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Chen, Bo

University of British Columbia

The transition to renewable energy sources (RESs), such as wind and solar, is vital for creating an environmentally sustainable electric power grid. However, this shift introduces significant technical challenges due to the variability and uncertainty inherent in renewable generation. Traditional electricity market pricing methods, such as locational marginal prices (LMPs), were designed for power systems largely operating in steady state and are not well-suited to handle the dynamic and uncertain nature of deep penetration of RESs. These changes call for updated market pricing methods that can ensure both economic efficiency and system reliability. This dissertation addresses the aforementioned challenges by developing real-time pricing methods that incorporate power system frequency dynamics and uncertainty into real-time electricity market operations. By embedding frequency dynamics into the pricing framework, we generalize the concept of LMPs to capture the costs of maintaining system frequency in a renewable-rich grid. This approach helps to mitigate the increased costs associated with setting aside reserves to handle rapid and frequent power fluctuations. We further assess the impact of probabilistic uncertainty in forecasts of generation and demand on the marginal price of electricity subject to tolerable levels of operational risk. We also develop a method to price power reserves that incentivizes generators to support system dynamic frequency performance. We additionally tailor a general modelling approach to represent the uncertainty arising from generation and demand, with a specific case study in analyzing electric vehicle charging patterns. Overall, through extensive numerical simulations, proposed pricing methods demonstrate additional revenue opportunities for generators to contribute to improved system dynamic performance. This research offers ideas for the future evolution of electricity markets, ensuring they are well-equipped to support the growing share of RESs in the electric power system.

Text

2025-04-04

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/90588

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/