Optimization of a Solar Water Pumping System in Varying Weather Conditions by a New Hybrid Method Based on Fuzzy Logic and Incremental Conductance

Abstract

The present work consists of developing a new hybrid FL-INC optimization algorithm for the solar water pumping system (SWPS) through a SEPIC converter whose objective is to improve these performances. This technique is based on the combination of the fuzzy logic of artificial intelligence and the incremental conductance (INC) technique. Indeed, the introduction of fuzzy logic to the INC algorithm allows the extraction of a maximum amount of power and an improvement in the efficiency of the SWPS. The performance of the system through the SEPIC converter is compared with those of the direct coupling to show the interest of the indirect coupling, which requires an adaptation stage driven by an optimal control algorithm. In addition, a comparative analysis between the proposed hybrid algorithm and the conventional optimization techniques, namely, P&O and INC Modified (M-INC), was carried out to confirm improvements related to the SWPS in terms of efficiency, tracking speed, power quality, tracking of the maximum power point under different weather changes, and pumped water flow.

Analysis of the Use of a Low-Power Photovoltaic System to Power a Water Pumping Station in a Tourist Town

“…Only then should the guarantee of energy supplies from RES be taken care of. The results and conclusions we obtain can be used to further research on and the optimization of the processes of selecting the optimal pump size, pump operation schedules, or pump operation control similar to research carried out on larger facilities with a different work structure [26,30,31], as well as the modernization of water distribution systems: the renovation of pipes or cooperation of the pumping station with the reservoir. The obtained results relate to a PV installation with a permanent structure facing south.…”

“…A distributed WPS equipped with photovoltaic systems intergraded with a solar tracking system yields better performance and is more advantageous compared with a non-tracking system [29]. Tracking can be optimized using a new hybrid FL-INC optimization algorithm for the solar water pumping system [30]. The use of Artificial Neural Networks (ANNs) mathematical modeling has allowed to us predict the power generated in the photovoltaic installation for up to 3 h of pumping water in agriculture [31].…”

Enhancing Performance of Photovoltaic Pump Systems in Remote Areas Using a Sliding Mode Technique for Maximum Power Point Tracking

“…The speed of the reference frame. techniques such as optimization algorithms [22,23], fuzzy logic systems [24], and artificial neural networks [25,26] have been previously introduced to design peak power point tracking controllers. Nonlinear control systems were also used such as backstepping [27] and sliding mode, typically used for controlling power electronic converters, which represent instances of variable structure systems.…”

Power consumption control of multi-pump systems of the main water drainage in underground mines based on the Mamdani fuzzy inference system

“…Moreover, in problems when an object has several input variables, it is advisable to apply a fuzzy logic inference due to simplified synthesis and control algorithms implemented. On its basis, there are developed irrigation control systems [15,16], pumping facilities powered from autonomous power plants using renewable energy sources [17][18][19][20][21][22], control systems of wind turbines electromechanical equipment [23], urban water supply [24], cascades of multi-pump systems [25], as well as the electric drive of a separate pumping unit [26].…”