Maximizing Output Power of a Solar Panel via Combination of Sun Tracking and Maximum Power Point Tracking by Fuzzy Controllers

Abstract

In applications with low-energy conversion efficiency, maximizing the output power improves the efficiency. The maximum output power of a solar panel depends on the environmental conditions and load profile. In this paper, a method based on simultaneous use of two fuzzy controllers is developed in order to maximize the generated output power of a solar panel in a photovoltaic system: fuzzy-based sun tracking and maximum power point tracking. The sun tracking is performed by changing the solar panel orientation in horizontal and vertical directions by two DC motors properly designed. A DC-DC converter is employed to track the solar panel maximum power point. In addition, the proposed system has the capability of the extraction of solar panelI-Vcurves. Experimental results present that the proposed fuzzy techniques result in increasing of power delivery from the solar panel, causing a reduction in size, weight, and cost of solar panels in photovoltaic systems.

Tracking strategy for photovoltaic solar systems in high latitudes

“…The direction of the sun is identified according to the feedback from error signals measured by sensors, and then the solar panel is turned toward the sun. Taherbaneh et al [9] developed a method based on the simultaneous use of two fuzzy controllers to maximize the generated output power while Roth et al [10] constructed and tested a tracker that uses the signal of a sun-detecting linear sensor to control the pointing, and Chin et al [11] proposed both a MATLAB/Simulink model and compact solar tracker, which ''operates at different modes to provide flexibility to accommodate different weather conditions and preferences for different users''.…”

A Photovoltaic Power System Using a High Step-up Converter for DC Load Applications

“…Therefore, I LK11 (1) can be determined as: (14) where L m11 is the magnetizing inductor of primary winding of coupled inductor and L m12 is its secondary winding inductor. According to Equation (14), I LK11 (1) can be rewritten by: (15) Moreover, I LK11 (2) can be given by: (16) Since current I D1 (1) is equal to I LK11 (2) and average current I D1(av) equals half of output current I O , the average current I D1(av) can be expressed as follows : (17) According to Equation (17), the boundary inductance L m11B can be determined as: (18) Based on the magnetic principle of coupled inductor, the relationship between inductances L m11B and L m12B can be expressed as follows:…”

“…Several MPPT algorithms have been proposed [11][12][13][14][15][16][17][18][19][20]. Some of the more popular MPPT algorithms are the constant voltage method [11,12], β method [13], system oscillation method [14,15], ripple correlation method [16], incremental conductance method [17] and perturb and observe method [18][19][20].…”

Solar Energy Measurement Using Arduino

“…This paper presented by Mohsen Taherbaneh et. al [5] proposed the method based on simulation of two fuzzy controllers in order to maximize the generate the output power of solar panel in a photovoltaic system. The output I-V curve from this project are the maximum current is 1.56A nad the maximum voltage are 20V with solar irradiance = 500W/m 2 and temperature = 34.5°C.…”