The majority of the life cycle costs (LCC) of a pump are related to the energy spent in pumping, with the rest being related to the purchase and maintenance of the equipment. Any optimizations in the energy efficiency of the pumps result in a considerable reduction of the total operational cost. The Fátima water supply system in Portugal was analyzed in order to minimize its operational energy costs. Different pump characteristic curves were analyzed and modeled in order to achieve the most efficient operation point. To determine the best daily pumping operational scheduling pattern, genetic algorithm (GA) optimization embedded in the modeling software was considered in contrast with a manual override (MO) approach. The main goal was to determine which pumps and what daily scheduling allowed the best economical solution. At the end of the analysis it was possible to reduce the original daily energy costs by 43.7%. This was achieved by introducing more appropriate pumps and by intelligent programming of their operation. Given the heuristic nature of GAs, different approaches were employed and the most common errors were pinpointed, whereby this investigation can be used as a reference for similar future developments.
An experimental comparison between two heat sinks systems has been performed. The area of the study is Guayaquil, Ecuador with an average annual temperature of 27 °C and an average annual relative humidity of 77% (UTM 0621517/09749485) where typical large HVAC systems with cooling towers are used. As a result of the high relative humidity in the area, the thermal efficiency of this type of heat exchanger is reduced. A geothermal heat exchanger cooling water using the constant and relatively low soil temperature is considered as a viable alternative for HVAC systems in this location. In this project, a prototype geothermal heat exchanger is built and experimentally compared with a cooling tower system. Through previous research, it was determined that the soil at this borehole consist of 5 % of landfill material; 86 % several strata of low plasticity silt, alternating silt; and 5 % sand. This location corresponds to the estuarine deposits of the Guayas River. The average soil temperature is 27 ° C, associated with a thermal conductivity of 1.87 W / m K and a thermal diffusivity of 0.085 m2 / day obtained from a Thermal Response Test of the soil. An experiment for the comparison of these two types of heat exchangers under a uniform heat load is designed and built. The cooling tower water installed has a capacity of 5 Tons of Refrigeration with a flow of 15 Gallons per minute. The geothermal heat exchanger consisting of four drilled to 42 meters deep vertical holes and connected in a parallel circuit. Both systems operate in periods of 8 and 12 hours during the hours of daylight. To simulate the thermal load in both cases, water is heated using two identical electric boilers with a nominal power of 9 kW each. Data from the energy consumption, and energy dissipation from each system is collected and analyzed. The Energy Efficiency Rating obtained for each system is on the order of 10.61 for the cooling tower water, and on the order of 14.78 for the geothermal heat exchanger, with savings of 61.7% in energy consumption and CO2 emissions by the system of geothermal cooling through better efficiency. We have also projected the costs of installation, operation and maintenance of both systems. Results suggest that despite the high cost of installation, a geothermal sink is a valid option for HVAC systems in cities or regions that have high temperatures and high humidity.
This research analyzes the tidal effect in the thermal properties of the ground for a case study in Guayaquil, Ecuador. A thermal response test (TRT) performed near the shore of the Guayas river presented periodic fluctuations in the thermal behavior concurrent with the tide cycle. First, an analytical solution for tide-induced water table fluctuations was used for the determination of the phreatic level for the days of the test. The analytical model accounted for the horizontal distance from the shore, the ground porosity, and permeability. Afterward, a geometric mean model was used to predict the thermal conductivity of soil considering the groundwater level fluctuations. Finally, a correlation between the effective thermal capacity of the ground and the phreatic level in the soil was found.
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