Sistemas híbridos con base en las energías renovables para el suministro de energía a plantas desaladoras / Hybrid systems with base in the renewable energy for the energy supply to desalination plants.

En el siguiente trabajo se modelan los sistemas híbridos con base en las energías renovables, quegaranticen las necesidades energéticas en plantas desaladoras de ósmosis inversa, con unacapacidad de hasta 50 m3 de producción diaria, a fin de obtener la combinación óptima. Para elprocesamiento de los datos se hará uso del software especializado HOMER. Se tomarán comoelementos de partida: la demanda eléctrica de una planta desaladora tipo, las especificacionestécnicas de los equipos propuestos, así como los potenciales de radiación solar y las velocidades deviento de la región analizada (Islas Canarias).Las conclusiones muestran que el sistema híbrido óptimo, desde el punto de vista técnico-económicopara el suministro de energía a desaladoras de ósmosis inversa con capacidad de producción de 50m3/día, será un sistema eólico- diesel, compuesto por: dos aerogeneradores, un banco de baterías yun generador diesel. Se demuestra que la velocidad del viento es la variable termodinámicadeterminante para la configuración de los sistemas híbridos estudiados, considerando los potencialesenergéticos naturales existentes en la región estudiada.Palabras claves: desalinización, ósmosis inversa, HOMER, Islas Canarias, sistemas híbridos, energíasrenovables._____________________________________________________________________AbstractIn the following work the hybrid systems with base in the renewable energy are modeled, to comparemany different design options based on their technical and economic merits. The energy necessitieswill be guaranteed in reverse osmosis desalination plants, with a capacity of up to 50 m3 of dailyproduction. The data processing was analyzed using the computer model, HOMER. The departureelements were: the electric demand of the desalination plant, the technical specifications of theequipments, as well as the potentials of solar radiation and the speeds of wind of the analyzed region(Canary Island).The conclusions show that the best hybrid system, from the technician-economic point of view for theenergy supply to a reverse osmosis desalination plants with 50 m3/día of capacity, will be an (eolicdiesel)system, composed by: two wind generators, a batteries bank and a diesel generator. It isdemonstrated that the wind speed is the determinant thermodynamic variable for the configuration ofthe analyzed hybrid systems, considering the existent natural energy potentials in the studied region.Key words:desalination, reverse osmosis, HOMER, Canary Islands, hybrid systems, renewable energy.</p

Machine Learning Models Applied to Manage the Operation of a Simple SWRO Desalination Plant and Its Application in Marine Vessels

In this work, two machine learning techniques, specifically decision trees (DTs) and support vector machines (SVMs), were applied to optimize the performance of a seawater reverse osmosis (SWRO) desalination plant with a capacity of 100 m3 per day. The input variables to the system were seawater pH, seawater conductivity, and three requirements: permeate flow rate, permeate conductivity, and total energy consumed by the desalination plant. These requirements were decided based on a cost function that prioritizes the water needs in a vessel and the maximum possible energy savings. The intelligent system modifies the actuators of the plant: feed flow rate control and high-pressure pump (HPP) operating pressure. This tool is proposed for the optimal use of desalination plants in marine vessels. Although both machine learning techniques output satisfactory results, it was concluded that the DTs technique (HPP pressure: root mean square error (RMSE) = 0.0104; feed flow rate: RMSE = 0.0196) is more accurate than SVMs (HPP pressure: RMSE = 0.0918; feed flow rate: RMSE = 0.0198) based on the metrics used. The final objective of the paper is to extrapolate the implementation of this smart system to other shipboard desalination plants and optimize their performance