Volatility of Power Grids Under Real-Time Pricing
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Author(s)
Roozbehani, Mardavij
Dahleh, Munther A.
Mitter, Sanjoy K.
Date Issued
May 2012
Journal
IEEE Transactions on Power Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Roozbehani, Mardavij, Munther A. Dahleh, and Sanjoy K. Mitter. “Volatility of Power Grids Under Real-Time Pricing.” IEEE Trans. Power Syst. 27, no. 4 (n.d.): 1926–1940.
Version
Original manuscript
Abstract
The paper proposes a framework for modeling and analysis of the dynamics of supply, demand, and clearing prices in power systems with real-time retail pricing and information asymmetry. Characterized by passing on the real-time wholesale electricity prices to the end consumers, real-time pricing creates a closed-loop feedback system between the physical layer and the market layer of the system. In the absence of a carefully designed control law, such direct feedback can increase sensitivity and lower the system's robustness to uncertainty in demand and generation. It is shown that price volatility can be characterized in terms of the system's maximal relative price elasticity, defined as the maximal ratio of the generalized price-elasticity of consumers to that of the producers. As this ratio increases, the system may become more volatile. Since new demand response technologies increase the price-elasticity of demand, and since increased penetration of distributed generation can also increase the uncertainty in price-based demand response, the theoretical findings suggest that the architecture under examination can potentially lead to increased volatility. This study highlights the need for assessing architecture systematically and in advance, in order to optimally strike the trade-offs between volatility/robustness and performance metrics such as economic efficiency and environmental efficiency.
Description
Original manuscript: June 7, 2011
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/tpwrs.2012.2195037
