Entropy

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14 pages, 5353 KiB

Open AccessArticle

Optimization and Evaluation of Ventilation Mode in Marine Data Center Based on AHP-Entropy Weight

by Guozeng Feng, Shuya Lei, Yuejiao Guo, Bo Meng and Qingfeng Jiang

Entropy 2019, 21(8), 796; https://doi.org/10.3390/e21080796 - 15 Aug 2019

Cited by 16 | Viewed by 3683

The ventilation mode affects the cooling efficiency of the air conditioners significantly in marine data centers. Three different ventilation modes, namely, underfloor ventilation, overhead ventilation, side ventilation, are numerically investigated for a typical marine data center. Four independent parameters, including temperature, velocity, air [...] Read more.

The ventilation mode affects the cooling efficiency of the air conditioners significantly in marine data centers. Three different ventilation modes, namely, underfloor ventilation, overhead ventilation, side ventilation, are numerically investigated for a typical marine data center. Four independent parameters, including temperature, velocity, air age, and uniformity index, are applied to evaluate the performances of the three ventilation modes. Further, the analytic hierarchy process (AHP) entropy weight model is established and further analysis is conducted to find the optimal ventilation mode of the marine data center. The results indicate that the underfloor ventilation mode has the best performance in the airflow patterns and temperature distribution evaluation projects, with the highest scores of 91.84 and 90.60. If low energy consumption is required, it is recommended to select the overhead ventilation mode with a maximum score of 93.50. The current evaluation results agree fairly well with the three dimensional simulation results, which further proves that the AHP entropy weight method is reasonable and has a high adaptability for the evaluation of air conditioning ventilation modes. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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28 pages, 1014 KiB

Open AccessArticle

Thermal Optimization of a Dual Pressure Goswami Cycle for Low Grade Thermal Sources

by Gustavo Guzmán, Lucía De Los Reyes, Eliana Noriega, Hermes Ramírez, Antonio Bula and Armando Fontalvo

Entropy 2019, 21(7), 711; https://doi.org/10.3390/e21070711 - 20 Jul 2019

Cited by 6 | Viewed by 4126

Abstract

This paper presents a theoretical investigation of a new configuration of the combined power and cooling cycle known as the Goswami cycle. The new configuration consists of two turbines operating at two different working pressures with a low-heat source temperature, below 150 °C. [...] Read more.

This paper presents a theoretical investigation of a new configuration of the combined power and cooling cycle known as the Goswami cycle. The new configuration consists of two turbines operating at two different working pressures with a low-heat source temperature, below 150 °C. A comprehensive analysis was conducted to determine the effect of key operation parameters such as ammonia mass fraction at the absorber outlet and boiler-rectifier, on the power output, cooling capacity, effective first efficiency, and effective exergy efficiency, while the performance of the dual-pressure configuration was compared with the original single pressure cycle. In addition, a Pareto optimization with a genetic algorithm was conducted to obtain the best power and cooling output combinations to maximize effective first law efficiency. Results showed that the new dual-pressure configuration generated more power than the single pressure cycle, by producing up to 327.8 kW, while the single pressure cycle produced up to 110.8 kW at a 150 °C boiler temperature. However, the results also showed that it reduced the cooling output as there was less mass flow rate in the refrigeration unit. Optimization results showed that optimum effective first law efficiency ranged between 9.1% and 13.7%. The maximum effective first law efficiency at the lowest net power (32 kW) and cooling (0.38 kW) outputs was also shown. On the other hand, it presented 13.6% effective first law efficiency when the net power output was 100 kW and the cooling capacity was 0.38 kW. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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14 pages, 2181 KiB

Open AccessArticle

Heat Transfer Coefficients Analysis in a Helical Double-Pipe Evaporator: Nusselt Number Correlations through Artificial Neural Networks

by Arianna Parrales, José Alfredo Hernández-Pérez, Oliver Flores, Horacio Hernandez, José Francisco Gómez-Aguilar, Ricardo Escobar-Jiménez and Armando Huicochea

Entropy 2019, 21(7), 689; https://doi.org/10.3390/e21070689 - 14 Jul 2019

Cited by 19 | Viewed by 4013

Abstract

In this study, two empirical correlations of the Nusselt number, based on two artificial neural networks (ANN), were developed to determine the heat transfer coefficients for each section of a vertical helical double-pipe evaporator with water as the working fluid. Each ANN was [...] Read more.

In this study, two empirical correlations of the Nusselt number, based on two artificial neural networks (ANN), were developed to determine the heat transfer coefficients for each section of a vertical helical double-pipe evaporator with water as the working fluid. Each ANN was obtained using an experimental database of 1109 values obtained from an evaporator coupled to an absorption heat transformer with energy recycling. The Nusselt number in the annular section was estimated based on the modified Wilson plot method solved by an ANN. This model included the Reynolds and Prandtl numbers as input variables and three neurons in their hidden layer. The Nusselt number in the inner section was estimated based on the Rohsenow equation, solved by an ANN. This ANN model included the numbers of the Prandtl and Jackob liquids as input variables and one neuron in their hidden layer. The coefficients of determination were

R^{2} > 0.99

for both models. Both ANN models satisfied the dimensionless condition of the Nusselt number. The Levenberg–Marquardt algorithm was chosen to determine the optimum values of the weights and biases. The transfer functions used for the learning process were the hyperbolic tangent sigmoid in the hidden layer and the linear function in the output layer. The Nusselt numbers, determined by the ANNs, proved adequate to predict the values of the heat transfer coefficients of a vertical helical double-pipe evaporator that considered biphasic flow with an accuracy of ±0.2 for the annular Nusselt and ±4 for the inner Nusselt. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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21 pages, 4720 KiB

Open AccessEditor’s ChoiceArticle

Multiobjective Optimization of a Plate Heat Exchanger in a Waste Heat Recovery Organic Rankine Cycle System for Natural Gas Engines

by Guillermo Valencia, José Núñez and Jorge Duarte

Entropy 2019, 21(7), 655; https://doi.org/10.3390/e21070655 - 3 Jul 2019

Cited by 47 | Viewed by 5062

Abstract

A multiobjective optimization of an organic Rankine cycle (ORC) evaporator, operating with toluene as the working fluid, is presented in this paper for waste heat recovery (WHR) from the exhaust gases of a 2 MW Jenbacher JMS 612 GS-N.L. gas internal combustion engine. [...] Read more.

A multiobjective optimization of an organic Rankine cycle (ORC) evaporator, operating with toluene as the working fluid, is presented in this paper for waste heat recovery (WHR) from the exhaust gases of a 2 MW Jenbacher JMS 612 GS-N.L. gas internal combustion engine. Indirect evaporation between the exhaust gas and the organic fluid in the parallel plate heat exchanger (ITC2) implied irreversible heat transfer and high investment costs, which were considered as objective functions to be minimized. Energy and exergy balances were applied to the system components, in addition to the phenomenological equations in the ITC2, to calculate global energy indicators, such as the thermal efficiency of the configuration, the heat recovery efficiency, the overall energy conversion efficiency, the absolute increase of engine thermal efficiency, and the reduction of the break-specific fuel consumption of the system, of the system integrated with the gas engine. The results allowed calculation of the plate spacing, plate height, plate width, and chevron angle that minimized the investment cost and entropy generation of the equipment, reaching 22.04 m² in the heat transfer area, 693.87 kW in the energy transfer by heat recovery from the exhaust gas, and 41.6% in the overall thermal efficiency of the ORC as a bottoming cycle for the engine. This type of result contributes to the inclusion of this technology in the industrial sector as a consequence of the improvement in thermal efficiency and economic viability. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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20 pages, 3388 KiB

Open AccessArticle

Thermodynamic and Economic Analyses of Reformative Design for High Back-Pressure Heating in Coal-Fueled Cogeneration Units

by Heng Chen, Yunyun Wu, Jidong Xu, Gang Xu, Yongping Yang, Wenyi Liu and Gangye Shi

Entropy 2019, 21(4), 342; https://doi.org/10.3390/e21040342 - 28 Mar 2019

Cited by 8 | Viewed by 4678

Abstract

High back-pressure (HBP) heating technology has been identified as an effective approach to improve the efficiency of combined heat and power (CHP). In this study, the novel concept of a HBP heating system with energy cascade utilization is developed and its probability examined. [...] Read more.

High back-pressure (HBP) heating technology has been identified as an effective approach to improve the efficiency of combined heat and power (CHP). In this study, the novel concept of a HBP heating system with energy cascade utilization is developed and its probability examined. In the reformative design, the extracted heating steam from the intermediate-pressure turbine (IPT) is first drawn to an additional turbine where its excess pressure can be converted into electricity, then steam with a lower pressure can be employed to heat the supply water. As a consequence, the exergy destruction in the supply water heating process can be reduced and the efficiency of the cogeneration unit raised. A detailed thermodynamic investigation was performed based on a typical coal-fired HBP–CHP unit incorporating the proposed configuration. The results show that the artificial thermal efficiency (ATE) promotion was as much as 2.01 percentage points, with an additional net power output of 8.4 MW compared to the reference unit. This was attributed to a 14.65 percentage-point increment in the exergy efficiency of the supply water heating process caused by the suggested retrofitting. The influences of the unit power output, unit heat output, supply water and return water temperatures and turbine back pressure on the thermal performance of the modified system are discussed as well. In addition, the economic performance of the new design is assessed, indicating that the proposed concept is financially feasible. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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25 pages, 6201 KiB

Open AccessArticle

Entropy Analysis of Temperature Swing Adsorption for CO₂ Capture Using the Computational Fluid Dynamics (CFD) Method

by Zhihao Guo, Shuai Deng, Shuangjun Li, Yahui Lian, Li Zhao and Xiangzhou Yuan

Entropy 2019, 21(3), 285; https://doi.org/10.3390/e21030285 - 15 Mar 2019

Cited by 6 | Viewed by 4522

Abstract

Carbon capture by adsorption is supposed to be an effective method to reduce CO₂ emissions, among which Temperature Swing Adsorption (TSA) can utilize low-grade thermal energy even from renewable energy source. At present, TSA technology still has several challenges to be practical [...] Read more.

Carbon capture by adsorption is supposed to be an effective method to reduce CO₂ emissions, among which Temperature Swing Adsorption (TSA) can utilize low-grade thermal energy even from renewable energy source. At present, TSA technology still has several challenges to be practical application, such as intensive energy-consumption and low energy-efficiency. Thermodynamics could be a powerful method to explore the energy conversion mechanism of TSA, among which entropy analysis could further provide a clear picture on the irreversible loss, even with a possible strategy of energy-efficient improvement. Based on the theory of non-equilibrium thermodynamics, the entropy analysis of TSA cycle is conducted, using the Computational Fluid Dynamics (CFD) method. The physical model and conservation equations are established and calculation methods for entropy generation are presented as well. The entropy generation of each process in cycle is analyzed, and the influence from the main parameters of desorption process is presented with optimization analysis. Finally, the performance of the cycle with regeneration is compared with that of the cycle without regeneration, and the method of reducing the entropy generation is obtained as well. This paper provides possible directions of performance improvement of TSA cycle with regards on energy utilization efficiency and the reduction of irreversible loss. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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14 pages, 3334 KiB

Open AccessArticle

Thermo-Economic Optimization of an Idealized Solar Tower Power Plant Combined with MED System

by Yanjie Zheng, Yunsheng Zhao, Shen Liang and Hongfei Zheng

Entropy 2018, 20(11), 822; https://doi.org/10.3390/e20110822 - 26 Oct 2018

Cited by 11 | Viewed by 3496

Abstract

Based on the reversible heat engine model, theoretical analysis is carried out for economic performance of a solar tower power plant (STPP) combined with multi-effect desalination (MED). Taking total revenue of the output power and the fresh water yield per unit investment cost [...] Read more.

Based on the reversible heat engine model, theoretical analysis is carried out for economic performance of a solar tower power plant (STPP) combined with multi-effect desalination (MED). Taking total revenue of the output power and the fresh water yield per unit investment cost as the economic objective function, the most economical working condition of the system is given by analyzing the influence of the system investment composition, the receiver operating temperature, the concentration ratio, the efficiency of the endoreversible heat engine, and the relative water price on the economic parameters of the system. The variation curves of the economic objective function are given out when the main parameter is changed. The results show that the ratio of water price to electricity price, or relative price index, has a significant impact on system economy. When the water price is relatively low, with the effect numbers of the desalination system increasing, and the economic efficiency of the overall system worsens. Only when the price of fresh water rises to a certain value does it make sense to increase the effect. Additionally, the threshold of the fresh water price to the electricity price ratio is 0.22. Under the conditions of the current price index and the heliostat (or reflector), the cost ratio and the system economy can be maximized by selecting the optimum receiver temperature, the endoreversible heat engine efficiency, and the optimum concentration ratio. Given the receiver surface temperature and the endoreversible heat engine efficiency, increasing the system concentration ratio of the heliostat will be in favor of the system economy. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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16 pages, 1634 KiB

Open AccessArticle

Big-Data-Mining-Based Improved K-Means Algorithm for Energy Use Analysis of Coal-Fired Power Plant Units: A Case Study

by Binghan Liu, Zhongguang Fu, Pengkai Wang, Lu Liu, Manda Gao and Ji Liu

Entropy 2018, 20(9), 702; https://doi.org/10.3390/e20090702 - 13 Sep 2018

Cited by 11 | Viewed by 3882

Abstract

The energy use analysis of coal-fired power plant units is of significance for energy conservation and consumption reduction. One of the most serious problems attributed to Chinese coal-fired power plants is coal waste. Several units in one plant may experience a practical rated [...] Read more.

The energy use analysis of coal-fired power plant units is of significance for energy conservation and consumption reduction. One of the most serious problems attributed to Chinese coal-fired power plants is coal waste. Several units in one plant may experience a practical rated output situation at the same time, which may increase the coal consumption of the power plant. Here, we propose a new hybrid methodology for plant-level load optimization to minimize coal consumption for coal-fired power plants. The proposed methodology includes two parts. One part determines the reference value of the controllable operating parameters of net coal consumption under typical load conditions, based on an improved K-means algorithm and the Hadoop platform. The other part utilizes a support vector machine to determine the sensitivity coefficients of various operating parameters for the net coal consumption under different load conditions. Additionally, the fuzzy rough set attribute reduction method was employed to obtain the minimalist properties reduction method parameters to reduce the complexity of the dataset. This work is based on continuously-measured information system data from a 600 MW coal-fired power plant in China. The results show that the proposed strategy achieves high energy conservation performance. Taking the 600 MW load optimization value as an example, the optimized power supply coal consumption is 307.95 g/(kW·h) compared to the actual operating value of 313.45 g/(kW·h). It is important for coal-fired power plants to reduce their coal consumption. Full article

(This article belongs to the Special Issue Thermodynamic Optimization)

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