Artículos

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

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.

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.

Ecuador's energy mix has greatly reduced its dependency on fossil fuels the last 15 years, down to a marginal role (5%) in electricity generation in 2017. The development plan for the Ecuadorian power network aims to keep adding hydropower to meet the increasing demand. A prospective lifecycle assessment (LCA) of the future power network (2012–2050) can determine the feasibility of the development plan and its environmental sustainability in the long run.

Heating, ventilation, and air conditioning (HVAC) systems provide the people working/living inside buildings with ‘conditioned air’ so that they will have a comfortable and safe environment. Thermal comfort is considered as an aspect of a sustainable building in almost all sustainable building evaluation methods and tools. In fact, in the building sector, HVAC systems represent between 40 and 60% of energy consumption. In this paper, two thermal comfort methods have been experimentally analysed (Predicted Mean Vote or the so-called Fanger’s method, and the Adaptive Comfort Method).

In this paper, we use the correlation between the average wind speed and the elevation above sea level to present a regression model for calculating the average wind speed and evaluating the wind potential in the southern region of Ecuador. After obtaining the regression model, an adjustment factor based on the topographic slope has been included, mainly since the wind speed could vary largely as it blows across the lower slope regions or intermediate hills of mountains.

The Villonaco Wind Farm is located between coordinates 693030 E 9558392 N and 693526 E 9556476 N in the province of Loja in southern Ecuador. It is the first wind farm in continental Ecuador, with a capacity of 16.5 MW and a location of roughly 2720 m above sea level in rugged terrain, which is especially relevant compared to others wind farms in the global context. This paper presents a statistical analysis of the Annual Energy Production of the Villonaco Wind Farm in the period from 2014 to 2018.