Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

Huang, Hao, Li, Fangxing, & Mishra, Yateendra (2015) Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation. IEEE Transactions on Smart Grid, 6(6), pp. 2704-2713.

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Abstract

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Impact and interest:

3 citations in Scopus
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3 citations in Web of Science®

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ID Code: 91591
Item Type: Journal Article
Refereed: Yes
Keywords: Demand Response, Load Management, Power Markets, Monte Carlo methods, demand side management
DOI: 10.1109/TSG.2015.2435011
ISSN: 1949-3061
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Power and Energy Systems Engineering (excl. Renewable Power) (090607)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 04 Jan 2016 23:11
Last Modified: 05 Jan 2016 22:58

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