Carlos Armenta-Déu

This article analyzes the energy self-sufficiency in a paired house using a hybrid renewable energy system installed in one house and using the second house for a null energy balance. The article searches for sustainable systems reducing energy dependence on fossil fuels and greenhouse gas emissions. The study is based on the application of the fundamental equations of energy, thermal, and electrical balance for a domestic installation. This system integrates a domestic wind turbine and a photovoltaic array, assisted by a battery bank as an energy storage system to compensate for energy imbalances during a power outage. The proposed design relies exclusively on electricity to meet all thermal and electrical demands, including heating, domestic hot water, air conditioning, appliances, and lighting. The design employs an air source heat pump for domestic hot water, heating, and air conditioning; this unit directly connects to the hybrid renewable energy system, and the battery bank assists the hybrid system when needed. The battery is charged and discharged according to the daily energy balance. A simulation is performed under various operating conditions to evaluate the proposed design feasibility. The study includes experimental tests to verify the simulation’s validity and the reliability of the system design. Experimental tests show good agreement between simulation and actual performance, with an accuracy higher than 99% ( σ _ave = 2.126), and demonstrate the feasibility of energy self-sufficiency in housing with hybrid renewable energy sources. Sustainable energy installations require highly efficient systems to supply thermal energy, such as high-performance aerothermal heat pumps.

The rising pollution levels in congested urban areas pose a serious threat to human health. Many solutions have been proposed to control and reduce gas emissions from road traffic, with results that are not entirely satisfactory. The adoption of new techniques and methodologies for early detection of pollutant emissions may enable effective management and control of road traffic contamination. The proposed method introduces an interactive protocol that facilitates communication between the traffic control center and a vehicle speed recognition system. This protocol autonomously adjusts vehicle speeds to align with traffic control center limits, correlating maximum velocity with greenhouse gas (GHG) concentrations in designated urban areas. The paper examines the environmental impacts of road traffic emissions in urban areas and explores strategies to mitigate them through speed limit management based on pollution levels. To implement this strategy, we suggest installing pollution detection sensors and interactive speed signage. GHG mitigation hinges on specific sensors that measure emissions from vehicle exhaust pipes strategically positioned along roads or pedestrian walkways. The integration of Artificial Intelligence enhances the protocol’s effectiveness, reducing significant deviations in vehicle performance and associated emissions. Simulation results indicate a potential reduction in GHG emissions of 21.8% when vehicles operate at 45 km/h, following a 15 km/h decrease from typical velocities and maintaining no acceleration. Additionally, vehicle speed, the extent of speed reduction, and acceleration rates influence the reductions in GHG emissions, yielding reference emission reductions of 12.4% and 15.2% for average speeds of 70 km/h and 45 km/h, respectively. Conversely, the maximum increase in GHG emissions can reach 66.7% when experiencing an acceleration of 3.6 m/s2, with a 15 km/h speed reduction. Theoretical predictions have demonstrated a high accuracy of 98.5% for speeds exceeding 57.5 km/h, regardless of the engine type. However, this accuracy diminishes at lower speeds (below 55 km/h), ranging from 69.5% to 98.5%, depending on engine type and acceleration rate. The proposed methodology improves the current state of the art in managing pollution levels and helps achieve early control of urban contamination from road traffic.

The paper studies and analyzes electric vehicle engines powered by hydrogen under the WLTP standard driving protocol. The driving range extension is estimated using a specific protocol developed for FCEV compared with the standard value for battery electric vehicles. The driving range is extended by 10 km, averaging over the four protocols, with a maximum of 11.6 km for the FTP-75 and a minimum of 7.7 km for the WLTP. This driving range extension represents a 1.8% driving range improvement, on average. Applying the FCEV current weight, the driving range is extended to 18.9 km and 20.4 km, on average, when using power source energy capacity standards for BEVs and FCEVs.

The paper describes the conversion of carbon dioxide into methanol in a chemical reactor under standard operating conditions. Electro-analytical techniques, cyclic voltammetry, and chrono-amperometry characterize the process. The electrochemical redox reaction develops using various catalyzers to evaluate the performance of the carbon dioxide conversion into methanol process under variable chemical conditions. The results of the applied technique showed an incomplete redox reaction with an electronic change of z = 2.84 on average, below the ideal number, z = 6, that may be due to methanol decomposition (reverse reaction) because the system operates with a reaction constant above the equilibrium value. The methanol production may improve by draining the methanol/water solution from the chemical reactor to reduce the methanol concentration in the electrochemical cell, shifting the forward reaction towards the formation of methanol, increasing the electron change number, which approaches the ideal value, and improving the methanol production efficiency. The draining process shows a significant increase in methanol formation, which depends on the draining flow rate and the catalyzer type. A simulation process shows that if we operate in optimum conditions, with no methanol decomposition through a reverse reaction, the redox reaction fulfills the ideal condition of maximum electronic change. The experimental tests validate the simulation results, showing a relevant increase in the electron change number with values up to z = 4.2 for optimum draining flow rate conditions (0.2 L/s). The experimental results show a relative increase factor of 4.7 in methanol production, meaning we can produce more than four times more methanol compared with no draining techniques. The data analysis shows that the draining flow rate has a threshold of 0.2 L/s, beyond which the extent of the reaction reverses, reducing the methanol formation due to a chemical reaction disequilibrium. The paper concludes that using the draining method, the methanol production mass rate increases significantly from an average value of 20.9 kg/h for non-draining use, considering all catalyzer types, to a range between 91.9 kg/h and 104.3 kg/h, depending on the flow rate. Averaging all values for different flow rates and comparing with the non-draining case, we obtain an absolute methanol production mass rate of 77 kg/h, meaning an incremental percentage of 469.1%, more than four times the initial production. Although the proposed methodology looks promising, applying this procedure on an industrial scale may suffer from restrictions since the chemical reactions intervening in the methanol formation do not perform linearly. According to experimental tests, the best option among the six catalyzers used for methanol production is the plain copper, with copper oxides (Cu₂O, CuO) and copper Sulphur (CuS) as feasible alternatives.

This work proposes a new method to refill fuel cell electric vehicle hydrogen tanks from a storage system in hydrogen refueling stations. The new method uses the storage tanks in cascade to supply hydrogen to the refueling station dispensers. This method reduces the hydrogen compressor power requirement and the energy consumption for refilling the vehicle tank; therefore, the proposed alternative design for hydrogen refueling stations is feasible and compatible with low-intensity renewable energy sources like solar photovoltaic, wind farms, or micro-hydro plants. Additionally, the cascade method supplies higher pressure to the dispenser throughout the day, thus reducing the refueling time for specific vehicle driving ranges. The simulation shows that the energy saving using the cascade method achieves 9% to 45%, depending on the vehicle attendance. The hydrogen refueling station design supports a daily vehicle attendance of 9 to 36 with a complete refueling process coverage. The carried-out simulation proves that the vehicle tank achieves the maximum attainable pressure of 700 bars with a storage system of six tanks. The data analysis shows that the daily hourly hydrogen demand follows a sinusoidal function, providing a practical tool to predict the hydrogen demand for any vehicle attendance, allowing the planners and station designers to resize the elements to fulfill the new requirements. The proposed system is also applicable to hydrogen ICE vehicles.

The study aims to evaluate the progressive increase in energy systems pollutant emissions due to the efficiency loss and continuous deterioration in the energy conversion process. The paper analyzes the GHG, nitrous oxide, sulfur dioxide, and fine particle emissions from vehicles, residential and commercial heating systems, public buildings, health centers, and industrial conglomerates, with the servicing time and degradation level. The analysis applies to various emitting gases or small particle systems, which generate environmental impact or cause human health problems. The paper proposes a detection method based on an engineering system to determine the real emissions rate of an energy conversion system, establishing an obsolescence threshold beyond which the system requires a replacement or refurbishment to achieve an admissible pollutant emissions rate. The proposed engineering solution uses sensors that detect individual or collective pollutant-emitting sources like vehicles, heating exhaust pipes, or industrial chimneys. The engineering solution uses a control system to prevent excessive pollutant emissions by managing the operational process and adjusting parameters to maintain the pollutant emissions below a selected threshold. The study represents an advance in fighting against reaching the critical pollution level in urban and congested areas where the incidence of GHG, nitrogen oxides, fine particles (PM), and other contaminant elements is more relevant. The principal novelty of the present study is its adaptability to all types of combustion processes and emission rates, providing a powerful tool for pollutant emission managers. The study also represents a significant advance in managing the combustion process to regulate GHG emissions.

This paper focuses on determining the state of charge (SOC) of lithium-ion batteries when they are in operation and the influence that the state of health (SOH) has on SOC determination. The paper studies the effects of the discharge rate on battery performance and evaluation of the SOC. The paper also analyzes the influence of battery aging on the determination of SOC. The online determination of SOC in lithium-ion batteries uses the linear behavior of battery discharge and the influence of the discharge rate on the battery voltage slope. The paper describes a simple algorithm that relates the SOC of the battery with online battery voltage. The proposed measurement method uses a very short controlled discharge at a specific rate that avoids unexpected interferences with the current operation of the battery during states of charge or discharge. We conducted a simulation process to evaluate the evolution of the SOC in Li-ion batteries for different operating stages. Experimental tests validate the proposed methodology, showing a close agreement between theoretical values and experimental results with 98% accuracy. The paper also deals with determining the aging factor in lithium batteries as a critical parameter to calculate the SOC. The method determines the aging factor using a specific simulation for calculating the SOC. The paper compares the results with the values obtained in an experimental test showing high agreement (>93%). The proposed model applies to all lithium-ion batteries and validates for a wide range of battery state-of-health, up to 50%, and with accurate prediction, higher than 90%.

The growing demand for energy and the need to reduce dependence on non-renewable sources have driven the research and application of sustainable technologies. In this context, an integrated solution that combines distributed energy generation from renewable sources, such as wind and hydro, with efficient management of household energy consumption is proposed. This study focuses on the hybrid renewable energy system simulation analysis designed to meet the demand of an off-grid household in a self-consumption mode. This combination of technologies allows adaptation to geographical location, resource availability, and consumer-specific needs, where only renewable resources are available to power non-grid-connected local communities in less developed areas. Given that wind and hydroelectric energy are variable resources over time, either seasonally or hourly, the aim is to find an optimal balance that maximizes electricity demand coverage for the longest possible time. A system is designed to integrate both energy sources, with one acting as a backup source, if necessary, thus ensuring a constant supply of electricity without oversizing the systems. This approach aims to maximize energy efficiency and contributes to closing the electricity access gap in communities not connected to the conventional electricity grid. The detailed analysis of this hybrid system provides valuable information for designing and implementing decentralized energy solutions in isolated communities. The paper represents a unique contribution to the state of the art in wind energy and hydropower hybrid renewable energy systems for isolated communities. It represents an advanced study on managing this type of installation by applying energy efficiency protocols and methods to optimize the system’s performance.