By Topic

Optimal real-time price based on a statistical demand elasticity model of electricity

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Rongshan Yu ; Inst. for Infocomm Res., A*STAR, Singapore, Singapore ; Wenxian Yang ; Rahardja, S.

In this paper, we study the price elasticity of electrical demand in a smart grid framework where the loads of a power system are scheduled by energy management controller (EMC) units that aim to maximize users' benefits by considering both load utilities and real-time electricity price. We show that different price responsive behaviors of electrical loads result from interaction between their utilities and electricity prices. Here, the utility is modeled as a function of time in order to represent the timeliness of loads. Based on the developed theory, we introduce a parametric utility model from which the price elastic behaviors of aggregated loads from a power system are established statistically as multi-dimensional demand-price functions. Finally, we investigate the problem of optimal real-time electricity prices under the framework of social welfare maximization. Considering demand elasticity from users, we show here that the optimal real-time electricity prices that maximize the social welfare of a power system will match the marginal costs of energy production at load levels resulting from these optimal electricity prices. The solution for this can be pre-calculated using a simple iterative algorithm without the need for excessive information exchange between users and the utility company. Theoretical results from this paper are validated through numerical examples using a simplified power network.

Published in:

Smart Grid Modeling and Simulation (SGMS), 2011 IEEE First International Workshop on

Date of Conference:

17-17 Oct. 2011