An optimized PSO-ANN model for improved prediction of water treatment desalination plant performance

An accurate prediction of the performance of water treatment desalination plants could directly improve the global socio-economic balance. In this regard, many researchers have been engaged in the various artificial intelligence applied soft computing techniques to predict actual process outcomes. Inspired by the significance of such techniques, an optimized Particle Swarm Optimization based Artificial Neural Network (PSO-ANN) technique has been proposed herewith to predict an accurate performance of the reverse osmosis (RO) based water treatment desalination plants. Literature suggests that the improvements of the soft computing models depend on their modeling parameters. Therefore, we have included an extended list of nine modeling parameters with a systematic indepth investigation to explore their optimal values. Finally, the model's simulations results (R2 = 99.1%, Error = 0.006) were found superior than the existing ANN models (R2 = 98.8%, Error = 0.060), with the same experimental datasets. Additionally, the simulation results recommend that among many parameters considered, the number of hidden layer nodes (n), swarm sizes (SS), and the weight of inertia (ω) play a major role in the model optimization. This study for a more accurate prediction of the plant's performance shall pave the way for the process design and control engineers to improve the plant efficiency further.

Comparing the utilities consumptions in Dubai per category and community: MANOVA and cluster analysis approaches

UAE is marked by the increasing demand for water and electricity due to demographic, environmental and economic factors, coupled with the dependence on water desalination process, which is costly, consumes a lot of energy and is non-environmentally friendly. Like most of the authorities in UAE, Dubai Electricity and Water Authority is facing the challenges of balancing supply with demand and responding to consumer requirements, from one side, and addressing the continuously increasing consumption and slowing it down from another side. Therefore, policy makers can benefit from statistical data analysis in order to make informed decisions. This study aims to equip decision makers with useful tools and analysis to address some of their short- and long-term objectives related to production and consumption. The current study focused on three main objectives: (i) analysing the production of the desalination plants in Dubai, (ii) comparing the consumptions of water and electricity based on the four categories residential, commercial, industrial and others, and (iii) segmenting the various communities in Dubai depending on their consumption behavior. The data used for this study is collected from the open government data and SAS Programming is adopted for data analysis. The results of the analysis revealed that the desalinated water production follows an upward trend, yet still not in line with the consumption growth. Furthermore, there are significant differences between the four categories for both water and electricity consumptions. The highest levels of consumptions are associated with the residential and commercial categories. Finally, the cluster analysis technique revealed fifteen clusters of communities depending on the consumption levels.

Localized Electroconvection at Ion-Exchange Membranes with Heterogeneous Surface Charge

Operating electrochemical membrane processes beyond the limiting current density bears the potential to decrease the investment cost of desalination plants significantly. However, while there are strategies for successfully reducing energy demand by shortening the plateau region, their influence on the formation of electroconvection is still unknown. This study demonstrates control over the electroconvective vortices' rotational direction and position using a surface patterning method. We compare the development of electroconvection at two membranes modified with patterns of different surface charges. We analyze the electroconvective vortex field's build-up, the vortices' rotational direction, and structural stability in the steady-state. Finally, we showcase the control possibilities by enforcing a specific structure along an asymmetric letter pattern. Such tailor-made patterns have the potential to diminish the plateau region's energy loss completely. Furthermore, the scale-up of these membranes to industrial processes will allow the economic operation in the overlimiting regime, significantly increasing their space-time yield.

Reverse Osmosis Desalination Plants Energy Consumption Management and Optimization for Improving Power Systems Voltage Stability with PV Generation Resources

This paper studies energy consumption management of seawater Reverse Osmosis (RO) desalination plants to maintain and enhance the Voltage Stability (VS) of Power Systems (PS) with Photovoltaic (PV) plant integration. We proposed a voltage-based management algorithm to determine the maximum power consumption for RO plants. The algorithm uses power flow study to determine the RO plant power consumption allowed within the voltage-permissible limits, considering the RO process constraints in order to maintain the desired fresh water supply. Three cases were studied for the proposed RO plant: typical operation with constant power consumption, controlled operation using ON/OFF scheduling of the High-Pressure Pumps (HPPs) and controlled operation using Variable Frequency Drive (VFD) control. A modified IEEE 30-bus system with a variable load was used as a case study with integration of three PV plants of 75 MWp total power capacity. The adopted 33.33 MW RO plant has a maximum capacity of 200,000 m3/day of fresh water production. The results reveal that while typical operation of RO plants can lead to voltage violation, applying the proposed load management algorithm can maintain the vs. of the PS. The total transmission power loss and power lines loading were also reduced. However, the study shows that applying VFD control is better than using ON/OFF control because the latter involves frequent starting up/shutting down the RO trains, which consequently requires flushing and cleaning procedures. Moreover, the specific energy consumption (SEC) and RO plant recover ratio decreases proportionally to the VFD output. Furthermore, the power consumption of the RO plant was optimized using the PSO technique to avoid unnecessary restriction of RO plant operation and water shortage likelihood.

Corrosion mitigation in desalination plants by ammonium-based ionic liquid

CuNi (90:10) alloy is widely used in desalination plants. CuNi alloy corrosion in sulfide-containing seawater is the fundamental problem in the desalination industry. Here we have confronted this difficulty by using ammonium-based ionic liquid (Diethyl (2-methoxyethyl)-methyl ammonium Bis(fluorosulfonyl)imide) [DEMEMA][FSI]. The results revealed that the [DEMEMA][FSI] can suppress Cu–Ni alloy corrosion in a solution of (3.5% NaCl + 10 ppm sulphide) with an efficiency of 98.4% at 120 ppm. This has been estimated by electrochemistry and gravimetry. Furthermore, [DEMEMA][FSI] inhibits the growth of sulfate-reducing bacteria SRB in saline water. Surface morphology testing confirmed [DEMEMA][FSI] adsorption on Cu–Ni surface alloys. In addition, quantum calculations have been used to theoretically predict inhibition efficiency [DEMEMA][FSI].

Rethinking Salt Supply Chains: Cost and Emissions Analysis for Coproduction of Salt and Fresh Water from U.S. Seawater

Is it feasible to build desalination plants for the coproduction of salt and fresh water from U.S. seawater that could lead to a restructuring of supply chains for salt imports? As it is predicted that climate change will increase water stress worldwide, an increasing number of countries are using desalination plants to generate fresh water. In most such cases, residual concentrates must be disposed of, and the disposal cost is increasing as countries are becoming more environmentally conscious. Selective salt recovery can help to alleviate this issue as it reduces the need for concentrate disposal and generates additional revenue. To gain some insights into the costs and benefits of coproduction plants, we have collected data on current desalination practices and salt imports in the United States along with the manufacturing costs and energy requirements for coproduction plants. We have used this data to build an optimization model to determine an optimal number and location of coproduction plants in the United States and their potential markets for the sale of coproduced salt. In our analysis, we consider a different total number of coproduction facilities, and for each configuration, we evaluate the resulting net water cost and carbon emissions impact. Our results indicate that there exists the potential for building several coproduction plants in the United States that would be both financially competitive with existing desalination plants and lead to a reduction in carbon emissions. This information might be of use to both governments and businesses when they make decisions about the type of desalination facilities built and the implemented “polluter pays” policies. This paper was accepted by Beril Toktay, Special Issue of Management Science: Business and Climate Change.