• Energy Research

This paper presents a multi-criteria optimization formulation for the optimal design of a water-heating system for homes. The proposed model accounts for the available solar radiation in the specific place where the solar collector is installed and the hot water demands. The goal is to target economic and environmental objectives by optimizing the design and operating conditions including the optimal hot water storage and distribution. The proposed model is applied to several scenarios for homes with different inhabitants and in various cities in Mexico. The results show that the location has significant effects on the optimal design and operation of the water-heating solar system.

The availability, accessibility, and sustainability of resources can enhance or jeopardize the security of meeting human needs for water, energy, and food in several regions of the world. For this reason, it is crucial to propose strategies that allow quantifying the current situation of resource security and preventing alarming scenarios in the future. The objective of this paper is to assess the current condition of food, energy, and water security of a region with rampant economic development, but struggling with natural resources as a result of its adverse climatic conditions. An approach for assessing the water–energy–food security in arid or semiarid areas is presented through different scenarios considering the availability, accessibility, and sustainability of the involved resources. The proposed approach is applied in the State of Nuevo Leon in Mexico, which is the second-most important state regarding contribution to the national Gross Domestic Product. Nevertheless, the rapid increase in its population and the semiarid climate condition with precedents of natural catastrophes jeopardize the continuity of its development. Results show that the state may not be able to meet the demands of water and food due to the stress generated on its resources. In contrast, the energy situation is more promising with the implementation of energy from renewable sources. The analysis is carried out over a past time period and making projections until 2030, providing a tool to be able to make decisions in the medium and long term. The main goal is to propose preventive measures and to ensure sustainable planning covering economic, social, and environmental needs without compromising the well-being of future generations. In this sense, the implementation of new policies for the water sector is analyzed, with the aim of reducing domestic and agricultural consumption, targeting improvements in the evaluated indices.

Abstract This work presents a mathematical model for the strategic planning of the energy supply chain accounting for fossil fuels and biofuels. The proposed model considers the fuel extraction, production, processing, and distribution to the consumer, as well as the interaction with forest plantations to capture emissions generated in the whole process. Matching law is incorporated to predict, control and understand the situation under study. People's behavior has been included to determine their preference for deciding whether to install a refinery or a biorefinery. The decision is influenced by economic factors such as emissions taxation. The proposed approach was applied to a case study in Mexico, where the profit of the whole system, generated emissions, and jobs are considered. Results show that by implementing matching law it is possible to promote biofuels production together with fossil fuels, as well as to determine the preferences in the system.

A mixed-integer nonlinear programming (MINLP) algorithm for the synthesis of cooling networks is presented. As opposed to previous models in which the minimization of utility consumption has been formulated, the algorithm considers simultaneously the capital cost for the coolers and the utility costs. The strategy is based on a superstructure that allows bypass and splitting of utility streams. Also, the superstructure considers a combination of arrangements in series and in parallel that allows for an efficient use of cooling streams. The typical arrangement of cooling networks in parallel usually conducts to higher total costs. Also, it is shown that the use of minimum amounts of cold utilities does not necessarily conduct to the minimum total cost. Three case studies are used to show the application of the proposed method.

The main problem related to the electricity generation planning is to ensure the total satisfaction of the demanded power along a period of time considering the population growth. Since the power demand is function of the growing population, there is a fast depletion of the environment caused mainly by the harmful emissions produced and the big amounts of water consumed in large power generation plants. Therefore, when a power supply system is planning, it is important to evaluate the negative outcomes that could be generated in the environment and to balance them with the economic performance of the system. In this work is presented an optimization approach for the strategic planning of electricity generation, the model seeks the optimal selection of technologies for the new power generation capacity (clean and conventional) which will satisfy the power demand in different scenarios in a specific period of time. The proposed multi-objective model is solved using the e-constraint method for determining a trade-off between economic, harmful emissions (CO2, NOx, SO2 and particle emissions), and water consumption through a set of Pareto diagrams. The power demand and the resources available for electricity generation in Mexico are presented as a case study, where it is possible to reduce up to 38.4% of emissions and 41.58% of water consumed, by minimizing these two factors, which has a significant environmental impact.

The unique properties of carbon nanotubes (CNTs) make them suitable for an incredible range of applications in materials science, electronics, energy management, and many other fields. CNTs can be manipulated chemically and physically in very useful ways, and their final properties and dimensions strongly depend on the parameters and the nature of the method used for their synthesis, this is why many methods of synthesis have been reported. Several key parameters and operating conditions have to be manipulated to produce CNTs with suitable properties for future applications, and it is evident that all these methods of synthesis need to be optimized. This paper presents an optimization approach for determining the best synthesis method and their corresponding operating conditions for synthesizing carbon nanotubes accounting for technical and economic issues as objective functions for a desired application. Proper correlations for the interaction between the considered variables are proposed, and these correlations are based on experimental data taken from literature. A case study considering three synthesis methods of carbon nanotubes (arc discharge, laser ablation, and chemical vapor deposition) is presented. The results indicate that the safest technology with the minimum cost and maximum efficiency was chemical vapor decomposition using turpentine as carbon source (with a cost of 0.374 USD/g, and 0.00088 % fatalities for exposure to 0.1 g of catalyst and 0.000006 % of fatalities per exposure to 4 g of carbon source during 8 min of processing).

The need to quantitatively measure the security of the water–energy–food (WEF) nexus sectors in a region is of great importance due to the vulnerability of each sector and the associated cost. This...

Abstract This study presents a mathematical programming approach for evaluating the exploitation and distribution of shale gas from potential reserves at a national level, depending upon existing infrastructure and water availability. The study describes an MILP model that simultaneously integrates water management with the design and planning of the supply chain, from basins to distribution markets and fresh water supply from available watersheds. The model is applied to a case based on the potential exploitation of shale gas basins in Mexico. The parameters of the model are mostly taken from the databases of the country, processed through the geographic information system ArcGIS. The solution provides the optimal decisions for exploitation and distribution, as well as for freshwater source selection and optimal wastewater management. Water management strategies include disposal, wastewater treatment in municipal plants and onsite treatment. The negative impact of water consumption of the optimal exploitation systems is assessed based mainly on the estimation of the water stress index. Results show that the shale gas exploitation would favor the energy independence of the country, but the availability of freshwater for some municipalities would be compromised.