This article reports a mathematical model with experimental measurements of a novel solar dryer named: Parvati Solar Dryer (PSD), which consists of a double angle linear collector and a cylindrical drying chamber with a translucent surface. Semi-theoretical and empirical thin-film models were evaluated to select the one with the best fit (higher coefficient of determination R2 and lower mean square error RMSE) in terms of the humidity ratio MR and taking into account that the drying chamber temperature does not exceed 35 ℃ to maintain the quality of the coffee. The linear collector has a mechanism that changes the reflection angles; therefore, the solar energy is captured over the focal zone where the drying chamber is located. Experimental tests were carried out using 25 kg of coffee beans of the Caturra Arabica variety. The initial coffee beans moisture content was dropped from 53 to 12.5% w.b. during a period of 33 days with 6 h of drying per day. The beans drying speed was 2.2 g/day with an average solar irradiance of 490.3 W/m2. The efficiency of the drying was 36.6%. It was found that the Hii model best fits the drying process with R^2 = 0.997 and RMSE = 0.0586. Finally, the average thermal diffusivity was 1.48 × 10^–10 m^2/s.
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. In this analysis, actual wind speed and active power values were used, outliers and missing data were identified, and a new methodology was used to complete the missing data. With the complete dataset, an analysis of variance was performed to compare the means of the annual energy production. The results obtained in this study show an error of ±4% compared to the information available on the website of the Agency for Regulation and Control of Energy and Non-Renewable Natural Resources of Ecuador.
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. Once the wind speed was obtained, both at 10 m and 100 m, the wind power density was calculated, which includes the impact of wind speed and air density. Finally, the model accuracy was obtained by comparing other free access data sources including actual data from meteorological stations, using statistical parameters to quantify the error. According to the results obtained, we find that wind speed has a good correlation with the terrain elevation of the southern region of Ecuador. The simulated wind speed compared to the actual data has errors between 7.75% and 16.89%, which indicates that the model can predict with > 83% accuracy. In addition, both the root means square error and the standard deviations have around 1 m/s of error.
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). The measurement campaign was divided into two stages. In an initial stage, HVAC electrical consumption, indoor temperature, carbon dioxide concentration, relative humidity, global horizontal irradiance, and outdoor temperature were measured through controlled conditions, performing a considerable number of tests in 112 days, covering all seasons. Later, in a second phase, with the experimental data, the two thermal comfort methods were calculated analytically. In both cases, the main conclusion is that – when the HVAC system was working with minimum energy consumption – more than 80% of the possible occupants would be satisfied with the indoor temperature, by more than 90% of the time.
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. For a quantitative analysis of the energy transition over the entire lifecycle, the simulation software® Global Emission Model of Integrated System (GEMIS) is used. The results show that the current development path of the Ecuadorian energy system reduces the emissions of CO2 per kWh generated by 65% due to the large share of renewable energies, mainly hydropower, which costs 1% of Gross Domestic Product. The obtained LCA footprints are similar to the literature benchmarks.