Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 5, Issue 2, Pages 789-798Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2013.2293131
Keywords
Demand response; real-time pricing; PAR minimization; stochastic approximation; simultaneous perturbation
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Funding
- Natural Science and Engineering Research Council of Canada (NSERC) [STPGP-396838]
- United States National Science Foundation [ECCS 1253516]
- Directorate For Engineering [1253516] Funding Source: National Science Foundation
- Div Of Electrical, Commun & Cyber Sys [1253516] Funding Source: National Science Foundation
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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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