Development and analysis of a new integrated solar energy system with thermal storage for fresh water and power production

Demir, Murat Emre; Dinçer, İbrahim

doi:10.1002/er.3846

Cited by 47 publications

(31 citation statements)

References 29 publications

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“…There is still some scope for improving the accuracy of the models and the computational time. Therefore, the future work for authors is to work on developing a holistic integrated solution, which can accurately estimate the state of a battery module in a minimum computational time.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of battery modules state for electric vehicle using artificial neural network and experimental validation

Liang

Bao

Zhang

et al. 2018

Energy Science & Engineering

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This work undertakes research problem on prediction of state of battery modules used in electric vehicle. Past studies focussed extensively on the estimation of state of charge and state of health of a single cell/battery. However, the focus on the estimation of state of entire battery module is hardly studied. During the actual operation of electric vehicle, the environmental conditions (road slope and climate) and factors such as abnormal voltage and temperature conditions causes the deviations among the battery modules from its equilibrium state. As a result, its power efficiency and the life‐cycle decreases. One of the reasons of deviation is the defects in manufacturing of a battery module. For this purpose, the evaluation and estimation of state of battery modules is a priority to have information on which module among the given ones should be discharged first. Therefore, this study proposes the methodology for the evaluation of state of battery modules based on its current and temperature. Firstly, the rules are defined based on experiments to determine the priority for the discharge of each of the six modules. Dataset of 6000 samples obtained comprises of the 12 inputs (temperature and current) and 6 outputs (on‐off state of switch). Each output represents the priority of module to be discharged. To analyze this multi‐input multi‐output dataset, the popular artificial intelligence algorithm namely, artificial neural network with three training algorithms (Levenberg, Scaled conjugate and Bayesian regularization), using a number of neurons from 2 to 20 in the hidden layer is used. It was found that the model obtained using Levenberg algorithm performs the best.

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Section: Discussionmentioning

confidence: 99%

Evaluation of battery modules state for electric vehicle using artificial neural network and experimental validation

Liang

Bao

Zhang

et al. 2018

Energy Science & Engineering

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“… σ and ϵ are Stefan Boltzmann constant and emissivity, respectively. A r is the receiver area, and h a is the convective heat transfer coefficient of the air and can be described as a follows:

h_{a} = 10.45 - V_{a} + 10 \sqrt{V_{a}} .

…”

Section: Thermodynamic Analysismentioning

confidence: 99%

“…The molten salt temperature decreases over time as a result of the heat losses occurred on the surface. The temperature difference ( θ ) can be calculated as follows:

ρ_{ms} V_{ms} c_{ms} \frac{dθ}{dt} = - U A_{t} θ,

where c ms , V ms , and ρ ms are the specific heat, volume, and density of the molten salt and can be formulated as follows:

ρ = 2090 - 0.636 T ((), ^{°} normalC),

c_{p} = 1443 + 0.172 T ((), ^{°} normalC .)

…”

Section: Thermodynamic Analysismentioning

confidence: 99%

Design and analysis of a solar tower power plant integrated with thermal energy storage system for cogeneration

Sorgulu

Dinçer

2018

Int J Energy Res

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Summary In the current study, a solar tower–based energy system integrated with a thermal energy storage option is offered to supply both the electricity and freshwater through distillation and reverse osmosis technologies. A high‐temperature thermal energy storage subsystem using molten salt is considered for the effective and efficient operation of the integrated system. The molten salt is heated up to 565°C through passing the solar tower. The thermal energy storage tanks are designed to store heat up to 12 hours. The temperature variations in the storage tanks are studied and compared accordingly for evaluation. The effect of operating temperatures on the freshwater production and overall system efficiency is determined. About 24.46 MW electricity is generated in the steam turbine under sunny conditions. Furthermore, the storage subsystem stores heat during sunny hours to utilize later in cloudy hours and night time. The produced power decreases to 20.17 MW in discharging hours due to temperature decrease in the tank. The electricity generated by the system is then used to produce freshwater through the reverse osmosis units and also to supply electricity for the residential use. A total flowrate of 240.02 kg/s freshwater is obtained by distillation and reverse osmosis subsystems.

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“…8,9 It works on the principle where the material itself will store and release an amount of heat when the phase changes during the operation. 18 Among these types of PCM, technical grade paraffin wax is the most popular PCM used for latent heat energy storage material in solar air heater applications 19 because of its ability to provide a wide range of application temperature, less expensive, chemically stable, and suitable to be used in many types of metal container. Many solar air heater applications using latent heat energy storage materials such as hydrated salt, 13 palmitic and lauric acid, 14,15 and technical grade paraffin wax 11,12 have been studied.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on performance of square tube absorber with phase change material

et al. 2019

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The intermittent nature of solar radiation has decreased the performance efficiency of solar heaters. Integrating the solar heater with thermal energy storage component could increase its performance effectively. In this article, an investigation on the effect of phase change material (PCM) as the thermal energy storage component on the performance of square aluminum tube was carried out experimentally. In the first phase, the temperature behavior of square aluminum tube with two types of PCM, namely, generic plant-based PCM (A2) and paraffin wax (A3), was compared with square aluminum tube without PCM (A1). In the second phase, the performance of square aluminum tube was investigated with different paraffin wax masses of 38 g (B1), 48 g (B2), and 58 g (B3). Based on the result, the A3 tube configuration performed better than A1 and A2 tube configurations with higher heat gain rate (0.08°C/s) and lower heat discharge rate (−0.04°C/s). The B2 tube configuration was found to have maximum heat gain of 3.73 kJ with higher heat discharge rate as compared with other square tube configurations. The average temperature difference between internal and external surface tube of B2 was lower (4.3°C) leading to higher average temperature difference at ambient temperature of 25.3°C. Instantaneous efficiency of the tube B2 is higher than the B1 and B3 tube configurations by 16% and 26%, respectively. The result suggests that the insertion of paraffin wax inside the square absorber tube improves the temperature response of the absorber in the situation of intermittent solar radiation. KEYWORDS cross-matrix absorber (CMA), phase change material (PCM), solar energy, thermal energy storage

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Development and analysis of a new integrated solar energy system with thermal storage for fresh water and power production

Cited by 47 publications

References 29 publications

Evaluation of battery modules state for electric vehicle using artificial neural network and experimental validation

Evaluation of battery modules state for electric vehicle using artificial neural network and experimental validation

Design and analysis of a solar tower power plant integrated with thermal energy storage system for cogeneration

Experimental study on performance of square tube absorber with phase change material

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