Embedded System for Electrical Load Characterization Based on Artificial Neuronal Networks in the Management of Electrical Demand in a Domotic System

Author(s):  
Kevin Andrés Suaza Cano ◽  
Ángel Stiven Angulo Gamboa ◽  
Javier Ferney Castillo Garcia
2021 ◽  
Vol MA2021-01 (54) ◽  
pp. 1313-1313
Author(s):  
Henevith Gisell Méndez Figueroa ◽  
Darío Colorado Garrido ◽  
R. Galván Martínez ◽  
Miguel Ángel Hernandez ◽  
Ricardo Orozco Cruz

Author(s):  
Benjamin M. Adams ◽  
Thomas H. Kuehn

CO2 Plume Geothermal (CPG) energy generation is a renewable technology that uses CO2 as the geologic working fluid within naturally permeable, sedimentary thermal reservoirs. In this paper, we compare the ability for CPG geothermal technology to meet electrical demand requirements, compared with other renewable technologies, for a 10MW, northern climate town near Minot, North Dakota. Wind and solar are both supply-driven technologies, capturing energy when it is available; However CPG is demand-driven—the rate at which energy is removed from within the earth is chosen to meet electrical demand. Using meteorological data, we compare estimated system performance with actual 2010 electrical load to gage each system’s ability to meet demand. CPG is found to most closely match system demand during the three-season (fall, winter, spring) year, where solar production is inversely related to demand. At the same time, wind does not track demand during any portion of the year, consistently having a large variability. None of these renewable technologies was found to track demand all year. Ultimately we show that CPG may be used to reliably track hourly demand during 95% of the year—an unattainable result for wind and solar.


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