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Model predictive and genetic algorithm based optimization of residential temperature control in the presence of time-varying electricity prices

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4 Author(s)
Diogenes Molina ; Georgia Institute of Technology, Atlanta, 30332, USA ; Coby Lu ; Vicktoriya Sherman ; Ronald Harley

This paper presents an optimization and control algorithm for residential temperature regulation. Concepts from system identification, model-predictive control, and genetic algorithms are evoked in the pursuit of an optimization methodology capable of achieving an acceptable compromise between comfort and cost in the presence of constant as well as time-varying electricity prices. Simulation results demonstrate that the proposed approach has the potential to achieve substantial energy savings and cost reductions while maintaining acceptable comfort levels.

Published in:

Industry Applications Society Annual Meeting (IAS), 2011 IEEE

Date of Conference:

9-13 Oct. 2011