Absorption systems are a sustainable solution as solar driven air conditioning devices in places with warm climatic conditions, however, the reliability of these systems must be improved. The absorbing component has a significant effect on the cycle performance, as this process is complex and needs efficient heat exchangers. This paper presents an experimental study of a bubble mode absorption in a plate heat exchanger (PHE)-type absorber with NH₃-LiNO₃ using a vapor distributor in order to increase the mass transfer at solar cooling operating conditions. The vapor distributor had a diameter of 0.005 m with five perforations distributed uniformly along the tube. Experiments were carried out using a corrugated plate heat exchanger model NB51, with three channels, where the ammonia vapor was injected in a bubble mode into the solution in the central channel. The range of solution concentrations and mass flow rates of the dilute solution were from 35 to 50% weight and 11.69 to 35.46 × 10⁻³ kg·s⁻¹, respectively. The mass flow rate of ammonia vapor was from 0.79 to 4.92 × 10⁻³ kg·s⁻¹ and the mass flow rate of cooling water was fixed at 0.31 kg·s⁻¹. The results achieved for the absorbed flux was 0.015 to 0.024 kg m⁻²·s⁻¹ and the values obtained for the mass transfer coefficient were in the order of 0.036 to 0.059 m·s⁻¹. The solution heat transfer coefficient values were obtained from 0.9 to 1.8 kW·m⁻²·K⁻¹ under transition conditions and from 0.96 to 3.16 kW·m⁻²·K⁻¹ at turbulent conditions. Nusselt number correlations were obtained based on experimental data during the absorption process with the NH₃-LiNO₃ working pair.

Dried, bitter orange leaves are widely used because of their nutritious and medicinal applications. As a result, many technologies have been used to accomplish its drying process. However, drying needs a long time and high energy demand, especially in humid climates. In this paper, bitter orange leaf drying was carried out using thermal and photovoltaic solar energy (integrated system, IS), eliminating the high humidity inside of the drying chamber to improve this process. A regular solar dryer (RD) was also used to compare the kinetics, mathematical modeling, and colorimetry study (as a quality parameter), evaluating both systems’ performances. The drying leaves’ weights were stabilized after 330 min in the RD and after 240 min in the IS, with a maximum drying rate of 0.021 kg water/kg dry matter∙min, reaching a relative humidity of 7.9%. The Page and Modified Page models were the best fitting to experimental results with an Ra² value of 0.9980. In addition, the colorimetric study showed a better-preserved color using the IS, with an ∆E of 9.12, while in the RD, the ∆E was 20.66. Thus, this system implementation can reduce agroindustry costs by reducing time and energy with a better-quality and sustainable product, avoiding 53.2 kg CO₂ emissions to the environment.

This work presents a numerical approach to compute optimal operating conditions that maximize the absorption flux into a heat exchanger designed for absorption refrigeration systems. Experimental data were obtained from a test circuit that operates in bubble absorption mode with an inner vapor distributor into a Plate Heat Exchanger-type (PHE-type) and interacts with ammonia vapor, NH3-H2O refrigerant, and cooling water. An artificial neural network (ANN) was trained to correlate the thermal properties of the solution and absorption flux in function of easily measurable parameters (concentrations, mass flows, and pressures of saturated and diluted solutions, flow and temperature of the ammonium vapor, environment temperature, and solution temperature). According to results, ANN is adequate to correlate the operational parameters and the transport phenomena inside the heat exchanger with a precision > 99%. ANN also quantitatively identified the ammonium vapor flow (43.1%), dilute solution flow (18.1%), and dilute solution concentration (13.1%) as the variables most importantly in influencing absorption flux optimization. Subsequently, a multivariable inverse artificial neural network was applied to improve the mass transfer into the PHE-type.It was identified that simultaneous optimization of the ammonia and dilute concentration flow rates improves the absorption flow performance by up to 96.3% under a worst-case scenario (ammonia flow rate2.0 kg/min). Finally, it was confirmed that incorporating the diluted solution concentration into the optimization contributes to improving the performance of the absorption process 1%. Results obtained are relevant in the search to produce more competitive absorption cooling systems, demonstrating the feasibility of improving the performance of heat exchangers without structural modifications. The proposed methodology represents an interesting option to be implemented to improve performance in solar cooling systems.

The offline protection coordination problem in the interconnected network has always been one of the important tasks for the researchers. This problem is remarkably constrained and non-linear when considering both the time dial and pickup settings. In addition, the consistent load and topology changes as well as the stochastic renewable distributed generation (DG) made the fixed protection settings become more vulnerable to coordination loss when a fault occurs. Hence, this proposal consists of an adaptive protection scheme that adjust the pickup current and time dial relay settings in a decoupled manner. Where the pickup current settings for each DOCR are determined by the maximum N-1 contingency current that passes through the relay. In addition, the DOCRs time dial settings are optimized alone using the EVOlutionary Algorithm of Random Variables with NORMal Distributions (Evonorm) algorithm. The proposed Evonorm algorithm which is an easy and effective method along with the seeding technique become suitable for adaptive protection coordination strategy. The proposal has been tested on the modified IEEE 14 and 30 bus systems. And results have shown that coordination is achieved.

An assessment of the thermal refurbishment of an outpatient medical center in a tropical location, such as the City of San Francisco de Campeche, was presented with the aim to diminish its energy consumption. A year-long energy audit of the facility was conducted to formulate and validate a numerical simulation model while scrutinizing enhancement strategies. The examined improvement alternatives encompass passive adjustments to the roof (utilizing insulating materials, applying reflective coatings, and installing a green roof), modifications to active systems incorporating inverter technology, and alterations to the walls via reflective paint. The outcomes of the simulated enhancement scenarios were assessed utilizing energy, environmental, and economic metrics: key performance index (KPI), equivalent CO₂ emission index (CEI), and net savings (NS). These results were subsequently juxtaposed against TOPSIS decision-making algorithms to ascertain the alternative that optimally balances the three options. It was identified that using reflective paint on the roof provides the best energy benefits and contributes to mitigating emissions from electricity use. Furthermore, combining this passive technology with the integration of inverter air conditioning systems offers the best economic return at the end of 15 years. For its part, the TOPSIS method indicated that by prioritizing the financial aspect, the reflective coating on the roof combined with inverter air conditioning is enough. However, adding a wall with insulating paint brings environmental and energy benefits. The results of this work serve as a starting point for the analysis of other post-occupied buildings in the region and others under tropical climatic conditions.