Výsledky vyhledávání - "Erasmo Cadenas"

Akademický článek

Short-Term Forecasting of Energy Production for a Photovoltaic System Using a NARX-CVM Hybrid Model

Autor: Eduardo Rangel-Heras, César Angeles-Camacho, Erasmo Cadenas-Calderón, Rafael Campos-Amezcua

Publikováno v: Energies, Vol 15, Iss 8, p 2842 (2022)

In this paper, a methodology for short-term forecasting of power generated by a photovoltaic module is reported. The method incorporates a nonlinear autoregressive with exogenous inputs (NARX) fed by the solar radiation and temperature times series,

Externí odkaz: https://doaj.org/article/41fbe91709b442398d9d6f4d22c846b2

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Akademický článek

Forecast of daily output energy of wind turbine using sARIMA and nonlinear autoregressive models

Autor: Jorge Luis Tena García, Erasmo Cadenas Calderón, Gilberto González Ávalos, Eduardo Rangel Heras, Alain Mbikayi Tshikala

Publikováno v: Advances in Mechanical Engineering, Vol 11 (2019)

Forecast models for wind speed and wind turbine power generation are valuable support tools for operators of Control Energy Center. In this work, a year of daily energy output of a wind turbine is analyzed. The original time series was separated into

Externí odkaz: https://doaj.org/article/b1d57445470c44ebb7712810c9102af4

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Akademický článek

Enhanced Prediction of Solar Radiation Using NARX Models with Corrected Input Vectors

Autor: Eduardo Rangel, Erasmo Cadenas, Rafael Campos-Amezcua, Jorge L. Tena

Publikováno v: Energies, Vol 13, Iss 10, p 2576 (2020)

The main objective of this work is to analyze and configure appropriately the input vectors to enhance the performance of NARX models to forecast solar radiation one hour ahead. For this study, Engle–Granger causality tests were implemented. Additi

Externí odkaz: https://doaj.org/article/38c6930ed66740a1ab4ac9332ce6cb50

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Akademický článek

Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Autor: Erasmo Cadenas, Wilfrido Rivera, Rafael Campos-Amezcua, Christopher Heard

Publikováno v: Energies, Vol 9, Iss 2, p 109 (2016)

Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA). This method’s performance is well studied for a large number of prediction problems. Th

Externí odkaz: https://doaj.org/article/e58ede24009f4ee194e397a1107bc760

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