Development of Experimental Set up for Modeling and Parameter Estimation of Solar Photovoltaic Array Fed Irrigation Pumps through Machine Learning Technique

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Project Summary Water pumps in irrigation sector as well as domestic and industrial sectors, have been benefitted by the introduction of renewable source based power production in these sectors. A number of DC motors and permanent magnet DC [PMDC] motors driven PV pumps are already in use in several parts of the world. However, they suffer from maintenance problems due to the presence of the commutator and brushes. Other brushless motors such as permanent magnet synchronous motor [PMSM], permanent magnet brushless DC motor [PMBLDCM], switched reluctance motor [SRM] and synchronous reluctance motors [SyRM] which exhibit their own advantages have been rarely used for SPV based water pumping systems. The Modeling and Parameter Estimation of Solar Photovoltaic Array Fed Irrigation Pumps aims to develop an accurate mathematical model of a solar photovoltaic [PV] array that can predict the electrical behavior of the system under various operating conditions. The project will involve estimating the parameters of the model using experimental data obtained from the PV array, such as current-voltage curves, irradiance and temperature variations, and other relevant measurements. This modelled and parameter-estimated solar PV array is used to drive a water pump for irrigation. The performance of the system will be analyzed, and factors that affect its efficiency, such as shading, dust accumulation, and module orientation, will be identified. Using the developed model, the project will investigate the impact of different variables, such as module configuration, tracking systems, and inverter technologies, on the system's performance, and make recommendations on optimizing the design and operation of the system. Also the recurrence in PV power generation leads to an unreliable water pumping in a PV based pumping system. This problem is aggravated when there is a bad climatic condition leading to underutilized or unutilized pumping operation. This problem is resolved by an external power backup in the form of a battery storage with a bidirectional buck-boost converter, in a PV-pumping system. In addition to it, an attempt will be made for integrating unidirectional and bidirectional converters to the utility grid. The bidirectional power flow control based topology offers an additional merit of feeding power to the utility grid by the installed PV array, in case the water pumping is not required. The accuracy of the developed model will be validated by comparing predicted results with experimental data obtained from the PV array under different conditions. The project aims to provide insights into the behavior of solar PV arrays, optimize their design and operation, and contribute to the development of sustainable energy solutions. Various advantages allied with the solar PV, also faces numerous challenges that comprise the designing of best possible configurations for solar PV arrays, optimised power converters with converter protocols, optimised maximum power point tracking [MPPT] techniques, and prediction of generated power under real-time environmental conditions, development of sensorless techniques of motors employed in water pumping for both standalone and grid-integrated topologies, mitigation of power quality issues to improve the power quality of the grid side for three-phase grid. Hence, various simulations are to be executed at specific software platforms through various solar PV electrical models, where modelling of these quantified electrical equivalent models should be reliable, robust, and accurate. In view of this it is important to comprehend that the precision of a commercially available solar PV simulation software resides on the electrical PV model selected, the model parameter extraction technique incorporated, and the preciseness in estimated model parameters through various techniques. This project aims the assessment of precise solar PV modelling parameters, validated through experimental current-voltage [I-V] data, and to achieve this goal. In this project SDM, DDM and TDM are selected and modeled for different case studies under different sets of environmental conditions through various modern metaheuristic and hybrid techniques. Keywords Modeling of solar photovoltaic, Environmental conditions, Optimization, Parameter Estimation, Renewable energy, Solar Photovoltaic, Motor-drive, MPPT of solar PV array, sensorless control of motor, Irrigation pumps, Utility grid, Bidirectional converter.