Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System

Abstract

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on the Canis latrans species, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler–Nichols and trial–error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities.

Enhanced Intelligent Closed Loop Direct Torque and Flux Control of Induction Motor for Standalone Photovoltaic Water Pumping System

“…Large numbers of techniques have been proposed to maintain the DC bus voltage at its reference. A PI controller was proposed by [41]. It consisted in converting the voltage error into speed.…”

An Efficient and Robust Current Control for Polymer Electrolyte Membrane Fuel Cell Power System

“…Hence, the controller uses the reference and the feedback, which is a measurement acquired by a sensor, to generate the control signal. The overall control function u of the PI controller is given in Equation ( 10) [36][37][38]; where e r is the error between the PEMFC current i L and the reference current i re f (expressed in Equation ( 9)). K p and K i represents, respectively, the proportional and the integral coefficients.…”

A Novel Method Based on Improved Coyote Optimization Algorithm for Searching the Best Tour for the Travelling Salesman Problem

“…Moreover, the information exchange among groups also helps COA to avoid trapping to local optimal. The application of COA has been carried out for many problems such as electric network operation optimization [25], control water-pumping system [26] and photovoltaic model parameters extraction [27], etc. However, the efficiency of COA for different problems such as the TSP problem is also a question that needs to be clarified.…”