Pallavi Bharadhwaj – PhD Thesis Defence

Location: B 303, Department of Electrical Engineering

Title : Modelling, Optimisation and Control of Photovoltaic Energy Conversion Systems
Speaker : Pallavi Bharadwaj, Department of Electrical Engineering, IISc
Date : Thu., Oct. 10th , 2019
Time : 9:00 AM
Venue : EE-B303

Abstract :

Uncertainty in global fossil fuel supplies and rising climate change concerns call for an urgent need to switch to renewable energy resources. There are several challenges associated with the harnessing of solar power, which have so far limited its contribution to only 8% of India’s energy mix. This work is an attempt to understand and overcome some of the fundamental challenges associated with the utilisation of the solar power.

Measurement of input and output of PV systems is the first challenge which involves expensive pyranometers. The development of in-house, low-cost, high-performance irradiation meters, with performance standardised on the basis of ISO 9060 standard, facilitates input irradiation and temperature input measurement. For output measurement, a switched mode power conversion based closed-loop controlled PV characterisation setup is developed in this work which reduces the ripple in PV current measurement as compared to open loop response.

Being a stochastic source of energy, it is difficult to predict its behavior but with the novel sequential parameter extraction method, this work presents a way of predicting the energy output of PV systems under varying ambient conditions with an improvement of 10% in the PV output prediction compared to the datasheet-based existing methods. The sequential optimisation solves the second challenge of modelling PV modules under steady state which is further enhanced for transient modelling by experimental evaluation of PV capacitance.

The third major challenge in PV energy conversion is imposed by shading, which is addressed by the first time introduction of subcell model to partial shading analysis. Subcell model is experimentally verified to be 93% accurate for opaque shading and 95% accurate for translucent shading. This model further facilitates the understanding of hotspot formation and dust induced reliability issues.

The fourth major problem is the global maximum power point tracking, to which the PV fraternity is still looking for a solution. This is addressed in this work using a fundamental shading fraction based GMPPT algorithm, wherein the shading versus global peak correlations are derived using module voltage information. This method is scalable from small to large PV strings and provides high maximum tracking speeds and improved energy capture as compared to popular existing MPPT algorithms.

All are welcome.

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