Solar and geothermal energies are considered cleaner and more useful energy sources that can be used to avoid the negative environmental impacts caused by burning fossil fuels. Several works have reported air-conditioning systems that use solar energy coupled to geothermal renewable energy as a thermal source. In this study, an Absorption Air-Conditioning System (AACS) used sodium hydroxide-water (NaOH-H₂O) instead of lithium bromide-water to reduce the cost. Low enthalpy geothermal heat was derived from two shallow wells, 50 and 55 m deep. These wells are of interest due to the thermal recovery (temperature vs. time) of 56.2 °C that was possible at the maximum depth, which can be used for the first stage of the process. These wells were coupled with solar energy as a geothermal energy application for direct uses such as air-conditioning systems. We studied the performance of an absorption cooling system operating with a NaOH-H₂O mixture and using a parabolic trough plant coupled with a low enthalpy geothermal heat system as a hybrid heat source, as an alternative process that can help reduce operating costs and carbon dioxide emissions. The numerical heat transfer results showed the maximum convective heat transfer coefficient, as function of fluid velocity, and maximum temperature for a depth higher than 40 m. The results showed that the highest temperatures occur at low fluid velocities of less than or equal to 5.0 m/s. Under these conditions, reaching temperatures between 51.0 and 56.2 °C in the well was possible, which is required of the geothermal energy for the solar energy process. A water stream was used as the working fluid in the parabolic trough collector field. During the evaluation stage, the average experimental storage tank temperature achieved by the parabolic trough plant was 93.8 °C on October 23 and 92.9 °C on October 25, 2017. The numerical simulation used to evaluate the performance of the absorption cycle used a generator temperature of 90 °C, a condenser and absorber temperature at 35 °C, and an evaporator temperature of 10 °C. The Coefficient of Performance was calculated as 0.71 under design conditions.

Thermal energy recovery systems have different candidates to mitigate CO₂ emissions as recommended by the UN in its list of SDGs. One of these promising systems is thermal absorption transformers, which generally use lithium-water bromide as the working fluid. A Double Stage Heat Transformer (DSHT) is a thermal machine that allows the recovery of thermal energy at a higher temperature than it is supplied through the effect of steam absorption in a concentrated solution of lithium bromide. There are very precise thermodynamic models which allow us to calculate all the possible operating conditions of the DSHT. To perform the control of these systems, the use of Artificial Intelligence (AI) is proposed with two computational techniques—Fuzzy Logic (FL) and Artificial Neural Network (ANN)—to calculate in real-time the set of variables that maximize the product’s Gross Temperature Lift (GTL) and Coefficient of Performance (COP) in a DSHT. The values for Coefficient of Determination (R²), Mean Square Error Root (MRSE), and Mean Error Bias (MBE) for the two types of computational techniques were analyzed and compared with the purpose of identifying which of them may be more accurate to calculate the operating conditions (temperatures, pressures, concentration and flows) with the highest COP for an interval of the value of the temperature absorption entered by the user. The result of the analysis of the evaluated techniques concluded that the control strategy of a DSHT in real-time will be based on the precise calculation of the refrigerant flow in the second evaporator with a Neural Network of 30 neurons, 300 weights and 40 bias, as it is more accurate than the Fuzzy Logic technique. The goodness-of-fit for two computational techniques was evaluated as having an R² higher than 0.98 for the provided data. Future AI controllers must be based on evaporator flow values with evaporator power at 3.9⁻⁰⁴ kg/KJ.

A parametric study of a ground-to-air heat exchanger (GAHE) using numerical models based on computational fluid dynamics with the finite volume method to evaluate the thermal potential of GAHE is presented. After the validation of the numerical code developed with published experimental data, it is proceeded to the study of the geometric parameters to define those that have the greatest impact on the application potential of GAHE. Climatological variables such as relative humidity, air flow velocity, and inlet air temperature are analyzed, as well as the increase in the thermal conductivity of the soil due to its humidity content. In addition, a study of the optimal installation depth as well as the length of the thermal insulation in the outlet pipe of the GAHE is presented. The results reveal that there is a higher heat exchange potential in the GAHE for an optimal burial depth of 4 m and a length of pipe of 15 m, 30% soil moisture content for heating and 32% for cooling, and a pipe diameter of 0.15 m. The use of thermal insulating is recommended only for the last 2 m of length in the outlet pipe of the GAHE.

The use of the phase change material (PCM) as a storage medium represents an important advance to store energy for the absorption cooling systems when solar energy is not available; however, the temperature of the storage tank is a key parameter for the adequate operation of the cooling system. This paper presents a parametric analysis of a flat and a commercial plate heat exchangers with MgCl₂·6H₂O as the PCM at absorption cooling conditions. The plate heat exchanger (PHE) is a chevron type with an angle of 45° and a plate area of 0.04 m². The governing equation was solved using the method of finite difference. The results showed that the corrugated plate improved the heat transfer than the flat plate; however, the flat plate obtained a higher operation time than the corrugated plate for the absorption cooling condition in the discharge process because the output temperature of the PHE was much higher than the operating conditions. Finally, the decrement of the PCM thickness and the increment of the input temperature and flowrate of the heating fluid improved the heat transfer of the PHE; however, the main thermal resistance was still in the PCM.

Electricity is fundamental to modern societies and will become even more so as its use expands through different technologies and population growth. Power generation is currently the largest source of carbon-dioxide (CO₂) emissions globally, but it is also the sector that is leading the transition to net zero emissions through the rapid rise of renewables. The impacts of COVID-19 on the electricity sector led to a reduction in the demand for electricity, while at the same time, the current global energy crisis has placed the security and affordability of electricity at the top of the political agenda in many countries. In this way, the decrease in the demand for electricity, as well as its gradual recovery, makes it necessary to carry out energy planning that considers the adverse effects caused by global events with a high socioeconomic impact. In this article, the Low Emission Analysis Platform (LEAP) 2020 software has been used to determine the distribution of energy sources to 2050 for Mexico. The variables that lead to the possible profiles for 2050 are social, economic, and technological. The results correspond to a possible future based on official data from the National Electric System (SEN) of Mexico. The forecast for 2050 indicates that the electricity sector will have almost double the current installed capacity; however, emissions do not correspond to twice as much: they are practically 50% higher.