• Energy Research

Mexico has more than 40 years of researching, investing, and obtaining electric power through wind energy. Within the country, there are highly windy areas, such as the Isthmus of Tehuantepec or the state of Tamaulipas, and there are about 2500 MW installed and 70,000 MW tested, all onshore. There are still no offshore wind farms in Mexico, despite having two main coasts, the East and the West, with the Gulf of Mexico and the Pacific Ocean, respectively. Although the Mexican coastal states of the Gulf of Mexico are Tamaulipas, Veracruz, Tabasco, Campeche, and Yucatán, this work focuses on the study and feasibility of offshore wind energy use on the coasts of the states of Tabasco, Campeche, and Yucatán. This is because of the availability of data in that region; however, sustainability criteria that can be used in other regions are also presented. MERRA-2 and ERA5 data were used employing WAsP and Windographer software. It was found that the capacity factor in the area of Tabasco, Campeche, and Yucatán is 32%, 37%, and 46%. It can be noted that, in the WF100% scenario, each of the wind farms could contribute more than 35% of the region’s electricity consumption; those of Campeche and Yucatán stand out with contributions of more than 70%.

In the present work, a methodology that allows optimizing the permanent magnet synchronous generator (PMSG) design by establishing limit values of magnet radius and length that maximize efficiency for the nominal parameters of the wind turbine is developed. The methodology consists of two fundamental models. One model calculates the generator parameters from the radius of the magnet base, and the other optimization model determines two optimum generators according to the optimization criteria of maximum efficiency and maximum efficiency with minimum weight starting from the axial length and the radius of the magnet base. For the optimization, the numerical method of the golden section was used. The model was validated from a 10 kW PMSG and the results of two optimum generators are presented according to the optimization criteria. In addition, when the obtained results are compared with the reference electric generator, an increase in efficiency of 1.15% and 0.81% and a reduction in weight of 30.79% and 39.15% of the optimized generators are obtained for maximum efficiency and minimum weight, respectively. Intermediate options between the maximum efficiency generator and the minimum weight generator allows for the selection of the optimum dimensioning for the electric generator as a function of the parameters from the wind turbine design.

Abstract Chilli is a vegetable that is produced and consumed in various parts of the world, not only for its culinary qualities but also for its nutritional content and potential industrialization. Mexico has the highest genetic diversity of chilli, with more than 40 varieties. A dried chilli has different properties of flavour, colour and pungency and a high added value; however, information about its dehydration is scarce. In this work, the dehydration of a red chilli, the “costeno” ( Capsicum annuum L.), which is highly appreciated for its organoleptic properties and used in the food industry, was carried out. The experimental study was performed at the Instituto of Energias Renovables (IER) of the Universidad Nacional Autonoma de Mexico (UNAM) in Temixco, Morelos, Mexico, located at 18°51′NL and 99°14′WL. The drying process was carried out at controlled temperatures of 45 °C, 55 °C and 65 °C, using a laboratory oven and an indirect tunnel-type solar dryer. The drying kinetics between 55 °C and 65 °C are similar, with drying times of 2.75 h and 3.0 h, respectively, while at 45 °C, the drying time was 6.25 h. Wang and Sing’s model gave a better fit for the drying kinetics at 45 °C, and the Page model was better for 55 °C and 65 °C. In the solar drying processes, two ranges of air velocity were established; high velocity was between 1.4 and 2.6 m/s, and low velocity was between 0.7 and 1.48 m/s. In both cases, a temperature between 31 °C and 45 °C was obtained. For the first range, the total drying time was 16 h, reaching a final moisture content between 0.057 kg of water/kg dry matter and 0.90 kg water/kg dry matter. For the second range, the time was 21 h, with a moisture content of 0.0611 kg of water/kg dry matter and 0.109 kg of water/kg dry matter.

A methodology for the optimization of renewable hybrid low power generation systems (RHLPS) is presented, analyzing its performance under different control strategies and thus reducing the costs of power generation using the existing equipment, and varying only the configuration of the factory settings. The above is achieved through the use of software tools for simulations and sensitivity analysis. In the first instance, a description of the different control strategies that have been applied to the RHLPSs is made. Secondly, a RHLPS optimization methodology is developed by means of control strategies. As a third and last point, the methodology is applied to a system in operation, where, through simulations, the optimal values are obtained and those allow to analyze the operation of the system under different control strategies. The results show that an appropriate control strategy allows a better performance and operation of the systems, and therefore it is important to perform an optimization and operational analysis to the existing systems, to make a better use of the equipment, as well as the available renewable resources.

SUMMARY The design of autonomous systems for the rural electrification is a complex task due to the diversity of variables involved in such processes. The absence of programs and methods that carry out this task in a clear and precise manner constitutes a barrier to the dissemination of these systems, although some tools have been developed that present other possible limitations. The exclusion of the environmental dimension in the design and evaluation process of hybrid systems means that the true benefits are not evaluated in terms of quality and quantity. In an attempt to overcome such deficiencies, this work presents a new method of design; approached from the multi-objective optimization of systems. The multi-objective optimization by means of enumerative search implemented by the Hybrid Optimization Model for Electric Renewable program is used to generate a set of solutions optimized economically by the value of the net present cost (NPC). The analysis of greenhouse gas emissions (in tCO2-eq.) in the life cycle of each one of the system components is carried out and a set of solutions with the values of the two objective functions is generated, namely NPC and NAESLC (net avoided emissions in the system life cycle). The method is applied to a case study in a Cuban rural community. The compromise solution obtained by means of the proposed algorithm includes a wind turbine (WT) of 25.4 and 8 kW of photovoltaic panels, while that of the HOGA includes a WT of 76 and 21 kW of photovoltaic panels. Both commitment solutions consider hydrogen storage instead of storage in batteries, as a better option for the energy storage. Copyright © 2011 John Wiley & Sons, Ltd.

One of the most common problems in wind resource assessment is that measured data are not always available at the site of interest. That is why, in several studies, reanalysis data have been used as an alternative, which, in some cases, have been validated by measured data. Mexico is no exception, since there are not many measurement towers in the country that provide valid records throughout the country. In view of the above, in this study a comparison was made between the measurements observed in six anemometric towers, located in different locations in the United Mexican States; data from the MERRA-2 and ERA-5 reanalysis; and data from the generalized wind climates (GWC), available in the Global Wind Atlas. The study was conducted at 80 m, which is the highest height at which data were recorded on the measurement towers at each site. In the case of the MERRA-2 and ERA-5 data, extrapolation of the data series to 80 m was required. In the case of the towers, a comparison of the two data sets measured at 80 m and the height at which two anemometers were available, was performed. This analysis was supported by Windographer version 4 software designed by the company UL solutions, from which *.tab files were exported at 80 m, which were then imported from the WAsP 10.0 program to perform the microscale modeling. The comparison variable was the mean power density, for which the relative deviations between the measured values and those obtained from the reanalysis data and the GWCs were determined. For a better interpretation of the relative errors calculated, an analysis of the orographic characteristics of all the sites was performed using the roughness index (RIX). The results obtained showed that the behavior of the reanalysis and the GWC data was not homogeneous in the sites studied; therefore, an adequate relationship between the magnitudes of the ΔRIX and the relative deviations was not observed, especially for the ERA5 and GWC. The ERA5 data were the furthest from the measured data, with relative deviations greater than 50% at five of the six sites; however, the MERRA-2 and GWC data were the closest to the measured data. The MERRA-2 data showed deviations of less than 11%, except at the La Venta site, where it was 29.5%—a site where the GWC also had a high deviation of 139.4%. The latter is attributable to the effects caused by the nearby wind farms on the wind flow measured by the La Venta station. In general, the MERRA-2 data are an alternative to performing a pre-analysis of the wind resource in Mexico.