then thedetermination of the threshold value will be very dilemma.Therefore, this study proposed a combination of ImprovedDifferential Evolution (IDE) and Jaya optimization based onpredictive curves using cubic spline interpolation to determinethe best particles after the IDE reaches convergent criteria, sothat with a large threshold value it will still get high accuracyand high convergent speed. Furthermore, the algorithmproposed in this study is known as Improved DifferentialEvolution and Jaya Based Spline (IDESJaya). The proposedalgorithm is compared with conventional P&O, Jaya based onSpline, and IDE. Simulation results show that the IDESJayatechnique is faster converging, provides a better overalltracking efficiency and higher accuracy

A Modified Maximum Power Point Tracking with Constant Power Generation Using Adaptive Neuro-Fuzzy Inference System Algorithm

Renewable energy is being used to lessen the consumption of fossil fuels. Solar energy is a common source of renewable energy. Solar energy is the most promising source of energy due to its long-term sustainability and availability. The output power of solar panels is strongly influenced by the intensity of sunlight and the temperature of the solar panels. Maximum Power Point Tracking (MPPT) control, which aims to optimize the output power of solar panels, is commonly used to increase the efficiency of solar panels. However, MPPT control often causes overvoltage disturbance in systems directly connected to the load. To limit the output power of solar panels, additional Constant Power Generation (CPG) control is required. In this research, a solar panel system will be created to supply submersible DC pumps without any energy storage devices. DC-DC SEPIC Converter is designed with MPPT control combined with CPG control to limit the output power of the converter using the Adaptive Neuro-Fuzzy Inference System method by 150 watts. When the output power of the solar panel is less than the power limit, then MPPT mode will work. While CPG mode works when the PV output power is greater than the limit power. The results of this research showed that the system can provide optimal power generated by solar panels in MPPT mode by increasing efficiency by up to 33.04% and CPG mode can limit power to 150 Watts to avoid overvoltage disturbance at load

Analysis between Perturb & Observe Controller and Fuzzy Logic Controller for a Photovoltaic System with CUK and SEPIC Converter

The power generation is using Photovoltaic (PV) cell is the best alternative developing for fossil fuel since it renewable green power, energy conservation and demand-side management. Solar energy most useful for sustainable development but due to it has a nonlinear current-voltage characteristic. It is difficult to track the maximum power produce by the PV module. This paper presents a comparison between the Single-Ended Primary-Inductor Converter (SEPIC) and CUK converter by using both Fuzzy Logic Controller (FLC) and Perturb & Observe (P&O) methods in maximum power point tracking (MPPT). In this paper, the performance, advantage and disadvantage for both converters and MPPT algorithm are described. A general model of a Photovoltaic system with proposed MPPT controller and converters is implemented in MATLAB/Simulink software. The input parameter of temperature and irradiation level will be under constant and variable level as to prove the system efficiency towards changing conditions. The simulation result will be analyzed in different case studies in order to prove the effectiveness timely response performances, efficiencies of our power of converting over input power of the PV module and the comparison of transient response of voltage ripple of the systems

نمذجة ومحاكاة أنظمة الطاقة الهجينة لتلبية متطلبات الحمل الديناميكي

يعرض هذا البحث نمذجة ودراسة نظام طاقة هجين مؤلف من مجموعة خلايا كهروشمسية مع مجموعة عنفات ريحية تم وصلها مع شبكة الكهرباء العامة التي تعتمد على طاقة الوقود الأحفوري، وذلك لتخفيف الطلب على هذا الوقود  -الضار بالبيئة والذي ينضب مع الزمن- خاصة في الأوقات التي نكون فيها قادرين على استثمار الطاقات المتجددة في الأيام المشمسة والأيام التي يكون فيه هبوب الرياح مناسباً. بالإضافة إلى تلبية متطلبات الأحمال الديناميكية المتغيرة في كافة الأوقات وبشكل خاص في ساعات ذروة الطلب على الطاقة. أجريت عمليات النمذجة في بيئة Matlab/Simulink، حيث تم محاكاة عمل محطات التوليد الهجينة لمدة يوم كامل بما فيه من اختلاف بارامترات الطقس (الإشعاع الشمسي وسرعة الرياح) بين ساعات الليل والنهار واختلاف الطلب على الطاقة خلال ساعات هذا اليوم. أخيراً تم عرض ومناقشة النتائج، حيث بينت النتائج توفير في استهلاك الوقود الأحفوري بنسب متفاوتة اعتماداً على كمية الطاقة المستخلصة من الخلايا الشمسية والعنفات الريحية والتي تعتمد على شدة الاشعاع الشمسي وسرعة الرياح المناسبة والتي ظهرت بشكل واضح عند الساعة 12 ظهراً والذي يعتبر ذروة استهلاك الطاقة في .ساعات اليوم. الأمر الذي يؤدي إلى لعب دور اقتصادي كبير في مجال الطاقة