Optimized Day-Ahead Pricing for Smart Grids with Device-Specific Scheduling Flexibility

Smart grids are capable of two-way communication between individual user devices and the electricity provider, enabling providers to create a control-feedback loop using time-dependent pricing. By charging users more in peak and less in off-peak hours, the provider can induce users to shift their co...

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Bibliographic Details
Published in:IEEE journal on selected areas in communications 2012-07, Vol.30 (6), p.1075-1085
Main Authors: Joe-Wong, Carlee, Sen, Soumya, Ha, Sangtae, Chiang, Mung
Format: Article
Language:English
Subjects:
Algorithms
Cost engineering
day-ahead pricing
Delay
demand response
Devices
Electric utilities
Electricity
Electricity distribution
Energy consumption
Flexibility
Generators
Mathematical models
Optimization
patience index
Pricing
Scheduling
Sensitivity
Smart-Grid pricing
Studies
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Summary:Smart grids are capable of two-way communication between individual user devices and the electricity provider, enabling providers to create a control-feedback loop using time-dependent pricing. By charging users more in peak and less in off-peak hours, the provider can induce users to shift their consumption to off-peak periods, thus relieving stress on the power grid and the cost incurred from large peak loads. We formulate the electricity provider's cost minimization problem in setting these prices by considering consumers' device-specific scheduling flexibility and the provider's cost structure of purchasing electricity from an electricity generator. Consumers' willingness to shift their device usage is modeled probabilistically, with parameters that can be estimated from real data. We develop an algorithm for computing day-ahead prices, and another algorithm for estimating and refining user reaction to the prices. Together, these two algorithms allow the provider to dynamically adjust the offered prices based on user behavior. Numerical simulations with data from an Ontario electricity provider show that our pricing algorithm can significantly reduce the cost incurred by the provider.
ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2012.120706