Seawater Greenhouse Research Articles

Wind energy systems adapted to the seawater greenhouse desalination unit designed for arid coastal countries

The wind energy can be used to power the seawater greenhouse. The aim of this study is to present the feasibility of wind energy in the seawater greenhouse desalination unit. The seawater greenhouse combines fresh water production with growth of crops in a greenhouse system. The technique is adapted for farms in arid coastal regions that are suffering from salt infected soils and shortages of potable groundwater. The dimension of the greenhouse has the greatest effect on the water production and energy consumption. A wide shallow greenhouse (200 m wide by 50 m deep) has been found to give 297 litres per day of fresh water in only eight hours (between 09.00 and 17.00). The greenhouse produces 98 % of total fresh water. This interval corresponds to the higher winds period.

Seawater Greenhouse Equipped with a Novel Solar Humidification-Dehumidification Desalination Unit in MAKRAN Coast: Fabrication and Experimental Study

The purpose of this study is the fabrication and performance evaluation of a new type of solar humidification–dehumidification (HD) desalination unit to supply sufficient fresh water for a seawater greenhouse in the MAKRAN coast in southeast Iran. In the proposed design, a particular type of air-to-air condenser is used. The cold air coming out of the greenhouse ventilation system (fan and pad) in summer and the cold ambient air in winter is used to supply the required cooling of the system. In this way, when cold air passes over the pipes in air-to-air condensers, condensation of water vapor occurs in the moist air inside the pipes, and fresh water is produced. Greenhouse fans, which have an air flow rate of around 20,000 m3/hr, are used to create this air flow. By fabricating two condensers, each using 42 rows of PVC pipes with a diameter of 75 mm, it is possible to produce 400 L of fresh water per day in a 400 m2 greenhouse. The required heating is provided by the solar farm, which includes 96 square meters of flat plate collectors. The steps of unit fabrication are described in detail in this research. However, the effect of greenhouse air temperature and circulating seawater flow rate on freshwater production, energy consumption, and energy intensity are also investigated. By increasing the flow rate of circulating seawater and decreasing the greenhouse air temperature, the production rate of the system increases. When the hot seawater and greenhouse air temperature are 61.7 °C and 26 °C, respectively, the maximum instantaneous production is estimated to be 80 L/h. The energy intensity of the HD desalination unit is varied between 3192 and 4382 kJ/L, and the gain output ratio of the system is around 0.6. The proposed system can be easily paired with conventional greenhouses employing a fan and pad cooling system and produces around 1.25 (L/m2·day) fresh water.

The forecast of power consumption and freshwater generation in a solar-assisted seawater greenhouse system using a multi-layer perceptron neural network

This research is a simulation of the solar seawater greenhouse framework by using a hybrid model of multilayer perceptron neural network and different optimization algorithms. Four key factors, roof transparency, the front evaporator height, greenhouse length, and width, are considered decision-making variables to investigate power consumption and water production. In this regard, six metaheuristic approaches are employed to hyper-tune the learning process of the neural network. The accuracy of the proposed models is estimated via statistical indicators. The obtained results show that biogeography-based optimization and genetic algorithm had the minimum RMSE value for both power consumption and water generation. Based on these criteria, the ACO method has the worst rank. It should be mentioned that some data are training set and some others are employed for the testing procedure. According to the results, less testing error is related to BBO and GA methods. Water consumption assessment represents that the least error is related to ACO strategy. It is found that by change of width and transparency, more water production is related to ES and GA methods with almost 120 m3/day and 105 m3/day, respectively. Moreover, ES, ACO, and GA have less power consumption. Finally, it is found that when transparency was 0.4, the water production value could be 115 m3/day while for 0.6 of transparency this amount was 95.

Predicting freshwater production in seawater greenhouses using hybrid artificial neural network models

Freshwater production in seawater greenhouses (SWGH) is an important topic for decision-makers in arid lands. Since arid and semi-arid lands face water shortages, the use of SWGH helps farmers to supply water. This study proposed an integrated artificial neural network (ANN) model, namely, the ANN-antlion optimization algorithm (ANN-ALO), for predicting freshwater production in a seawater greenhouse. The width, length, and height of the evaporators and the roof transparency coefficient of the SWGH were used as the inputs of the models. The ability of ANN-ALO was benchmarked against the ANN-particle swarm optimization (ANN-PSO), ANN, and ANN-bat algorithms (ANN-BA). The novelties of the current study are the novel hybrid ANN models, the fuzzy reasoning concept for reducing the computational time, the comprehensive analysis of the uncertainty of the parameters and inputs, and the use of non-climate data. Comparing the models’ performances in the test phase demonstrated that the ANN-ALO model performed best, with a Root Mean Square Error (RMSE) value that was 18%, 33%, and 39% lower than that of the ANN-BA, ANN-PSO, and ANN models, respectively. For the ANN model, the percent bias (PBIAS) value in the training stage was 0.20, whereas for the ANN-BA, ANN-PSO, and ANN-ALO models, it was 0.14, 0.16, and 0.12, respectively. This study also indicated that the width of the seawater greenhouse was the most important parameter for predicting freshwater production.Furthermore, the results suggested that an evaporator height of 2 m resulted in the highest predicted freshwater production for all the widths except 200 m. The lowest freshwater production for different widths occurred at an evaporator height of 3 m. The generalized likelihood estimation for uncertainty analysis indicated that the uncertainty of the input parameters was lower than that of the model parameters.

Utilization of Radial Basis Function Neural Network model for Water production forecasting in Seawater Greenhouse units

The solar seawater greenhouse desalination is a plant that simulates the natural water cycle through seawater evaporation and condensation into freshwater. In the present work, the radial basis function neural network integrated with different optimization algorithms is presented to predict the water production capacity considering the effect of various parameters on the performance seawater greenhouse system. Different statistical metrics are employed to examine the performance of the proposed models. Also, in order to obtain a more satisfactory performance of water production forecasting in a seawater greenhouse, the effect of neurons’ numbers in the hidden layer of the proposed neural network is studied. According to the obtained results, the forecasting accuracy of the proposed radial basis function neural network optimized with the hybrid particle swarm optimization–gray wolf optimizer algorithm with nine neurons in the hidden layer with the correlation coefficient and coefficient of determination of 0.998 and 0.996 in training phase is much better than those of the other models. Also, the best values for the front greenhouse dimension are obtained as Width = 125 m, Length = 200 m, and Height = 4 m. Also, the roof transparency is obtained by 0.6.

Predicting freshwater production and energy consumption in a seawater greenhouse based on ensemble frameworks using optimized multi-layer perceptron

Water shortage in arid and semi-arid land is one of the most important challenges of decision-makers. The seawater greenhouse (SWG) is a useful solution for water supply in the agriculture sector. The optimal design of a SWG with lower consumption of energy and higher freshwater production is a real challenge for the decision-makers. This study used two ensemble models and multiple multi-layer perceptron (MLP) models based on non-climate data to predict freshwater production energy consumption in the SWG. The Copula Bayesian average model (CBMA) was used to develop the BMA model using different copula functions and distributions. In the first level, multiple MLP models using the dimension of SWG as inputs predicted freshwater and energy consumption in a SWG. In the next level, The CBMA and BMA were used to predict freshwater production and energy consumption. The uncertainty analysis of outputs, use of new models and non-climate data are the novelties of the current study. The results indicated that the CBMA decreased the mean absolute error (MAE) value of the BMA, MLP-SEOA, MLP-SCA, MLP-BA, MLP-PSO, and MLP models by 2.7%, 19%, 31%, 40%, 41%, and 42%, respectively for predicting freshwater production. The root mean square error (RMSE) of the CBMA was 40%, 49%, 56%, 57%, 62%, and 64% lower than those of the BMA, MLP-SEOA, MLP-SCA, MLP-BA, MLP-PSO, and MLP models, respectively for predicting energy consumption. The uncertainty analysis indicated that the CBMA and BMA provided the lowest uncertainty among other models. The current study results indicated that the use of ensemble models improved the accuracy of individual models for predicting energy consumption and freshwater production. The findings of the study indicated that the ensemble models using the dimension of SWGs as inputs successfully predicted energy consumption and freshwater production in a SWG.

Enhancement of freshwater production of the seawater greenhouse condenser

Seawater greenhouse (SWGH) is a technology established to overcome issues related to open field cultivation in arid areas, such as the high ambient temperature and the shortage of freshwater. It adopts the humidification-dehumidification concept where evaporated moisture from a saline water source is condensed to produce freshwater within the greenhouse body. Various condenser designs are adopted to increase freshwater production in order to meet the irrigation demand. The aim of this study was to experimentally investigate the practicality of using the packed-type direct contact condenser in the SWGH to produce more freshwater at low costs, simple design and high efficiency, and to explore the impact of the manipulating six operational variables (inlet air temperature of the humidifier, air mass flowrate of the humidifier, inlet water temperature of the humidifier, water mass flowrate of the humidifier, inlet water temperature of the dehumidifier and water mass flowrate of the dehumidifier) on freshwater condensation rate. For this purpose, a direct contact condenser was designed and manufactured. Sixty-four full factorial experiments were conducted to study the effect of the six operational variables. Each variable was operated at two levels (high and low flowrate), and each experiment lasted for 10 min and followed by a 30-min waiting time. Results showed that freshwater production varied between 0.257 and 2.590 L for every 10 min. When using Minitab statistical software to investigate the significant variables that contributed to the maximum freshwater production, it was found that the inlet air temperature of the humidifier had the greatest influence, followed by the inlet water temperature of the humidifier; the former had a negative impact while the latter had a positive impact on freshwater production. The response optimizer tool revealed that the optimal combination of variables contributed to maximize freshwater production when all variables were in the high mode and the inlet air temperature of the humidifier was in the low mode. The comparison between the old plastic condenser and the new proposed direct contact condenser showed that the latter can produce 75.9 times more freshwater at the same condenser volume.

Modeling of Seawater Greenhouse by a block diagram environment program and an equations solver program and simulations on different Moroccan locations

Modeling of Seawater Greenhouse by a block diagram environment program and an equations solver program and simulations on different Moroccan locations

Prediction of power consumption and water productivity of seawater greenhouse system using random vector functional link network integrated with artificial ecosystem-based optimization

The seawater greenhouse desalination technology is a kind of desalination plant which simulates the water cycle through seawater evaporation and condensation into freshwater. A novel random vector functional link (RVFL) network integrated with artificial ecosystem-based optimization (AEO) algorithm is proposed to predict the performance of the seawater greenhouse (SWGH) system. Power consumption and water productivity of the SWGH are predicted using the proposed RVFL-AEO model. The statistical analyses using different statistical criteria such as root mean square error, mean absolute error, mean relative error, efficiency coefficient, coefficient of determination, overall index, and coefficient of residual mass are also carried out to examine the efficiency of the proposed neural network. The statistical tools obtained a perfect match between the experimental and the proposed model results. The performance of the RVFL-AEO model is compared with that of the conventional RVFL model. RVFL-AEO showed a better performance compared with RVFL; which indicates the role of AEO in obtaining the optimal RVFL parameters that enhances the accuracy of the model.

Solar pond driven seawater greenhouse – simulations on different Moroccan locations

Solar pond driven seawater greenhouse – simulations on different Moroccan locations

Review on Seawater Greenhouse: Achievements and Future Development

Background: Seawater greenhouse (SWGH) is a technology established to overcome issues related to open field cultivation in arid areas like high temperatures and freshwater shortage. So far, five pilot Seawater greenhouses were built around the world; in Spain, United Arab Emirates, Oman, Australia and Somaliland. All the patents related to the Seawater greenhouse components and designs mentioned were reviewed. Methods:: The Seawater greenhouse adopts the humidification-dehumidification (HDH) concept where evaporated moisture from saline water source is condensed to produce freshwater within the greenhouse body. Many advancements have been made throughout the past 25 years to optimize the Seawater greenhouse by means of structural improvement, heat distribution, condenser design and material, source of feed water and the evaporator via both trial-and-error and simulation approaches. The latter included numerical, mathematical, analytical and artificial neural network simulations. Various condenser designs were adopted in order to increase freshwater production to meet the irrigation demand of the seawater greenhouse. Results and Conclusion: To make the Seawater greenhouse self-sufficient in terms of energy production, the use of renewable energies and nonconventional sources was also investigated like the use of geothermal, solar and wind energy to produce electricity for the greenhouse operation and for other requirements as well. The use of reverse osmosis along with reverse electro dialysis to produce freshwater and electricity in the seawater greenhouse, was also one of the ideas suggested to improve and solve the associated constraints. Direct contact dehumidification is another development suggested to improve the condensation rate. This new approach seems to be very promising as it involves low capital, operation and maintenance costs, high freshwater production, and fouling- and corrosion-free.

Artificial neural network simulation of the condenser of seawater greenhouse in Oman

The prediction of freshwater production from the condenser of an agricultural seawater greenhouse is important for designing the greenhouse process. Two models, namely, Artificial Neural Network and multilinear regression (denoted as ANN and RA, respectively), were developed and tested to predict the freshwater production rate considering ambient solar intensity, condenser inlet moist-air temperature, humidity ratio and mass flowrate, and inlet coolant temperature. Statistical analysis indicated that all parameters significantly affected the prediction (p < 0.05). The accuracy of the ANN and RA models was then compared to two models previously developed by Yetilmezsoy and Abdul-Wahab and Al-Ismaili et al. (denoted as Yetilmezsoy model and Al-Ismaili model, respectively). The ANN model showed the best prediction when seven statistical criteria were considered. The Pearson correlations for ANN, RA, Yetilmezsoy, and Al-Ismaili models were observed as 1.00, 0.98, 0.88, and 0.96, respectively, while mean absolute percentage errors (MAPE) were 17.84, 79.72, 63.24, and 80.50%, respectively. Hence it could be recommended to use ANN model for the prediction of freshwater production rate, however other three simple models could also be used with lower accuracy in the cases of unavailability of the ANN model.

Predicting the water production of a solar seawater greenhouse desalination unit using multi-layer perceptron model

A solar seawater greenhouse is a type of desalination plant that uses solar energy and seawater to humidify the interior of the greenhouse and produce fresh water from the humid air (humidification-dehumidification process). The produced water is used both for irrigating agricultural crops and for drinking. Many parameters affect the performance of seawater greenhouses. The present study employed an artificial neural network to examine the effective parameters of the greenhouse on the fresh water production such as width, length, the height of the front evaporator, and roof transparency. A suitable structure was obtained for the multi-layer perceptron (MLP) method and the mathematical statistics % AARE, RMSE, and R2, were used to evaluate network performance. The method showed good agreement with the experimental data. Using the optimized created network, the effect of each parameter on the produced fresh water was assessed. Finally, a 125 m wide and 200 m long of greenhouse with a 4 m height of front evaporator and roof transparency of 0.6 that produced 161.6 m3/day of fresh water was introduced as the optimal seawater greenhouse.

Empirical model for the condenser of the seawater greenhouse

ABSTRACTSeawater greenhouses (SWGH) utilize seawater or saline/brackish groundwater for cooling the microclimate and providing freshwater for irrigation through a humidification–dehumidification desalination process. The overall effectiveness of the SWGH greatly depends on the effectiveness of its condenser. The present study provides a good review on the available simulation models of the SWGH condenser and proposes a multiple linear regression model to predict the dehumidification rate of the condenser in the Oman SWGH. Four climatic and operational input variables were considered, including solar irradiance, inlet moist air temperature, inlet humidity ratio, and inlet air mass flow rate. The results showed that the model accurately predicts the dehumidification rate when compared against experimental values [a mean predictive error (PE) = −0.127 kg/h and root mean square error (RMSE) = 4.691 kg/h]. The model also outperformed some other model in several accuracy indicators such as PE, mean absolute predictive error, RMSE, R2, index of agreement and fractional variance.

Brine utilisation for cooling and salt production in wind-driven seawater greenhouses: Design and modelling

Brine disposal is a major challenge facing the desalination industry. Discharged brines pollute the oceans and aquifers. Here is it proposed to reduce the volume of brines by means of evaporative coolers in seawater greenhouses, thus enabling the cultivation of high-value crops and production of sea salt. Unlike in typical greenhouses, only natural wind is used for ventilation, without electric fans. We present a model to predict the water evaporation, salt production, internal temperature and humidity according to ambient conditions. Predictions are presented for three case studies: (a) the Horn of Africa (Berbera) where a seawater desalination plant will be coupled to salt production; (b) Iran (Ahwaz) for management of hypersaline water from the Gotvand dam; (c) Gujarat (Ahmedabad) where natural seawater is fed to the cooling process, enhancing salt production in solar salt works. Water evaporation per face area of evaporator pad is predicted in the range 33 to 83m3/m2·yr, and salt production up to 5.8tonnes/m2·yr. Temperature is lowest close to the evaporator pad, increasing downwind, such that the cooling effect mostly dissipates within 15m of the cooling pad. Depending on location, peak temperatures reduce by 8–16°C at the hottest time of year.

Study on parameters effective on the performance of a humidification-dehumidification seawater greenhouse using support vector regression

A Seawater greenhouse is a desalination plant that, using solar energy and seawater, humidifies the interior of the greenhouse and produces water from the humid air. The produced water can be used both for irrigation and human consumption. Many factors affect the performance of a seawater greenhouse. In this study, using artificial neural networks, the effects of greenhouse width and length, first evaporator height, and roof transparency on the water production and energy consumption of a seawater greenhouse were examined with the help of Support Vector Regression (SVR) method. A suitable structure was obtained for this method, and %AARE, RMSE and R2 statistic measures were used for evaluating the performance of the network. This method shows the favorable correspondence with experimental data. Using the prepared optimized network, the effect of each parameter on water production and energy consumption was examined for a wide range of variations in the parameter values. Finally, a 125m wide, 200m long greenhouse with a 4m high evaporator and permeability of 0.6 was found to be the optimum configuration, offering a daily water production of 161.6m3 for 1.558kWh of energy consumed per cubic meter of water produced.

PROPOSAL STUDY DESERT FOREST NEAR ES-SIDER OIL PORT NW LIBYA

Located that oil port of siders following waha Oil Company which is located west of sirt on covering the moving sand dunes pot dominated system desertification. The solar energy will be used to evaporated brine and generate cool air pure water in order to grow food inside the greenhouses where the sea water will be used facilities. Concentrated idea of the project to exploit an area of about 20km through which pipeline to flow of sea water to the ground which may allow the lows of Nature which produce fresh water from sea water and change climate conditions to humid climate contributes to the rainfall and characterized the technology that will be used in the project to its ability to transform large tracts of desert into green produce commercial quantities of food and energy crops and freshwater used the project is based on the establishment of greenhouse where sea water used provide growth conditions cold and wet of vegetables in addition to the production of fresh water and will be connected to the solar with thermal units for the desalination of sea water supported by technology and will allow pilot also cultivation of algae in the system of bioreactors optical and farming systems in basins exposed produces plant food ,water, energy between greenhouse protected salt water and solar power intensive and cultivation of algae and technological and scientific . the basic idea of this project is to bring sea water into the desert then vaporized process centered on what is known as sea water where the evaporating sea water by solar energy and then intensify freshwater not only that but maintains a moist interior cool and are ideal for the cultivation of crops ,it was the first model to sea water greenhouse a unit area of 2000 square meters in port Augusta in Australia&nbsp;and has won its first crop tomatoes in the last months ago ,Sahara forest project combines the technology and solar power uses mirrors to focus the light on the complex to heat which in turn produces steam for the management of turbine generator at a supplying greenhouse powered and operated and the greenhouse extended solar power plant with water marking them more efficient that the project is promising and important in the field of renewable energy and to take advantage of the potential and of solar energy in our integrated project and ambitious aims to cultivate bio-fuels to generate an energy clean aimed at protecting the environmental may work on climate change. The project is based on the new Technologies in carpeted into solar energy and seawater Greenhouse and cultivation of green algae and for the cultivation of arid areas and the provision of food and fresh water as well as bio-fuels to generate clean energy. The idea of the project is simple and Natural based on the use of solar energy in the evaporation of salty seawater to generate cold air and water and clean energy in deserts and Technology use Mirrors sunlight to form steam to Run turbines which in turn generate electricity is expected to shift the equipment desert to the territory to the a prosperous agricultural out about the need to drill water wells which increase water shortage and possible planting any kind of vegetables in greenhouse sea water are essential in the project which cost to be cooling desert air warm and ? Wet with sea water before being admitted to the greenhouse and this air humidifier will feed crops inside greenhouse then dryer where flowing sea water heated warmly sun? and soon meet air humidifies of channels containing water condenses fresh water and dripped drops on the external aspects of channels that can be assembled the process mimic what happens in Nature evaporates sea water as a result of the sun’s heat and work is underway to cooling leads to the formation of clouds and condense these vapors of water to fall water like rain only 10-15 % of moist air condenses into fresh water and the rest out of the surrounding tress thus the greenhouse creating green surroundings around the will be through energy intensive and through the use of Mirrors to focus sunlight on pipes and boilers for water district cause radiation intensive production high heat inside the pipe provides enough power to turn Turbines team which in turn would for electrical power and six cell additional power to the people are a population of benefiting says a specialist and is Neil Crompton one energy experts there is huge potential for these new Technologies unit focused and one covering only 9% of the area of&nbsp;deserts ground and can provide five global need for energy as well as can invest this technique streaming tons of sea water per day using only 20 thousand greenhouse.

The Use of Solar Energy in the Desalination Sea Water in Agricultural Greenhouse

The limited resources of fresh water in arid areas like the Middle East and North Africa MENA have led to the use of poor quality water in irrigation agriculture. These can reduce crop yield and environmental damage. Agriculture accounts for 70% of overall consumption in freshwater. Given the evaporation phenomena that occur in arid regions, this figure rises to 90%. This study focuses on the concept of combining the greenhouse with the desalination of seawater This concept is intended for small scale applications in remote areas where only saline water and solar energy are available. The main objective of this research work is to analyze the production of fresh water using solar energy in the desalination of sea water in the greenhouse. This operating system is in need of thorough study of evaporators, condensers and design of the greenhouse. Desalination, combining the greenhouse to the use of sea water while exploiting the phenomenon of condensation of water vapor in the air, seems to respond positively to the needs of agricultural irrigation. Keywords : Seawater greenhouse; Condenser; dry bulb temperature; relative humidity; seawater temperature; humid air flux; seawater flux; Sultanate of Oman.

Study of influence of operational parameters on the mass condensate flux in the condenser of seawater greenhouse at Muscat, Oman

The main objective of this theoretical work is to study the influence of the operating parameters such as relative humidity, dry-bulb temperature, seawater temperature, humid air flow rate, and seawater flow rate on fresh water produced by dehumidification of humid air in the condenser of an existing seawater greenhouse that is located in Muscat, Oman. The theoretical results show that the mass condensate rate of the process increases with the augmentation of the relative humidity, the dry-bulb temperature, and the humid air flow rate. However, the seawater temperature and the seawater flow rate have a negative effect. The maximum theoretical mass condensate rate obtained was about 155 kg/h. This result is obtained under the following conditions: for air dry-bulb temperature Tdb = 50°C, relative humidity RH = 97%, inlet seawater temperature Tswin = 28.33°C, humid air flow rate m˙air=23.22kg/s, and seawater flow rate m˙sw=5.87kg/s.

The Bubble-Greenhouse: A holistic sustainable approach to small-scale water desalination in remote regions

The Bubble-Greenhouse system combines the well established Seawater Greenhouse concept with a novel humidification–dehumidification (HD) process, based on the large air/water interface generated by bubbling air through a water filled column. Multistage bubble evaporators and multistage bubble condensers allow for effective recovery and reuse of latent heat via a heating/cooling circuit throughout all column stages. The system can operate with salinities of 5000–35,000ppm. Following the HD process, cooled vapour provides the tropical type greenhouse with a humid environment for selected crops. Additional condensation occurs along the greenhouse skin and is gravity-fed to drip line irrigation. Low grade energy options such as solar-thermal, photovoltaic, wind, geo-thermal and salinity-gradient solar ponds provide the energy for the Bubble-Greenhouse. Alternatively, waste heat from diesel power stations nearby can provide cogeneration of electricity and bubble evaporator heat and pressure requirements. Crops grown inside a greenhouse demonstrate a strongly reduced water demand and the closed environment protects crops from insects and diseases. As the technology is conceptually simple to implement, it holds great potential for community participation, empowerment, skills development and capacity building of local people in remote locations.