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Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Author

Listed:
  • Daniel Losada

    (Electrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, Colombia)

  • Ameena Al-Sumaiti

    (Advanced Power and Energy Center, Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi 127788, United Arab Emirates)

  • Sergio Rivera

    (Electrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, Colombia)

Abstract

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

Suggested Citation

  • Daniel Losada & Ameena Al-Sumaiti & Sergio Rivera, 2021. "Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments," Energies, MDPI, vol. 14(10), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2885-:d:556158
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    References listed on IDEAS

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