School of
Information Technology and Electrical Engineering

Speaker: Saeid Veysi Raygani
Seminar Date: Mon, 30/03/2020 - 14:00
Venue: 47A-352
Host: Prof Firuz Zare

Seminar Type:  PhD Thesis Review


Due to environmental concerns and exhausting fossil fuel reserves, the photovoltaic (PV) penetration level has been consistently growing, and it is rapidly becoming a significant proportion of generation in many countries. However, the intermittency of solar PV systems and expensive management strategies are the main barriers to the high penetration of large-scale solar PV systems. In the power system operation, the energy market operators run unit commitment (UC) and economic dispatch problems to assess the security and operating cost of power systems. However, conventional unit commitment models are deterministic and cannot capture the full range of high level of extra uncertainty added by PV generation.

The objective of this project is to develop and validate new approaches to facilitate the effective integration of utility-scale solar PV systems to power systems. The primary focus is to model PV output and characterise PV variability and uncertainty, and then develop unit commitment models that incorporate the unique characteristics of the solar PV systems. Accordingly, the first parts of this thesis deal with the development of the PV output and variability prediction model. This model is based on global horizontal irradiance and considers the local environmental conditions such as temperature and wind speed. The solar PV predictive model is used to predict the solar output in the security-constrained unit commitment models. Various optimisation methods are applied to the unit commitment problem to deal with the uncertainty of solar PV systems and loads. The energy market operators could utilise the developed unit commitment models, which provide a cost-effective and robust solution for intermittent large-scale solar systems and uncertain loads. The developed robust unit commitment model incorporates the unique characteristics of the solar PV systems in its uncertainty set definition. We have also developed a risk-averse unit commitment model that consolidated the risk management concept and robustness in the unit commitment problem. This tractable and robust model shapes the cost distribution under the uncertainty of solar PV systems. The experimental studies of the proposed models on the IEEE 118-Bus test-system verified the effectiveness of the proposed models in hedging the uncertainty and cost management.


Saeid Veysi Raygani is a Ph.D. candidate in the power systems group in the School of Information Technology and Electrical Engineering at the University of Queensland under the supervision of Dr. Daniel Martin and Dr. Michael Forbes. Saeid received his BSc degree in Electrical Engineering in power systems from Khajeh Nasir Toosi University, Tehran, Iran, and MSc degree in electric railway systems from Iran University of Science and Technology, Tehran, Iran. Saeid is a Registered Professional Engineer of Queensland (RPEQ) and currently working for Siemens Overhead Medium Voltage Switchgears (OMVS). His main research interests include power systems operations under uncertainty and electric railways.