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

Daniel Losada, Ameena Al-Sumaiti and Sergio Rivera
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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

Energies, 2021, vol. 14, issue 10, 1-22

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.

Keywords: uncertainty cost; electricity demand; controllable load; probability density estimator; probability density function; expected value (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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