Real-Time Pricing for Demand Response Based on Stochastic Approximation

Samadi P, Mohsenian-Rad H, Wong VWS, Schober R (2014)


Publication Language: English

Publication Type: Journal article

Publication year: 2014

Journal

Book Volume: 5

Pages Range: 789 - 798

Journal Issue: 2

DOI: 10.1109/TSG.2013.2293131

Abstract

In this paper, we propose a new pricing algorithm to minimize the peak-to-average ratio (PAR) in aggregate load demand. The key challenge that we seek to address is the energy provider's uncertainty about the impact of prices on users' load profiles, in particular when users are equipped with automated energy consumption scheduling (ECS) devices. We use an iterative stochastic approximation approach to design two real-time pricing algorithms based on finite-difference and simultaneous perturbation methods, respectively. We also propose the use of a system simulator unit (SSU) that employs approximate dynamic programming to simulate the operation of the ECS devices and users' price-responsiveness. Simulation results show that our proposed real-time pricing algorithms reduce the PAR in aggregate load and help the users to reduce their energy expenses.

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How to cite

APA:

Samadi, P., Mohsenian-Rad, H., Wong, V.W.S., & Schober, R. (2014). Real-Time Pricing for Demand Response Based on Stochastic Approximation. IEEE Transactions on Smart Grid, 5(2), 789 - 798. https://doi.org/10.1109/TSG.2013.2293131

MLA:

Samadi, Pedram, et al. "Real-Time Pricing for Demand Response Based on Stochastic Approximation." IEEE Transactions on Smart Grid 5.2 (2014): 789 - 798.

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