Feature Selection in Energy Consumption of Solar Catamaran INER 1 on Galapagos Island
Marcelo Moya,
Javier Martínez-Gómez,
Esteban Urresta and
Martín Cordovez-Dammer
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Marcelo Moya: Technology Transfer and Incubation Department, Instituto de Investigación Geológico y Energético (IIGE), Quito 170518, Ecuador
Javier Martínez-Gómez: Technology Transfer and Incubation Department, Instituto de Investigación Geológico y Energético (IIGE), Quito 170518, Ecuador
Esteban Urresta: Technology Transfer and Incubation Department, Instituto de Investigación Geológico y Energético (IIGE), Quito 170518, Ecuador
Martín Cordovez-Dammer: Technology Transfer and Incubation Department, Instituto de Investigación Geológico y Energético (IIGE), Quito 170518, Ecuador
Energies, 2022, vol. 15, issue 8, 1-17
Abstract:
Maritime passenger transport in the Galapagos Islands–Itabaca Channel is based on boats with combustion engines that consume an annual average of 4200 gallons of fuel and produce about 38 tons of CO 2 per year. The operation of the solar catamaran “INER 1” electric propulsion (PV) is a renewable and sustainable model for passenger shipping in the Galapagos Islands. In this regard, the detailed study of the relationship between the variability of solar radiation, the abrupt change of tides due to changes in wind speed and direction, and the increase in tourists, according to dry and wet seasons, cause high energy consumption. The boats must absorb energy from the electrical grid of the islands; this energy is from renewable (solar and wind) and, mostly, of fossil origin so identifying the source of the energy absorbed by the boats is essential. The aim of this study was to select the most influential attributes in the operation of the solar catamaran “INER 1” in the Galapagos Islands. The methodology for knowledge discovery in the databases was determined by selecting attributes that combine environmental, social, and energy variables affecting the energy performance of the solar catamaran. The energy consumption of the boats features a direct relationship with the attributes defined in this research as: (1) Energ (energy used), (2) Tur (tourists and residents), (3) Fotov (PV park), (4) Glrad (global radiation), (5) date (date and time), (6) Term9 (thermo-electric 9). Considering the six best attributes filtered by the proposed algorithms, 4.95% in the mean squared error parameter and a 98.94% accuracy in the classification and prediction of the energy consumed by boats were obtained.
Keywords: Galapagos Islands; biodiversity; solar photovoltaic; sustainable shipping; algorithm; artificial intelligence (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: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:8:p:2761-:d:790124
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