Cuckoo search–based maximum power point tracking controller for PV water pumping system

Abstract

In this paper, a novel-based tracking controller is developed to ensure maximum power point operation for photovoltaic (PV) water pumping systems (PVWPS). PVWPS consists of a PV array followed by a controlled DC cuk converter which feeds a permanent magnet DC motor coupled with a centrifugal pump. The proposed controller is adaptive-logic based that search, detect and track by using Cuckoo Search (CS) technique. This controller may be specified by three control algorithms, each one has its own constraints for Maximum Power Point tracking achievement. The first two CS control algorithms are based on the sensed old chopping ratio, insolation and temperature as inputs in addition to the PV and motor–pump performance parameters. These controllers are implemented to predict the operating and maximum point voltage and power. The third CS control algorithm is constrained by the outputs of the first two CS control algorithms and motor–pump performance parameters. The third CS controllers are implemented also to predict the optimum DC–DC converter duty ratio based on solar insolation, ambient temperature and motor–pump constants. Each algorithm is provided by its own proposed control function. The new approach has proven accuracy, robustness and effectiveness of efficient energy utilization for stand-alone PVWPS one as it is the most accurate, fastest and easiest.

Improving power quality and load profile using PV‐Battery‐SAPF system with metaheuristic tuning and its HIL validation

“…CSA was used to compute the optimum firing angle of the boost converter and it was concluded that it is more robust, has a variable step size, and yields faster convergence and high efficiency. 16,17 This is due to Lévy flight, as larger steps at times require less iteration. The performance in CSA does not depend on the initial samples and their positions unlike particle swarm optimization (PSO).…”

“…χ k i ⊆χ i = set of node in the neighbor of i that K has not visited "yet". After ants have completed the tour, pheromone evaporation of arcs is triggered and then each ant K deposits a quantity of pheromone Δτ k ij t ð Þ on each arc it has used as equation (17).…”

“…The metaheuristic approaches like cuckoo search algorithm (CSA) is advantageous when considering fast design process as it requires lesser tuning parameters. CSA was used to compute the optimum firing angle of the boost converter and it was concluded that it is more robust, has a variable step size, and yields faster convergence and high efficiency . This is due to Lévy flight, as larger steps at times require less iteration.…”

An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions

“…Another study was undertaken in 2017 [11] to improve the performance of the CS-to have fast convergence at initialization and lower oscillations at steady-state conditions. They used the standard CS [6], which creates high oscillations at steady-state conditions.…”

FPGA Implementation of Floating Point Based Cuckoo Search Algorithm

“…The applications of the CSA are diverse and can be applied in problem solving and design optimization [1], [11]. For example, the maximum power tracking of photovoltaic systems using CSA is investigated in [12], [13]. The results have shown that the CSA surpasses other optimization techniques such as perturb and observe (P&O) and particle swarm optimization (PSO).…”