Artículos

Having an accurate model of the power curve of a wind turbine allows us to better monitor its operation and planning of storage capacity. Since wind speed and direction is of a highly stochastic nature, the forecasting of the power generated by the wind turbine is of the same nature as well. In this paper, a method for obtaining a robust confidence band containing the power curve of a wind turbine under test conditions is presented. Here, the confidence band is bound by two curves which are estimated using parametric statistical inference techniques.

El objetivo del presente trabajo está relacionado con el proyecto de investigación “Evaluación de la contaminación atmosférica por fuentes de combustión en la ciudad de Loja y su mitigación con energías renovables”, que se desarrolla en la UNL y específicamente con la caracterización de las emisiones gaseosas y material particulado de las fuentes de contaminación atmosférica por combustión de fuentes móviles y fijas en la ciudad de Loja.

Reducing solar infrastructure costs is one of the main reasons for its global growth. In Ecuador adjustments to the legal framework have to be made to encourage the installation of small photovoltaic solar structures for electricity customers connected to low voltage distribution networks for their personal consumption, and any surplus energy be injected into the grid.

Due to its zero-marginal-cost, the high penetration of renewable energy sources in the electricity markets threatens incumbents’ business models who are gradually shifting towards fixed power charges instead of the traditional energy charges. The purpose of this study is to assess the impacts of these fixed power charges on the economics of PV systems under self-consumption schemes. Using real demand and generation data, simulations include detailed computation of annual billing savings, payback-time, self-consumption and self-sufficiency of a dwelling coupled with PV-battery system.

This study aims to improve our knowledge concerning the air quality by analysing carbon dioxide (CO2) emissions emanating from motor vehicles. The vehicle fleet was characterized by means of surveys, vehicular seating capacity, and collection of information from both public and private entities.

Accurate and reliable prediction of wind energy in the short term is of great importance for the efficient operation of wind farms. One of the procedures to search for, summarize, organize and synthesize existing information is a systematic literature review. In this article, we present a systematic literature review on the predictive models of wind energy, aiming to establish the baseline for the development of a short-term wind energy prediction model that employs artificial intelligence tools to be applied in the Villonaco Wind Power Plant.

El estudio de guías para el cambio de luminarias de vapor de sodio por vapor de mercurio y en el futuro mediato luminarias LED por luminarias de vapor de sodio

Wind energy is a non-programmable form of generation, hence, accurate and reliable wind energy prediction is of great importance for the efficient operation of wind farms. This article presents a study for the prediction of active power for the Villonaco Wind Farm (VWF), located in southern Ecuador at approximately 2700 m above sea level.

The World Wind Energy Association (WWEA) forecasts that installed wind capacity worldwide will reach 800 GW by the end of 2021. Because wind is a random resource, both in speed and direction, the short-term forecasting of wind energy has become an important issue to be investigated.

Operation and maintenance (O&M) activities represent a significant share of the total expenditure of a wind farm. Of these expenses, costs associated with unexpected failures account for the highest percentage. Therefore, it is clear that early detection of wind turbine (WT) failures, which can be achieved through appropriate condition monitoring (CM), is critical to reduce O&M costs.