Electronic Thesis and Dissertation Repository


Master of Engineering Science


Electrical and Computer Engineering


Dr. Mohammad Reza Dadash Zadeh


In this thesis, a real-time optimal dispatching (RTOD) algorithm is developed by formulating a mixed integer linear programming problem to determine charging and discharging power set-points of a privately owned energy storage system (ESS) in a competitive electricity market. The objective of the optimization problem is to generate revenue by exploiting price volatility in the day-ahead/week-ahead market. Moreover, this thesis aims to evaluate and improve the usefulness of publicly available electricity market prices for RTOD of a privately owned ESS in a competitive electricity market by developing a new adaptive technique. The pre-dispatch and the corresponding ex-post hourly Ontario energy prices are employed as the forecasted and actual prices. A compressed air ESS unit is optimally sized and modeled for evaluations. The conventional RTOD algorithm is developed, and its sensitivity to price forecast inaccuracy is evaluated. It is demonstrated that the forecast inaccuracy of publicly available market prices significantly reduces the ESS revenue. Then, a new adaptive algorithm is proposed and evaluated which adapts the objective function of the optimization problem online based on historical market prices. The outcomes reveal that the proposed adaptive RTOD can significantly reduce the adverse impact of the price forecast inaccuracy on the ESS revenue by online calibration of the 24-h-ahead market prices using 24-h-behind market prices. Moreover, the concept of optimal weekly usage of cryogenic energy storage (CES) is introduced and compared with the common daily usage. The results reveal significant benefits of weekly usage of the CES as compared to the daily usage.