Residential demand response under uncertainty

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Abstract

This paper considers a residential market with real-time electricity pricing and flexible electricity consumption profiles for customers. Such a market raises an optimisation problem for home automation systems where they need to schedule consumption activities to reduce costs, whilst maintaining a base level of comfort and convenience. This optimisation problem faces uncertainty in real-time prices, weather conditions, and occupant behaviour. The paper presents two online stochastic combinatorial optimisation algorithms that produce fast, high-quality solutions to this problem. These algorithms are compared with reactive control strategies and a clairvoyant controller. Our results demonstrate the value of stochastic information and online stochastic optimisation in residential demand response. © 2013 Springer-Verlag.

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APA

Scott, P., Thiébaux, S., Van Den Briel, M., & Van Hentenryck, P. (2013). Residential demand response under uncertainty. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8124 LNCS, pp. 645–660). https://doi.org/10.1007/978-3-642-40627-0_48

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