Improved Output Characteristic of Distributed Hybrid Solar–Wind Generating Materials by Using Fuzzy and Immune MPPT Control Method

2011 ◽  
Vol 321 ◽  
pp. 76-79
Author(s):  
Li Qun Liu ◽  
Chun Xia Liu
Keyword(s):  
Solar Wind ◽  
Electric Power ◽  
Control Method ◽  
Response Speed ◽  
Climatic Conditions ◽  
Output Characteristic ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Power Point ◽  
Response Feedback

The price of photovoltaic (PV) materials and wind generating system (WGS) materials is costly, and the stand-alone PV or WGS can not steadily supplied electric power for end user, fortunately, solar power and wind power can compensate well for one another under various locations and climatic conditions, an efficient maximum power point tracking (MPPT) method for hybrid solar-wind electricity materials is important to extract maximum power from wind and solar energy because of the costly price of PV and WGS. The fuzzy MPPT method is used to track the maximum power point (MPP) of distributed small WGS and PV and hybrid solar-wind system. In order to decrease the output oscillation, the immune response feedback principle (IRFP) is used to improve the track speed and response speed and robust of output characteristic of electricity materials, the results displayed that the immune theory can effectively improve the performance and the stability of electric power of stand-alone or hybrid generating materials.

Optimal Command for Photovoltaic Systems in Real Outdoor Weather Conditions

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Hafsa Abouadane ◽  
Abderrahim Fakkar ◽  
Benyounes Oukarfi
Keyword(s):  
Maximum Power Point Tracking ◽  
Accurate Determination ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The photovoltaic panel is characterized by a unique point called the maximum power point (MPP) where the panel produces its maximum power. However, this point is highly influenced by the weather conditions and the fluctuation of load which drop the efficiency of the photovoltaic system. Therefore, the insertion of the maximum power point tracking (MPPT) is compulsory to track the maximum power of the panel. The approach adopted in this paper is based on combining the strengths of two maximum power point tracking techniques. As a result, an efficient maximum power point tracking method is obtained. It leads to an accurate determination of the MPP during different situations of climatic conditions and load. To validate the effectiveness of the proposed MPPT method, it has been simulated in matlab/simulink under different conditions.

scholarly journals Survey of Six Maximum Power Point Tracking Algorithms under Standard Test conditions

2021 ◽  
Vol 03 (01) ◽  
pp. 53-62
Author(s):  
Mohammed Salah Bouakkaz ◽  
◽  
Ahcene Boukadoum ◽  
Omar Boudebbouz ◽  
Issam Attoui ◽  
...  
Keyword(s):  
Short Circuit ◽  
Maximum Power Point Tracking ◽  
Open Circuit ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Hill Climbing ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In this work, a survey is carried out on six MPPT algorithms which include conventional and artificial intelligence based approaches. Maximum Power Point Tracking (MPPT) algorithms are used in PV systems to extract the maximum power in varying climatic conditions. The following most popular MPPT techniques are being reviewed and studied: Hill Climbing (HC), Perturb and Observe (P&O), Incremental Conductance (INC), Open-Circuit Voltage (OCV), Short Circuit Current (SCC), and Fuzzy Logic Control (FLC). The algorithms are evaluated, analyzed, and interpreted using a Matlab-Simulink environment to show the performance and limitations of each algorithm

scholarly journals Design of an Efficient Maximum Power Point Tracker Based on ANFIS Using an Experimental Photovoltaic System Data

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 858 ◽  
Author(s):  
Sadeq D. Al-Majidi ◽  
Maysam F. Abbod ◽  
Hamed S. Al-Raweshidy
Keyword(s):  
Fuzzy Inference ◽  
Experimental Tests ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Training Data ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Inference System ◽  
Photovoltaic Array ◽  
Power Point

Maximum power point tracking (MPPT) techniques are a fundamental part in photovoltaic system design for increasing the generated output power of a photovoltaic array. Whilst varying techniques have been proposed, the adaptive neural-fuzzy inference system (ANFIS) is the most powerful method for an MPPT because of its fast response and less oscillation. However, accurate training data are a big challenge for designing an efficient ANFIS-MPPT. In this paper, an ANFIS-MPPT method based on a large experimental training data is designed to avoid the system from experiencing a high training error. Those data are collected throughout the whole of 2018 from experimental tests of a photovoltaic array installed at Brunel University, London, United Kingdom. Normally, data from experimental tests include errors and therefore are analyzed using a curve fitting technique to optimize the tuning of ANFIS model. To evaluate the performance, the proposed ANFIS-MPPT method is simulated using a MATLAB/Simulink model for a photovoltaic system. A real measurement test of a semi-cloudy day is used to calculate the average efficiency of the proposed method under varying climatic conditions. The results reveal that the proposed method accurately tracks the optimized maximum power point whilst achieving efficiencies of more than 99.3%.

Study on Maximum Power Point Tracking for Grid-Connected Photovoltaic System

2010 ◽  
Vol 121-122 ◽  
pp. 93-96 ◽  
Author(s):  
Hou Sheng Zhang
Keyword(s):  
Control Method ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Variable Step Size ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Solar Radiation Intensity ◽  
Power Point

As the energy crisis and the pollution are serious, the exploitation of solar has received more and more attentions. It is well known that for a given solar radiation intensity and solar cell temperature there exists a maximum power point at which the power generated from the PV panel is at its maximum. In order to improve the efficiency of the system, the main method is to regulate the output of array to develop the maximum power point tracking (MPPT). In this paper the principle and control method of DC/DC conversion in grid-connected photovoltaic system are experimentally discussed. The conductance incremental method is analyzed in detail, and an improved variable step-size control method is implemented for MPPT with pulse width modulation. The experimental results prove the feasibility and correctness of the control method.

scholarly journals A Robust Maximum Power Point Tracking Control Method for a PEM Fuel Cell Power System

2018 ◽  
Vol 8 (12) ◽  
pp. 2449 ◽  
Author(s):  
Mohamed Derbeli ◽  
Oscar Barambones ◽  
Lassaad Sbita
Keyword(s):  
Proton Exchange Membrane ◽  
Control Method ◽  
Rapid Change ◽  
Proton Exchange ◽  
Operating Conditions ◽  
Maximum Power ◽  
Backstepping Technique ◽  
Maximum Power Point ◽  
Power Point ◽  
Efficient Power

Taking into account the limited capability of proton exchange membrane fuel cells (PEMFCs) to produce energy, it is mandatory to provide solutions, in which an efficient power produced by PEMFCs can be attained. The maximum power point tracker (MPPT) plays a considerable role in the performance improvement of the PEMFCs. Conventional MPPT algorithms showed good performances due to their simplicity and easy implementation. However, oscillations around the maximum power point and inefficiency in the case of rapid change in operating conditions are their main drawbacks. To this end, a new MPPT scheme based on a current reference estimator is presented. The main goal of this work is to keep the PEMFCs functioning at an efficient power point. This goal is achieved using the backstepping technique, which drives the DC–DC boost converter inserted between the PEMFC and the load. The stability of the proposed algorithm is demonstrated by means of Lyapunov analysis. To verify the ability of the proposed method, an extensive simulation test is executed in a Matlab–Simulink T M environment. Compared with the well-known proportional–integral (PI) controller, results indicate that the proposed backstepping technique offers rapid and adequate converging to the operating power point.

scholarly journals Kalman Filter-Based Online Identification of the Electric Power Characteristic of Solid Oxide Fuel Cells Aiming at Maximum Power Point Tracking

Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 58 ◽  
Author(s):  
Andreas Rauh ◽  
Wiebke Frenkel ◽  
Julia Kersten
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Electric Power ◽  
Maximum Power ◽  
Power Characteristic ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Stochastic Filter ◽  
Power Point

High-temperature fuel cells are one of the devices currently investigated for an integration into distributed power supply grids. Such distributed grids aim at the simultaneous production of thermal energy and electricity. To maximize the efficiency of fuel cell systems, it is reasonable to track the point of maximum electric power production and to operate the system in close vicinity to this point. However, variations of gas mass flows, especially the concentration of hydrogen contained in the anode gas, as well as variations of the internal temperature distribution in the fuel cell stack module lead to the fact that the maximum power point changes in dependence of the aforementioned phenomena. Therefore, this paper first proposes a real-time capable stochastic filter approach for the local identification of the electric power characteristic of the fuel cell. Second, based on this estimate, a maximum power point tracking procedure is derived. It is based on an iteration procedure under consideration of the estimation accuracy of the stochastic filter and adjusts the fuel cell’s electric current so that optimal operating points are guaranteed. Numerical simulations, based on real measured data gathered at a test rig available at the Chair of Mechatronics at the University of Rostock, Germany, conclude this paper.

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