Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2016Researchpeer-review

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Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear controller
is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.
Original languageEnglish
Title of host publicationProceedings of IEEE ISGT 2016
Number of pages6
Publication date2016
ISBN (Print)978-1-5090-3358-4
Publication statusPublished - 2016
Event2016 IEEE PES Innovative Smart Grid Technologies - Ljubljana, Slovenia
Duration: 9 Oct 201612 Oct 2016


Conference2016 IEEE PES Innovative Smart Grid Technologies

    Research areas

  • Economic model predictive control, Flexible electricity consumption, Load shifting, Nonlinear model-based controller, Smart grid
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ID: 126535014