Water distillation tower: Experimental investigation, economic assessment, and performance prediction using optimized machine-learning model

Elsheikh, Ammar H.; El‐Said, Emad M.S.; Elaziz, Mohamed Abd; Fujii, Manabu; El-Tahan, Hamed R.

doi:10.1016/j.jclepro.2023.135896

Cited by 81 publications

(10 citation statements)

References 63 publications

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“…Several scholars have focused on this significant issue that urgently needs to be addressed effectively, and many methods have been proposed. Model-based approaches [3][4][5][6][7][8][9], data-driven strategies [10][11][12][13][14][15][16][17][18][19][20][21], and hybrid prognostics [22][23][24][25][26][27][28] are the three main groups into which these methods may be categorized.…”

Section: Introductionmentioning

confidence: 99%

“…Machine learning [10] and statistical methods are commonly used in data-driven technologies. Like the support vector machine (SVM) [11], multilayer perceptron (MLP) [12], and random vector functional link (RVFL) neural network [13], they play a significant role in various engineering applications. Data-driven techniques are also widely applied in the field of lithium-ion battery forecasting.…”

Section: Introductionmentioning

confidence: 99%

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A Lithium-Ion Battery Capacity and RUL Prediction Fusion Method Based on Decomposition Strategy and GRU

Liu

Luo

et al. 2023

Batteries

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To safeguard the security and dependability of battery management systems (BMS), it is essential to provide reliable forecasts of battery capacity and remaining useful life (RUL). However, most of the current prediction methods use the measurement data directly to carry out prediction work, which ignores the objective measurement noise and capacity increase during the aging process of batteries. In this study, an integrated prediction method is introduced to highlight the prediction of lithium-ion battery capacity and RUL. This approach incorporates several techniques, including variational modal decomposition (VMD) with entropy detection, a double Gaussian model, and a gated recurrent unit neural network (GRU NN). Specifically, the PE−VMD algorithm is first utilized to perform a noise reduction process on the capacity data obtained from the measurements, and this results in a global degradation trend sequence and local fluctuation sequences. Afterward, the global degradation prediction model is established by employing the double Gaussian aging model proposed in this paper, and the local prediction models are built for each local fluctuation sequence by GRU NN. Lastly, the proposed hybrid prediction methodology is validated through battery capacity and RUL prediction studies on experimental data from three sources, and its accuracy is also compared with prediction algorithms from the recent related literature. Experimental results demonstrate that the proposed hybrid prediction method exhibits high precision in the predicting future capacity and RUL of lithium-ion batteries, along with strong robustness and predictive stability.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Lithium-Ion Battery Capacity and RUL Prediction Fusion Method Based on Decomposition Strategy and GRU

Liu

Luo

et al. 2023

Batteries

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show abstract

“…Furthermore, using artifcial intelligence accurately predicts thermal efciency and the overall performance of the system. [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Year-Round Experimental Analysis of the Productivity of Vapour-Based Multistage Solar Still: A Developmental Study

Mkhize

Msomi

2023

Journal of Renewable Energy

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The standalone vapour-based multistage solar still with stacked stages (MSS-SS) belongs to a pool of widely studied small-scale water desalination devices through solar thermal energy. This work contributes to the body of knowledge by presenting a system with new configurations. There is a need to develop small-scale systems to be reliable devices for freshwater provision, as brackish water is available for processing. The experimental study was conducted in a field under actual weather conditions, with the data logged and analysed to study the systems’ behaviour under varying meteorological conditions. A maximum distillate yield of 7790 ml, corresponded to a maximum daily average solar radiation at high range. There was a 21.8% decrease to 6090 ml at moderate daily average range and a further decline of 80.5% to 1190 ml in the low daily average range, representing a significant drop in the distillate yield caused by the insufficient heat collection at low range. The high, moderate, and low ranges corresponded to summer, spring and autumn, and winter, respectively. The lower values of the moderate range were the most optimum operationally. The impulsive modes were ideal for high rates of the heat inputs, while the continuous were for low rates. The assumption of a continuous mode and a further increase in the rate of thermal energy input caused thermal damage necessitating the augmentation of the thermal energy storage (TES) device due to a larger collector-to-basin area (CBA) ratio. The distillate yield trends from the stages were dynamic and were the inverse of the stage temperature, which was dictated by the mode and rate of the thermal energy input. These trends were such that stage 5 > 3 > 2 > 1 > 4 at moderate to high ranges and changed a low range. The summer season enhanced the cumulative saline water (SW) preheating and heat recovery to 66.8°C. The economic analysis found that at its most productive level, the cost of producing water per litre (CPL) from the vapour-based MSS-SS was R 4.05. The small-scale water purification systems are helpful, especially in remote areas.

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“…This paper reports the voltage-unbalance compensation performance of a three-phase inverter for a voltage unbalance compensator controlled by using the method of symmetrical components for an induction motor [15]. Some references [16][17][18][19][20] 3-φ load 1-φ load In addition to excessive neutral currents, an unbalanced distribution system leads to voltage unbalance. The operation of three-phase induction motors under unbalanced voltages can have serious negative effects on their performance, including overheating, decreased efficiency, and reduced output torque.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

Lin

et al. 2023

Sustainability

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A mixed-integer linear programming (MILP) model that includes reductions in neutral current, feeder energy-loss cost, customer interruption cost, and labor cost is developed to derive the optimal phase-swapping strategy to enhance the phase balancing of distribution feeders. The neutral current of the distribution feeder is reduced by the phase-swapping strategy so that the tripping of the low-energy overcurrent relay can be prevented and customer-service interruption costs and the labor cost to execute the phase-swapping works can be justified by the energy-loss reduction obtained. The novelty of the study is its derivation of the phase-swapping strategy using mixed-integer linear programming to solve the problem of the unbalance of the distribution feeders. A Taipower distribution feeder is used to derive the phase-swapping strategy to demonstrate the proposed MILP model for phase balancing. The comparison of the phase currents and neutral current before phase-swapping reveals that the three-phase balance was not only significantly improved, but that the voltage unbalance was also decreased dramatically using the proposed phase-swapping strategy.

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Water distillation tower: Experimental investigation, economic assessment, and performance prediction using optimized machine-learning model

Cited by 81 publications

References 63 publications

A Lithium-Ion Battery Capacity and RUL Prediction Fusion Method Based on Decomposition Strategy and GRU

A Lithium-Ion Battery Capacity and RUL Prediction Fusion Method Based on Decomposition Strategy and GRU

Year-Round Experimental Analysis of the Productivity of Vapour-Based Multistage Solar Still: A Developmental Study

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

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