Seawater Reverse Osmosis Desalination Plant Research Articles

Integrated stratigraphical, hydrogeochemical, and geophysical studies to characterize the shallow groundwater aquifers in Wadi Araba area, western Gulf of Suez, Egypt

The construction of the New Galala City besides great mining (e.g., konoozmisr) and Seawater Reverse Osmosis Desalination Plant projects in the semiarid Gulf of Suez region of Egypt increases the demand for groundwater resources. So, the current research provides integrated stratigraphical, hydrogeochemical, and geophysical studies to investigate the shallow groundwater aquifers in Wadi Araba area on the western side of the Gulf of Suez. The stratigraphic column starts with pre-Cambrian basement rocks which are non-conformably overlain by sedimentary succession of Phanerozoic Erathem. A detailed land magnetic profile has been conducted and processed to estimate the aquifer’s geometrical parameters. This includes the subsurface spatial extension and thickness to delineate the prevailed subsurface structures in the study area. Lithostratigraphically, these aquifers are represented by the Paleozoic- lower Cretaceous siliciclastic-dominated sediments of the Nubia Group and fractured carbonate-dominated facies of the upper Cretaceous Galala Formation. Lithological characters, sedimentary facies (fluvial to shallow and open marine), microfacies types, and diagenesis processes (e.g., compaction, cementation, dissolution, and fracturing) are the main factors that affect the quality of the shallow aquifers in the study area. The main microfacies of the studied aquifers are quartz arenite, subarkose, sublitharenite, mudstone/wackestone, and packstone/grainstone. These facies are characterized by different primary and secondary porosities. According to the water sampling standard methods, nineteen groundwater samples were collected from the available hand-dug wells and springs from the Nubian sandstone aquifer and the Upper Cretaceous aquifer, respectively. Inductively coupled plasma–mass spectrometry (ICP–MS), titration, spectrophotometer and a flame photometer were used to obtain a complete chemical analysis. The results of hydrochemical analyses indicated that total dissolved solids (TDS) and concentrations of major ions as well in the lower Cretaceous aquifer increase toward the Gulf of Suez and in general higher than that of springs of the Upper Cretaceous Aquifer. The predominant factors influencing groundwater chemistry include seawater intrusion, evaporation, mineral alteration, dissolution of fossils, and ion exchange. Groundwater in the study area is unsuitable for drinking except in one sample and moderately suitable for irrigation with caution for higher salinity in samples located near the Gulf of Suez.

Harnessing solar and wind power for sustainable seawater desalination: A multi-criteria geospatial suitability analysis

Water and energy sustainability are major concerns of the world's nations at present. This research introduces a geographical decision-making model for strategically selecting optimal locations for seawater reverse-osmosis desalination plants (SWRODPs). Furthermore, it assesses the best electrification approach, considering onshore wind turbine (WT) or solar photovoltaic (PV) power plants. A representative case-study of the Egyptian Red Sea Coast Region (ERSCR) is considered to validate the proposed model. The study delineates nineteen assessment criteria for building an informed selection of SWRODPs' potential locations. Seven experts with at least ten years of expertise in desalination and renewable technologies were selected to obtain accurate assessment criteria that imitate the real-life selection process. The group best-worth method (GBWM) was employed to ascertain optimal weights for the geospatial model criteria. The findings indicate that a mere 6.11 % of the total land area is deemed suitable, with the remaining 93.89 % classified as restricted. The suitable area is divided into different suitability classes in which about 65.85 % of the suitable area is found good for establishing the SWRODPs, while about 23.65 % of suitable land is found of moderate suitability. Besides, about 9.21 % and 0.03 % of suitable lands are considered very good and excellent suitability for implementing SWRODPs' projects. Moreover, the analysis pinpointed 8 % of the ERSCR (∼12,810 km2) as a highly suitable area for PV installation, predominantly within Qusir, Ras Sidr, Hurghada, and Ataqa districts. Concurrently, a scant 0.15 % (∼244 km2) is optimal for WT in the Qusir district. Further, the results offer proposals to the authorities and energy investors with about 50,200 km2 and 39,858 km2 of the ERSCR suitable for establishing SWRODPs powered by PV and WT, respectively. Overall, the research findings are anticipated to bolster the UN's sustainable development goals 6 and 7 and align with Egypt's Vision 2030.

ANN based-model for estimating the boron permeability coefficient as boric acid in SWRO desalination plants using ensemble-based machine learning

This study examines the relationship between input conditions and the prediction of boron rejection in full-scale seawater reverse osmosis (SWRO) desalination plants using ensemble-based machine learning. While reverse osmosis is the dominant desalination technology, limited research has focused on analyzing plant performance under actual operating conditions. To address this gap, we developed and implemented machine learning algorithms to forecast boron permeability coefficient values, which are indicative of boron rejection concentrations in the permeate. Our analysis utilizes data from a SWRO desalination plant in southeast Spain, examining various input variables and their influence on the prediction of these parameters. The results demonstrate that our ensemble-based machine learning approach can predict boron permeability coefficient values with a reasonable margin of error of 1 mgL−1, as evidenced by mean average error (MAE) and mean absolute percentage error (MAPE) values of 7.93·10–8 and 11.8 %, respectively. In conclusion, an innovative application of artificial intelligence algorithms in the field of water purification under real operational conditions has been introduced, thus introducing valuable insights into the use of machine learning algorithms for forecasting boron rejection concentrations in full-scale SWRO desalination plants. The findings lay the foundation for future researches exploring automated and deep-learning methods in water purification.

A comprehensive evaluation of the temporal and spatial fouling characteristics of RO membranes in a full-scale seawater desalination plant

The fouling of seawater reverse osmosis (SWRO) membranes remains a persistent challenge in desalination. Previous research has focused mainly on fouling separately; however, organic, inorganic, and biofouling can coexist and influence each other. Hence, in-depth study of the spatiotemporal changes in actual combined fouling in full-scale seawater desalination will provide more effective information for fouling investigation and control. In this study, we monitored (i) the operational performance of a full-scale desalination plant for 7 years and (ii) the development and characterization of membrane and spacer fouling at different locations of spiral-wound membrane modules sampled after 2.5-, 3.5-, and 7-year operation. The findings showed that (i) operational performance indicators declined with time (normalized flux 40 % reduction, salt rejection 2 % in 7 years), with a limited effect of the 20-day cleaning frequency, (ii) fouling accumulation in the membrane module mainly occurred at the feed side of the lead module and the microbial community in these area exhibited the highest diversity, (iii) the dominant microbial OTUs belonged mainly to Proteobacteria (43–70 %), followed by Bacteroidetes (10–11 %), (iv) Phylogenetic molecular ecological networks and Spearman correlation analysis revealed that Chloroflexi (Anaerolineae) and Planctomycetes were keystone species in maintaining the community structure and biofilm maturation and significantly impacted the foulant content on the SWRO membrane, even with low abundance, and that (v) fouling accumulation was composed of polysaccharides, soluble microbial products, marine humic acid-like substances, and inorganic Ca/Fe/Mg/Si dominate the fouling layer of both the membrane and spacer. Overall, variation partitioning analysis quantitatively describes the increasing contribution of biofouling over time. Ultimately, the organic‒inorganic-biofouling interaction (70 %) significantly contributed to the overall fouling of the membrane after 7 years of operation. These results can be used to develop more targeted fouling control strategies to optimize SWRO desalination plant design and operation.

Polyelectrolyte multilayers modification of nanofiltration membranes to improve selective separation of mono- and multivalent cations in seawater brine

Nowadays, brine produced in the Reverse Osmosis (RO) seawater desalination plants is a significant and largely untapped source of critical minerals and metals, which is usually discharged into the seas as wastewater. As a front face stage in the brine mining process, nanofiltration (NF) membranes can be used to separate brine stream into monovalent and multivalent ion-rich streams. Since high separation factors are required in seawater RO brine, polyelectrolyte multilayers with Layer-by-Layer (LbL) technique were used in this study to modify commercial polyamide NF membranes and improve their performance. Two common polyelectrolytes, poly(diallyldimethylammonium chloride) (PDADMAC) and poly(sodium 4-styrenesulfonate) (PSS) were coated onto two poly-piperazine polyamide NF membranes (NF270 and Desal-5 DL). The effects of the bilayers number and the outer layer charge on membranes’ performance were studied using two crossflow filtration setups with two different membrane sizes to find the membrane with the higher monovalent/multivalent separation factor. Desal-5 DL membrane coated with 5.5 bilayers provided the highest selectivity factors for mono/multivalent cations (> 21), the highest average rejection of multivalent cations group (about 95.7%) for short-term experiments. Another interesting result was the increase in water permeance of the Desal-5 DL membrane after it was coated with 5.5 bLs (indicating more than 20% improvement in pure water permeance). In addition, the stability test with brines at 20 bar showed that this membrane was stable over an extended period of filtration (22 hours) with an even higher selectivity factor of 34 and multivalent cations rejection of 97.7% on average.

Optimization of sustainable seawater desalination: Modeling renewable energy integration and energy storage concepts

Many arid and semi-arid regions of the world face growing freshwater scarcity, requiring increased utilization of seawater desalination to augment the existing freshwater resources. Seawater reverse osmosis (RO) is currently one of the most deployed technologies, due to its electrical energy efficiency and comparatively low costs. However, the required energy for desalination processes is often still converted from fossil sources. Given the growing demand for seawater desalination and the energy sector’s parallel decarbonization, the substitution by renewable energy sources (RES) is a critical issue. The volatility, lower availability of renewable energy, and cost for required electrical energy storage (EES) are all obstacles to the decarbonization of large-scale desalination plants and may affect production volume and water production costs negatively.This paper presents a mathematical model to determine a cost-optimal energy conversion and EES mix for the design and operation of large-scale seawater RO desalination plants. The linear program ensures satisfaction of the plant’s energetic demands. Furthermore, the model allows to investigate the general feasibility of integrating RES into large-scale desalination processes, which are examined by means of a case study while employing location-specific weather data. Different types of energy conversion technologies and the effect of EES on operating behavior, greenhouse gas emissions, and water unit costs are investigated. Specifically, the indirect storage of electrical energy via the smart management of a desalination plant’s oversized RO membranes is examined and compared to battery energy storage (BES).Results indicate that RES cannot meet an RO desalination plant’s full and constant electrical load demand without a high BES capacity, which is probably not feasible from a technical and economic point of view. The economic penalty from energy storage costs on one unit of desalinated water ranges from 3.10 $/m3 up to 5.38 $/m3. However, operating an oversized RO desalination plant intermittently could reduce the energy-related costs substantially and potentially provide a more appropriate way of adapting to a volatile supply of energy from renewable sources in order to decarbonize the desalination processes. Specific emissions of desalinated water can be reduced from 1.5 kg CO2 eq./m3 when relying mostly on combined cycle gas turbines down to 0.124 kg CO2 eq./m3 by intermittent operation and fully relying on renewable energy sources.

Pilot study of emerging low-energy seawater reverse osmosis desalination technologies for high-salinity, high-temperature, and high-turbidity seawater

The increasing impact of climate change has worsened drought conditions, leading to a surge in the demand for seawater desalination. However, current seawater reverse osmosis (SWRO) desalination technologies are not energy-efficient for handling the high-salinity, high-temperature, and high-turbidity seawater found in the Arabian Gulf. Therefore, a pilot-scale SWRO desalination plant was established to evaluate the new desalination technologies. The pilot plant tested high-performance SWRO membranes, meshed tube filtration (MTF) as a low-energy pretreatment for the high turbidity induced by algal blooms, and membrane capacitive deionization (MCDI) to improve permeate quality. The high-performance SWRO membrane demonstrated exceptional salt rejection and produced permeate quality in the range of 250–455 mg/L from the feed with salinities of 47,500–53,500 mg/L. MTF was effective in controlling turbidity, and the energy consumption was reduced by 77 % compared to the existing pretreatment process. Furthermore, MCDI exhibited similar levels of energy efficiency as brackish water reverse osmosis and may have the potential for future deployment by enhancing process development. Based on the pilot plant results, it is expected that a 100,000–200,000 m3/d SWRO desalination plant will have a specific energy consumption of 3.11–3.13 kWh/m3 for final product water quality at or below 200 mg/L.

Forecasting of Permeate Conductivity using MLR and ANN Methods of Boujdour Seawater Reverse Osmosis Desalination Plant

Background: For many years, seawater desalination technique has been operational to deal with water scarcity. In Boujdour region, located near the Atlantic Ocean southwest of Morocco, most water drinking is produced by a reverse osmosis seawater desalination plant. The permeate conductivity prediction is used to evaluate the performance of desalination plants. Objective: The present paper focuses on the modeling and comparison of the Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) for the prediction of permeate conductivity for a one-year period. Methods: Six input variables are considered, including turbidity, temperature, pH, feed conductivity, feed flow, and transmembrane pressure (TMP). Firstly, the MLR identifies the most important variables influencing the permeate conductivity with the aim of developing a regression model for the dependent and independent parameters. Secondly, the ANN method is examined to analyze the performance of desalination plant. A study of the effect of the number of neurons and the number of hidden layers on the efficiency of the neural network has been made. Results and Conclusion: Results confirm that the MLR and ANN models forecast the permeate conductivity with a suitable coordination coefficient of the real and predicted values. ANN model has been successfully tested for reliability with a correlation coefficient R2 of 99.097% and a mean square error (MSE) of 0.002607.

Selective lithium separation from desalination concentrates via the synergy of extractant mixtures

Seawater reverse osmosis (SWRO) desalination plants generate high volumes of concentrates, which contain, in addition to major salts, some elements of growing interest in minor concentrations. This is the case of lithium, highly demanded in the battery industry. In this work, the separation of Li+ from model SWRO brines has been evaluated by obtaining Li+ extraction curves with the combination of extractants DBM•TOPO and FDOD•TOPO, proving that both mixtures are capable of extracting Li+ under basic pH conditions, due to the keto-enolic tautomerism of the β-diketones. Li+ extraction values of 95.4 % for DBM•TOPO (pH = 12.2) and 100 % for FDOD•TOPO (pH = 9.0) were achieved. This behaviour was verified by the FT-IR analysis of the sample before and after the Li+ extraction. Finally, the selective separation of Li+ against other cations, such as Na+, K+, Mg2+, Ca2+ and Sr2+, present in the model brines at higher concentrations, was determined. Under mentioned experimental conditions, these cations are not extracted, reaching to Li+ selective separation close to 100 %. This study shows the first results on the selective extraction of lithium in complex SWRO brines, fostered through promising extractants mixtures showing a synergic effect towards Li+ in such multicomponent matrices.

Energy Efficiency Optimization in Onboard SWRO Desalination Plants Based on a Genetic Neuro-Fuzzy System

This work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) on board a marine vessel. This investigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.

A novel IEF-DLNN and multi-objective based optimizing control strategy for seawater reverse osmosis desalination plant

Over the past years, Seawater Desalination (SWD) has been enhanced regularly. In this desalination process, numerous technologies are available. The Reverse Osmosis (RO) process, which requires effectual control strategies, is the most commercially-dominant technology. Therefore, for SWD, a novel Interpolation and Exponential Function-centered Deep Learning Neural Network (IEF-DLNN) and multi-objective-based optimizing control system has been proposed in this research methodology. Initially, the input data are gathered; then, to control the desalination process, an optimal control technique has been utilized by employing Probability-centric Dove Swarm Optimization-Proportional Integral Derivative (PDSO-PID). The attributes of permeate are extracted before entering the RO process; after that, by utilizing the IEF-DLNN, the trajectory is predicted. For optimal selection, the extracted attributes are deemed if the trajectory is present, or else to mitigate energy consumption along with cost, the RO Desalination (ROD) is performed. In an experimental evaluation, regarding certain performance metrics, the proposed model's performance is analogized with the prevailing methodologies. The outcomes demonstrated that the proposed system achieved better performance.

Comparison of liquid ferrate and ferric chloride coagulants for humic acid removal in a seawater reverse osmosis desalination plant

Comparison of liquid ferrate and ferric chloride coagulants for humic acid removal in a seawater reverse osmosis desalination plant

A proposed safe design of the reverse osmosis system

In a seawater reverse osmosis (SWRO) desalination plant, the SWRO system includes the high-pressure pump, the high-pressure piping, the energy recovery equipment, the pressure vessels and the RO membranes. The membranes are the most delicate part of the plant and are subject to continuous operational variations during water production. Designers of plants propose various solutions to protect the RO system through the use of mechanical and control/automation devices. This paper aims to present several design and operational considerations and address them through a proposed technical solution. With the correct combination of instruments, the RO membranes are protected and the overpressure in the system can only happen due to malfunction or failure of the instruments.

ANALYSIS AND FEASIBILITY OF CHEMICAL PRODUCTS REDUCTION IN THE CLEAN IN PLACE OF ULTRAFILTRATION AS A PRE-TREATMENT TECHNOLOGY FOR REVERSE OSMOSIS DESALINATION

The reverse osmosis seawater desalination plants open-intake requires different strategies of pre-treatment to reduce the biofouling and scaling. The UltraFiltration (UF) technology is a recent application to this process. In this work, some alternatives to chemical products reducing in chemically enhanced backwash (CEB) and clean in place (CIP) of a UF rack have been studied. Mainly the sodium hypochlorite consumption, due to its biofouling precursor effect over reverse osmosis membranes. For this purpose, the optimal filtration time has been studied, to get the highest water production prior to the CIP, as well as some modifications in the conventional CIP's, modifying the duration of the stages of the same. The results were compared with the current mode of daily operation of the CEB. The results show that a reduction of up to 60% in the amount of sodium hypochlorite per cubic meter of water produced employed in UF CEB's, mini CIP's and CIP's can be achieved. However, the consumption of the rest of chemical dosing increased notably, and therefore the operating cost of UF also increased. In addition, there was an increase of desalted water consumption to the chemical products removed, up to almost 95,84 %, in comparison with the currently operational mode of CEB. On the other hand, operating the UF plant in the manner proposed requires a automatization of the process and expert staff to programme the control. Therefore, based on the results obtained, the alternatives proposed could reduce the chemical products in use, but it is not conclusive in terms of exploitation operational costs. Key Words: Ultrafiltration, Reverse osmosis, Open-intake, Clean in place, Chemically Enhanced Backwash, chemical products reduction, biofouling, pre-treatment.

Fouling control in SWRO desalination during harmful algal blooms: A historical review and future developments

Harmful algal blooms (HABs) are a major barrier to the stable and efficient operation of seawater reverse osmosis (SWRO) desalination plants. Although the intensity varies regionally, the occurrence of HABs impairs plant operation through severe particulate, organic, and biological fouling of both pretreatment and RO systems. As a result, considerable effort has been put into developing and optimizing pre-treatment techniques to mitigate these problems. This study reviews the historical changes and current status of pretreatment applications based on >110 datasets for large SWRO desalination plants. Chronological analysis underscores the increasing trend in the operation of dissolved air flotation and ultrafiltration systems since severe HABs in the Middle East from 2008 to 2009. The impact of HAB characteristics on system performance was also analyzed, and the efficiency of current pretreatment systems for the removal of HABs was evaluated, along with proposals for operational guidelines. Finally, future strategies for i) intelligent monitoring and prediction of HABs, ii) improvement of unit processes for the removal of algal organic matter, and iii) utilization of algal biomass to alleviate environmental impact were systematically delineated for smarter, safer, and greener operation of future SWRO desalination plants in response to the occurrence of HABs.

Energy and water without carbon: Integrated desalination and nuclear power at Diablo Canyon

A seawater reverse osmosis (SWRO) desalination plant collocated with an existing nuclear plant would have low electricity costs, could share the power plant’s seawater intake and outfall, and would have zero carbon footprint during operation. Unlike thermal desalination technologies, electrically-driven SWRO is ideal for retrofitting existing power plants because the turbines and condensers would not need expensive modifications. Here, we evaluate the techno-economic feasibility of collocating a large-scale SWRO plant with an existing nuclear power plant, specifically the 2.2 GWe Diablo Canyon Nuclear Power Plant on California’s central coast. The seawater that cools the nuclear plant’s condensers provides the feed water for desalination. The desalination brine is diluted with the remaining condenser coolant before being discharged to the ocean. A brushed-screen intake structure, serving both the nuclear power plant and the desalination plant, can comply with strict California regulations protecting marine organisms. This coproduction arrangement has a significant cost advantage relative to a stand-alone desalination plant. The levelized cost of water (LCOW) ranges from US$0.77 to US$0.98 per m3 of fresh water, with water distribution to offtakers adding US$0.02 to US$0.21 per m3 over 20–185 km. In comparison, California’s largest desalination plant, in Carlsbad, has an LCOW of about US$1.84 per m3. These cost savings result from reduced power costs (about US$0.054 per kWh) and from sharing some expensive infrastructure. Further, nuclear electricity allows a Carlsbad-size SWRO to avoid 47 kt/y of CO2 emissions relative to grid electricity. Examination of substantially larger desalination plants introduces additional considerations. This study is the first to show that collocated SWRO and nuclear power are strongly coupled and have a significant economic advantage over seawater desalination at other sites. These benefits should apply to dozens of existing nuclear power plants worldwide.

Advanced coagulation with liquid ferrate as SWRO desalination pretreatment during severe algal bloom. Process performance, environmental impact, and cost analysis

Harmful algal bloom (HABs) events represent a major operational challenge for seawater reverse osmosis (SWRO) desalination plants, leading to severe membrane fouling, increased chemical consumption and plant shutdowns. Current pretreatment practice applying conventional coagulation, flocculation, and sedimentation (CFS) with ferric chloride has shown limited capability in reducing seawater fouling potential during HABs events. The use of in-situ generated liquid ferrate (Fe(VI)) has recently been proposed for CFS pretreatment due to its capability of acting simultaneously as a coagulant, oxidant, and disinfectant. In this study, the use of ferric chloride (conventional coagulation) was compared to liquid ferrate (advanced coagulation) during HABs events, in terms of process performance, life-cycle assessment (LCA) and cost analysis. Results show that a 10 times lower concentration of Fe salt was required in advanced coagulation compared to conventional coagulation to achieve a similar performance in terms of turbidity and TOC removal. Using liquid ferrate also resulted in a higher total ATP removal (>99%) and lower dissolved Fe concentration. The advanced coagulation reduced dry sludge production by 88%, resulting in a significant decrease in environmental impacts and operational costs.

Can Aggregate-Associated Organisms Influence the Fouling in a SWRO Desalination Plant?

This pilot study investigates the formation of aggregates within a desalination plant, before and after pre-treatment, as well as their potential impact on fouling. The objective is to provide an understanding of the biofouling potential of the feed water within a seawater reverse osmosis (SWRO) desalination plant, due to the limited removal of fouling precursors. The 16S and 18S rRNA was extracted from the water samples, and the aggregates and sequenced. Pre-treatment systems, within the plant remove < 5 µm precursors and organisms; however, smaller size particles progress through the plant, allowing for the formation of aggregates. These become hot spots for microbes, due to their nutrient gradients, facilitating the formation of niche environments, supporting the proliferation of those organisms. Aggregate-associated organisms are consistent with those identified on fouled SWRO membranes. This study examines, for the first time, the factors supporting the formation of aggregates within a desalination system, as well as their microbial communities and biofouling potential.

Characterization of the water mass dynamic changes surrounding a seawater reverse osmosis desalination plant on the east coast of the Kingdom of Bahrain

Characterization of the water mass dynamic changes surrounding a seawater reverse osmosis desalination plant on the east coast of the Kingdom of Bahrain

A MILP-based operational decision-making methodology for demand-side management applied to desalinated water supply systems supported by a solar photovoltaic plant: A case study in agricultural industry

In the field of water management, desalination industry has faced various economic and environmental challenges. Renewable energies and the incorporation of operational strategies such as demand-side management have been able to contribute with the aim of facing them. Nonetheless, it is necessary to continue studying demand-side management for water supply systems emphasising it as a strategic tool to make operational decisions. This article presents a methodology based on a novel Mixed-Integer Linear Programming model in order to program the operation of a seawater reverse osmosis desalination plant with one pumping station for a desertic remote agricultural zone, in accordance with the principles of demand-side management. A photovoltaic solar plant connected to the grid is considered as a renewable energy source. The mathematical model aims to establish the optimal hourly operating load of the system that minimises the daily margin of purchased electricity costs minus sales income of generated electricity. The case study where the methodology is tested is an agricultural area in Northern Chile. The proposed methodology in this paper establishes the basis for future research and industrial applications, considering that it can be generalised to other geographical situations, as well as being modifiable to be adapted for more complex water supply systems and/or other renewable energy sources.