The exploitation of solar energy in remote areas through photovoltaic (PV) systems is an attractive solution for water pumping for irrigation systems. The design of a photovoltaic water pumping system (PVWPS) strictly depends on the estimation of the crop water requirements and land use since the water demand varies during the watering season and the solar irradiation changes time by time. It is of significance to conduct dynamic simulations in order to achieve the successful and optimal design. The aim of this paper is to develop a dynamic modelling tool for the design of a of photovoltaic water pumping system by combining the models of the water demand, the solar PV power and the pumping system, which can be used to validate the design procedure in terms of matching between water demand and water supply. Both alternate current (AC) and direct current (DC) pumps and both fixed and two-axis tracking PV array were analyzed. The tool has been applied in a case study. Results show that it has the ability to do rapid design and optimization of PV water pumping system by reducing the power peak and selecting the proper devices from both technical and economic viewpoints. Among the different alternatives considered in this study, the AC fixed system represented the best cost effective solution.

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Dynamic modelling of a pv pumping system with special consideration on water demand

Pumping of water requires excessive energy for its operation by consuming a massive amount of diesel, gasoline, electric power etc. The more promising alternative energies to perform the same operation without any energy cost are solar photovoltaic (PV) and wind. These fastest growing renewable energies are more reliable and well suitable for remote villages where there is no possibility of extending transmission lines. Furthermore, these systems are optimal for conditions like only small amount of water needed to be pumped for a particular time. Unlike conventional energy sources of electric power, the renewable energy sources are not dispatchable its power output cannot be controlled. In that case, it involves power conversion stages so that it would necessitate to design an advanced control strategy technique. Those control strategies greatly avoid and protects the system from detrimental operating conditions by monitoring input voltage, water flow, torque, power, pressure, speed and motor vibration etc. Henceforth the use of efficient control strategy not only increase the performance of system it also helps to increase the number of operational hours of solar PV and wind energy systems. In this manuscript, the research work of various control strategies carried out in solar PV and wind energy-based water pumping systems are presented. Additionally, this paper intends to discuss the energy management strategies applied for renewable energy fed water pumping system when the system assisted with third energy system (battery bank, fuel cell, etc). These benefited systems ensure good design, guarantees the control speed required for the motor, regulates the flow of water, assuring accurate operation for all conversion and finally, it maintains precise balance in between the renewable energy generated and power required by the load (pump).

Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review

Variable Speed Pumping: A Guide to Successful Applications

Robust DPC-SVM control strategy for shunt active power filter based on H∞ regulators

Cavitation is one of the major disadvantages in pumping system, which enhance to form bubbles in the pipeline and it reduces the efficiency of the pump. So it should be identified and take the preventive measure. Machine Learning is a fast and computational method which can easily detect any faults in the pumping system. Still now lots of work has been done on a detection of fault in the pumping system, but mainly those work has done based on vibration details and variation of speed. The paper presents how by the help of machine learning algorithm by varying the speed and pressure cavitation can be identified. It is the comparative study between how the vibration and speed together affects the cavitation result and variation of speed and pressure affects the cavitation. Support Vector Machine is one of the classification methods in machine learning algorithm where it can be easily classified the cavitation problem. So this paper analyses how the method of SVM can more efficiently detect the cavitation problem with the centrifugal water pump.

Centrifugal Pump Cavitation Detection Using Machine Learning Algorithm Technique

Real time simulation of Variable Speed Parallel Pumping system

This work focuses on the photovoltaic array fed water pumping system utilizing induction motor with the model developed in Matlab/Simulink. PV system is designed to avail the solar energy by means of Photovoltaic cells. It consists of an arrangement of several components, including solar panels to absorb and convert sunlight into electricity. Maximum Power Point Tracking is a technique used to maximize power output from the Photovoltaic module and finally a 3 phase induction motor is driven through it. In this paper a Photovoltaic array is used to run a induction motor that drives the centrifugal pump. The simulink model of the PV array connected to induction motor where MPPT technique (perturb and observable) plays an important role that is developed in MATLAB and the outputs are observed.

V. K. Arun Shankar

Papers

Centrifugal Pump Cavitation Detection Using Machine Learning Algorithm Technique

Real time simulation of Variable Speed Parallel Pumping system

Modelling and simulation of solar photovoltaic fed induction motor for water pumping application using perturb and observer MPPT algorithm

Implementation of Shunt Active Filter for Harmonic Compensation in a 3 Phase 3 Wire Distribution Network

Sensorless parameter estimation of VFD based cascade centrifugal pumping system using automatic pump curve adaption method