Uncertainty cost functions in climate-dependent controllable loads in commercial environments

Daniel Losada, Ameena Al-Sumaiti, Sergio Rivera

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageBritish English
Article number2885
JournalEnergies
Volume14
Issue number10
DOIs
StatePublished - 2 May 2021

Keywords

  • Controllable load
  • Electricity demand
  • Expected value
  • Probability density estimator
  • Probability density function
  • Uncertainty cost

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