Results 1 - 10 of 82
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[en] This paper presents a GPC-PID control strategy for a cooling-coil unit in heating, ventilation and air conditioning systems. By analysis of the cooling towers and chillers, different models in the occupied period are considered in each operating condition. Because of the complication of components, well tuned PID controllers are unsatisfied, and the results are poor over a wide range of operation conditions. To solve this problem, a GPC-PID controller with hierarchical structure is proposed based on minimizing the generalized predictive control criterion to tune conventional PID controller parameters. Simulation and experiments show that the proposed controller is able to deal with a wide range of operating conditions and to achieve better performance than conventional methods
[en] This paper presents a model-based optimization strategy for the condenser water loop of centralized heating, ventilation and air conditioning (HVAC) systems. Through analyzing each component characteristics and interactions within and between cooling towers and chillers, the optimization problem is formulated as that of minimizing the total operating cost of all energy consuming devices with mechanical limitations, component interactions, outdoor environment and indoor cooling load demands as constraints. A modified genetic algorithm for this particular problem is proposed to obtain the optimal set points of the process. Simulations and experimental results on a centralized HVAC pilot plant show that the operating cost of the condenser water loop can be substantially reduced compared with conventional operation strategies
[en] In this work, an experimental and a comparative study on terms of tower characteristics (KaV/L), water to air flow ratio (L/G) and efficiency for two film type packings are presented for a wide range of (L/G) ratio from 0.2 to 4. The packings used in this work are vertical corrugated packing (VCP) and horizontal corrugated packing (HCP). The obtained results showed that the performance of the cooling tower is affected by the type and arrangement of the packings. Also, the tower performance showed a decrease with an increase in the (L/G) ratio as is also observed in other types of cooling towers. The results showed the tower with vertical corrugated packing (VCP) has higher efficiency than the one with horizontal corrugated packing (HCP)
[en] Cooling towers are one of the biggest heat and mass transfer devices that are in widespread use. In this paper, we use a detailed model of counter flow wet cooling towers in investigating the performance characteristics. The validity of the model is checked by experimental data reported in the literature. The thermal performance of the cooling towers is clearly explained in terms of varying air and water temperatures, as well as the driving potential for convection and evaporation heat transfer, along the height of the tower. The relative contribution of each mode of heat transfer rate to the total heat transfer rate in the cooling tower is established. It is demonstrated with an example problem that the predominant mode of heat transfer is evaporation. For example, evaporation contributes about 62.5% of the total rate of heat transfer at the bottom of the tower and almost 90% at the top of the tower. The variation of air and water temperatures along the height of the tower (process line) is explained on psychometric charts
[en] Highlights: • Self-adaptive Jaya algorithm is proposed for optimal design of thermal devices. • Optimization of heat pipe, cooling tower, heat sink and thermo-acoustic prime mover is presented. • Results of the proposed algorithm are better than the other optimization techniques. • The proposed algorithm may be conveniently used for the optimization of other devices. - Abstract: The present study explores the use of an improved Jaya algorithm called self-adaptive Jaya algorithm for optimal design of selected thermal devices viz; heat pipe, cooling tower, honeycomb heat sink and thermo-acoustic prime mover. Four different optimization case studies of the selected thermal devices are presented. The researchers had attempted the same design problems in the past using niched pareto genetic algorithm (NPGA), response surface method (RSM), leap-frog optimization program with constraints (LFOPC) algorithm, teaching-learning based optimization (TLBO) algorithm, grenade explosion method (GEM) and multi-objective genetic algorithm (MOGA). The results achieved by using self-adaptive Jaya algorithm are compared with those achieved by using the NPGA, RSM, LFOPC, TLBO, GEM and MOGA algorithms. The self-adaptive Jaya algorithm is proved superior as compared to the other optimization methods in terms of the results, computational effort and function evalutions.
[en] Highlights: • New application for Savonius turbine is presented. • Turbine can improve cooling efficiency of a cooling tower like a windbreaker. • New arrangement is useful from thermal and power generation viewpoints. - Abstract: Two large Savonius turbine have been proposed to use near the radiators of a natural draft dry cooling tower instead of previously proposed solid windbreakers. A numerical procedure has been used to predict the flow field unsteadily, and calculate the cooling improvement and power generation in turbines. Numerical results showed that rotating turbines could improve cooling capacity as the same order of solid windbreakers. It was surprisingly concluded that presence of cooling tower near Savonius turbine increased its power generation. Ultimately, it was concluded that overall improvement of the proposed arrangement was considerable from thermal and clean energy production viewpoints
[en] Highlights: • Radiator-type windbreakers are more efficient than solid types. • They can improve cooling efficiency by three times of solid types. • Radiator-type windbreakers are efficient even at normal condition. - Abstract: Cooling efficiency of a natural draft dry cooling tower decreases under crosswind condition. Many researchers frequently recommended solid windbreakers to improve the cooling efficiency. The present research work concerns with the cooling performance assessment of the cooling tower under crosswind condition when the windbreakers are fabricated from the same type of cooling tower radiators. Computational fluid dynamics approach based on the finite volume method has been used to assess the cooling performance of the cooling tower. Numerical results show that radiator type windbreakers can substantially more improve the cooling efficiency than the usual solid types do
[en] This paper describes an application of artificial neural networks (ANNs) to predict the performance of a cooling tower under a broad range of operating conditions. In order to gather data for training and testing the proposed ANN model, an experimental counter flow cooling tower was operated at steady state conditions while varying the dry bulb temperature and relative humidity of the air entering the tower and the temperature of the incoming hot water along with the flow rates of the air and water streams. Utilizing some of the experimental data for training, an ANN model based on a standard back propagation algorithm was developed. The model was used for predicting various performance parameters of the system, namely the heat rejection rate at the tower, the rate of water evaporated into the air stream, the temperature of the outgoing water stream and the dry bulb temperature and relative humidity of the outgoing air stream. The performances of the ANN predictions were tested using experimental data not employed in the training process. The predictions usually agreed well with the experimental values with correlation coefficients in the range of 0.975-0.994, mean relative errors in the range of 0.89-4.64% and very low root mean square errors. Furthermore, the ANN yielded agreeable results when it was used for predicting the system performance outside the range of the experiments. The results show that the ANN approach can be applied successfully and can provide high accuracy and reliability for predicting the performance of cooling towers
[en] Highlights: ► Simulation of cooling tower performance under different operating conditions. ► Cooling tower performance is simulated using ASPEN PLUS. ► Levenberg–Marquardt method used to adjust model parameters. ► Air and water outlet temperatures are in good accordance with experimental data. - Abstract: Simulation of cooling tower performance considering operating conditions away from design is typically based on the geometrical parameters provided by the cooling tower vendor, which are often unavailable or outdated. In this paper a different approach for cooling tower modeling based on equilibrium stages and Murphree efficiencies to describe heat and mass transfer is presented. This approach is validated with published data and with data collected from an industrial application. Cooling tower performance is simulated using ASPEN PLUS. Murphree stage efficiency values for the process simulator model were optimized by minimizing the squared difference between the experimental and calculated data using the Levenberg–Marquardt method. The minimization algorithm was implemented in Microsoft Excel with Visual Basic for Applications, integrated with the process simulator (ASPEN PLUS) using Aspen Simulation Workbook. The simulated cooling tower air and water outlet temperatures are in good accordance with experimental data when applying only the outlet water temperature to calibrate the model. The methodology is accurate for simulating cooling towers at different operational conditions.
[en] Highlights: → New methodology for evaluation of CT performance is presented. → It enables to study impacts of local irregularities in CT on plant's power output. → Poppe model for applications on the local basis of CTs is presented. → Empirical model connecting cooling water temperature with power output is derived. → Study is based on measured data from a plant and natural draft CT. - Abstract: A methodology for the evaluation of a natural draft cooling tower (CT) that is a part of a power plant is proposed. In this work the connection between CT performance and power output is established. The methodology consists of three subparts, i.e. Cooling Tower Profiler (CTP) method, CT model and model of a power plant. In the first part of the paper the three subparts of the methodology are described. Focus is given to the empirical model of the plant and a new application of the Poppe model. The simple empirical model enables accurate prediction of the power increase as a function of cooling water temperature and load to the plant. On the other hand, Poppe governing equations were derived for application on the local basis of CT. Moreover, the constraints and assumptions of CT analysis are discussed. The methodology is presented on real data from the power plant and CT. This is the base for application of the methodology presented in the second part of the paper where the focus is given on minimizing the error of the methodology. A small area with irregularities is analyzed and results are reported. Furthermore, a simplified computational approach to solving the Poppe equations is proposed yielding faster calculation with preserved accuracy.