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Govind Ballabh Pant University of Agriculture and Technology, Pantnagar

After independence, development of the rural sector was considered the primary concern of the Government of India. In 1949, with the appointment of the Radhakrishnan University Education Commission, imparting of agricultural education through the setting up of rural universities became the focal point. Later, in 1954 an Indo-American team led by Dr. K.R. Damle, the Vice-President of ICAR, was constituted that arrived at the idea of establishing a Rural University on the land-grant pattern of USA. As a consequence a contract between the Government of India, the Technical Cooperation Mission and some land-grant universities of USA, was signed to promote agricultural education in the country. The US universities included the universities of Tennessee, the Ohio State University, the Kansas State University, The University of Illinois, the Pennsylvania State University and the University of Missouri. The task of assisting Uttar Pradesh in establishing an agricultural university was assigned to the University of Illinois which signed a contract in 1959 to establish an agricultural University in the State. Dean, H.W. Hannah, of the University of Illinois prepared a blueprint for a Rural University to be set up at the Tarai State Farm in the district Nainital, UP. In the initial stage the University of Illinois also offered the services of its scientists and teachers. Thus, in 1960, the first agricultural university of India, UP Agricultural University, came into being by an Act of legislation, UP Act XI-V of 1958. The Act was later amended under UP Universities Re-enactment and Amendment Act 1972 and the University was rechristened as Govind Ballabh Pant University of Agriculture and Technology keeping in view the contributions of Pt. Govind Ballabh Pant, the then Chief Minister of UP. The University was dedicated to the Nation by the first Prime Minister of India Pt Jawaharlal Nehru on 17 November 1960. The G.B. Pant University is a symbol of successful partnership between India and the United States. The establishment of this university brought about a revolution in agricultural education, research and extension. It paved the way for setting up of 31 other agricultural universities in the country.

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20171
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Subject: Electrical Engineering × Author: Joshi, Puneet × End date: 2017 × Start date: 2017 × Type: Thesis ×
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    ThesisItemOpen Access
    Development and performance investigation of a novel meta-heuristic based MPPT for photovoltaic systems
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Joshi, Puneet; Arora, Sudha
    Solar energy is transformed into Electrical energy through PV systems consisting of PV panels, power conditioners & controllers and a load. Generally, there is a shift in the maximum power point with the change in the environmental conditions, a load change or due to partial shading. Hence, Maximum Power Point Tracking (MPPT) controller is required that ensures the maximum power extraction under all conditions. Many MPPT techniques for PV systems have been developed that are broadly classified as conventional methods and the modern approaches. These techniques vary in many aspects such as PV array dependency, application domain, complexity, convergence speed, periodic tuning, efficiency, simplicity, digital or analog implementation, sensors required, and cost. This work presents a novel hybridization of the Particle Swarm Optimization and the Coral reef Optimization approaches for MPPT for PV systems. In order to study the performance of the proposed method, ten widely-adopted MPPT algorithms; viz., Perturb and Observe (P&O) method, Adaptive step-size P&O method, Drift-free P&O method, Incremental Conductance (INC) Method, Adaptive step-size INC method, Incremental Resistance (INR) Method, Adaptive step-size INR method and three meta-heuristics based approaches, viz., Particle Swarm Optimization (PSO) based method, Gravitational Search Algorithm (GSA) based method, hybrid PSO-GSA method are compared with it using the Matlab/Simulink software. Firstly, the behavior of the conventional techniques was studied in presence of solar irradiation variations, imitating the natural variations occurring in the irradiance throughout the year, under constant temperature (250C). Thereafter, the methods were ranked based on the power obtained under each test conditions. In addition, the superiority of the methods was highlighted by simulation results. It was concluded that both INC method and the conventional P&O method showed the best overall efficiency ( ≈ 97%) under all test patterns. However, the meta-heuristics based approaches displayed even better results for the MPPT application. These methods, in general, exhibited very high efficiency ( ≈ 98.8%) and convergence rate under various test conditions. Amongst the selected methods, the proposed PSO-CRO method displayed highest efficiency ( ≈ 99.6%) and fastest convergence rate. Additionally, statistical analysis and two-sampled T-test were performed to determine the ordering of the methods. In addition, the meta-heuristics based approaches were tested under four partial shading conditions as well. All the methods were able to converge to the global maximum power again very quickly with an excellent efficacy. Simulation results show that the proposed PSO-CRO method can rapidly track the true MPP under different conditions with reduced steady state oscillations (to practically zero) once it is located. Furthermore, the proposed method has the ability to track the MPP for the extreme environmental condition, e.g., large fluctuations of insolation and partial shading condition. The outcome indicates the proposed method has obvious advantages, especially the performance being superior to the conventional methods. Additionally, the algorithm is simple to program and can be computed very rapidly using state-of-the art hardware technologies.