Search Results (16)

As an important part of industrial production, the optimization of circulating water systems is of great significance for improving energy efficiency and reducing operating costs. However, traditional optimization methods lack real-time and dynamic adjustment capabilities and often cannot fully cope with the complex and changeable industrial environment and energy demands. Advances in computer technology can enable people to use machine learning models to process information and data and ultimately help simplify simulation and optimization. In this paper, the circulating water system of a Fluid Catalytic Cracking (FCC) unit is optimized and evaluated based on process simulation and machine learning, adopting 284 sets of industrial operating data. The cooler network of the system is modified from a parallel structure to a series mode, and the effect is clarified using the ASPEN HYSYS software V12. Meanwhile, the fan power of the cooling tower is predicted by employing an optimized Gradient Boosting Regression (GBR) model, and the influence of the parallel-to-series transformation on the fan power is discussed. It is shown that the computer modeling results are in coincidence with the industrial data. Converting the parallel design to a series arrangement of the cooler network can significantly decrease the water consumption, with a reduction of 11%. The fan power of the cooling tower is also reduced by 8% after the optimization. Considering the changes in both water consumption and fan power, the saved total economic cost is 8.65%, and the decreased gas emission is 2142.06 kg/h. By building the optimization prediction system, the real-time sequencing and monitoring of equipment parameters are realized, which saves costs and improves process safety. Full article

To effectively reduce building energy consumption, a novel full fresh air system with a heat source tower (HST) and a borehole heat exchanger (BHE) was proposed for space cooling and dehumidification in this paper. The cooling system only adopts geothermal energy to produce dry and cold fresh air for space cooling and dehumidification through the BHE and HST, which has the advantage of non-condensate water compared to BHE systems integrated with a fan coil or chilled beam. Based on the established mathematical model of the cooling system, this paper analyzed the system characteristics, feasibility, operation strategy, energy performance, and cost-effectiveness of the proposed model in detail. The results show that the mathematical model has less than 10% error in estimating the system performance compared to the practical HST–BHE experimental set up. Under the specific boundary conditions, the cooling and dehumidification capacity of this system increases with the decrease in the air temperature, air moisture content, and inlet water temperature of the HST. The optimal cooling capacity and the system COP can be achieved when the air–water flow ratio is at 4:3. A case study was conducted in a residential building in Shenyang with an area of about 1800 m². It was found that this system can fully meet the cooling and dehumidification demand in such a residential building. The operation strategy of the cooling system can be optimized by adjusting the air–water flow ratio from 4:3 to 3:2 during the early cooling season (7 June–1 July) and end cooling season (3 August–1 September). As a result, the average COP of the cooling system during the whole cooling season can be improved from 6.1 to 8.7. Compared with the air source heat pump (ASHP) and the ground source heat pump (GSHP) for space cooling, the proposed cooling system can achieve an energy saving rate of 123% and 26%, respectively. Considering that the BHE of the GSHP can be part of the proposed HST–BHE cooling system, the integration of the HST and GHSP for space cooling (and heating) is strongly recommended in actual applications. Full article

Energy and climate targets necessitate efficiency indicators to reflect resource-saving potentials. Prevailing indicators for cooling towers, however, often omit the effect of outside conditions. Hence, this study introduces an innovative indicator grounded in the energy efficiency ratio. Our proposed metric is the cost–benefit ratio between electricity demand and the thermodynamic minimum airflow. Thus, we call the novel indicator the airflow performance indicator. To validate its feasibility, we apply the indicator first to an extensive dataset encompassing 6575 cooling tower models and second to a year-long case study involving a data center’s wet cooling system. As a result, the energy performance indicator demonstrates that dry cooling requires eight times more minimum airflow at the median than evaporative cooling would, directly correlating to the fan power. Furthermore, efficiency benchmarks derived from the dataset of 6575 cooling tower models provide a comparative assessment of the case study. Defining the quantified benefit as minimum airflow additionally underscores the limitations of free cooling as the wet cooling system only partly covers the cooling demand, requiring chillers additionally. In conclusion, the indicator empowers the identification of energy-saving potentials in the selection, design, and operation of cooling towers. Moreover, the functional unit definition provides a foundation for future life cycle assessments of cooling towers, enhancing cooling tower efficiency and sustainability. Full article

When examining the history of wind engineering, it is evident that many full-scale/model test comparisons have found noticeable differences between the results. Although understanding the causes of these differences is important for practical purposes, limited numerical and experimental conditions have often resulted in subjective explanations for full-scale/model test comparisons without scientific validation. To address this issue, this article suggests the use of the computational fluid dynamics technique or the multiple-fan actively controlled wind tunnel technique to quantitatively reveal the adverse effects that impact the reliability of the traditional atmospheric boundary layer wind tunnel tests for a large cooling tower, including not only the widely acknowledged influences (Reynolds number effects and turbulent flow characteristics effects) but also the non-stationarity effects that have potential influences. Established on the novel proposition, a new research scheme for future full-scale/model test wind effects comparisons for large cooling towers has been formulated based on the numerical or physical simulations of the sinusoidal flow fields. Using the Pengcheng cooling tower as a case study, the research recognized the very significant impact of Reynolds number effects, the non-stationarity effects that cannot be ignored, and the negligible effects of turbulent flow characteristics. Full article

Significant harm from heat has become a key restriction for deep metal mining with increasing mining depth. This paper proposes a refrigeration ventilation system for deep metal mines combined with an existing air cycling system and builds an experimental platform with six stope simulation boxes. Using the heat current method and the driving-resistance balance relationship, the heat transfer and flow constraints of the system were constructed. An artificial neural network was used to establish models of heat exchangers and refrigerators with historical experimental data. Combining the models of the system and stope simulation box, an algorithm that iterates the water outlet temperature of the evaporator and condenser of the refrigerator was proposed to design the coupled simulation model. The heat balance analysis and comparison of the air outlet temperatures of the stope, as well as the heat transfer rates of the heat exchangers with the experimental data, validated the coupled simulation model. Additionally, the effects of cooling fans and the air inlet temperature of the cooling tower were discussed, which provided a powerful modelling method for the coupled model of a refrigeration ventilation system, helps to reduce energy consumption, and improves the sustainability of mining production. Full article

Persistent low-frequency (<180 Hz) acoustic detection took place within the boundaries of Oak Ridge National Laboratory to monitor full power operations of the High Flux Isotope Reactor. Three acoustic sensors were installed at distances of 69, 101, and 914 m from the northeast corner of the cooling towers to monitor and assess four reactor power generation cycles. Features were extracted from power spectral density calculations where data were collected during reactor on and off operations. Diverse spectral features were present during full reactor power, including a 21.4 Hz fundamental frequency and ascending harmonics. Using bandpass filters, these related frequencies were isolated and summed, and the root mean square energy was calculated. The method of isolating and summing characteristic features provided a significant improvement in identifying acoustic behavior related to reactor power when the raw signals were obscured by noise. Full article

Using a one-dimensional code, we computed the power (enthalpy discharge rate) of a twelve-cell mechanical draft cooling tower (MDCT) using over two hundred visible condensed water vapor plume volume measurements derived from images, weather data, and tower operating conditions. The plume images were simultaneously captured by multiple stationary digital cameras surrounding the cooling tower. An analysis technique combining structure from motion (SfM), a neural-network-based image segmentation algorithm, and space carving was used to quantify the volumes. Afterwards, the power output was computed using novel techniques in the one-dimensional code that included cooling tower exhaust plume adjacency effects implemented with a modified version of the entrainment function, weather data averaged from eleven stations, and fan operations at the times when plume volumes were measured. The model was then compared with the averaged observed power output, and it validated well with an average error ranging from 6 to 12%, depending on the meteorological data used in the simulations. This methodology can possibly determine power plant fuel consumption rates by applying visible imagery. Full article

The performance of air conditioning systems deteriorate due to the natural aging and wear caused by operating the devices. This is termed “aging degradation,” and it results from a lack of appropriate maintenance which accelerates the degree of performance degradation. The performance degradation of an air conditioning system can cause problems such as increased energy consumption, deteriorated indoor heating environment, and shortened lifespan of air conditioning equipment. To prevent such problems, it is important to establish a long-term maintenance plan to recover degraded performance, such as predicting an appropriate maintenance time by identifying the real-time performance degradation rate based on a system’s operation data. In this study, the performance degradation rate, according to the operating time, was estimated using long-term operation data for devices constituting a heat source system, and the effect of performance degradation of the heat source system’s operation and energy consumption was reviewed using a simulation. The performance degradation rate of the target device was estimated by analyzing the variation trend of the calibration coefficient, which was calculated when the initial performance prediction model was calibrated through operating data. Using this approach, it was confirmed that the annual performance degradation rate was 1.0–1.4% for the heat source equipment, 0.4–1.2% for the cooling towers, and 0.8–1.3% for the pumps. In addition, a heat source system energy simulation calculated the 15-year performance degradation of the heat source equipment to be 34–52% and 7–19% for both the cooling towers and pumps. Due to the equipment performance deterioration, the number of operating heat source equipment and cooling tower fans, and the pump flow rate gradually increased every year, thus accelerating the performance deterioration even further. As a result, energy consumption in the 15th year increased by approximately 41% compared with the initial energy consumption. Full article

Previous studies have been conducted by employing various methods to reduce the condenser water temperature, a crucial control variable to consider when attempting to improve the operational efficiency of a chiller. The existing literature dealing with the effects of low-condenser water temperatures is limited, as the cooling water flow rate is often considered the operating variable of the condenser loop. However, to produce additional low condenser water temperatures, the approach temperature of the cooling tower in the system must be reduced. To reduce the approach temperature, it is necessary to review the physical behavior and efficiency of the cooling tower according to the change in the liquid to gas ratio (LGR), which is dependent upon the condenser water flow rate and the cooling tower fan air flow rate within the condenser loop. However, this process has rarely been reviewed in previous studies. Therefore, this study developed a new cooling tower control algorithm from the LGR perspective, and the operational effectiveness was quantitatively reviewed using EnergyPlus. Compared to the conventional conditions, when the cooling tower operation algorithm for low-approach temperatures was applied, the annual energy saving was 27.0%, the average chiller COP was improved by 27.8%, and the average system COP was improved by 47.4%. Furthermore, even when the algorithm was not applied at the same condenser water set temperature, the annual energy saving was 15%. The average COP of the chiller and COP of the system is improved by 2% and 23.2%, respectively. These results indicated that when a cooling tower is operated with a low LGR, even under the same outdoor air and load conditions, the cooling system’s efficiency can be improved with a change in the control algorithm without installing additional high-efficiency equipment. Full article

Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to provide the best trade-offs between two conflicting objectives: maximization of the effectiveness of the cooling towers and minimization of the overall power requirement of the refrigeration system. The optimization process respects the constraints to guarantee the correct and safe operation of the equipment when the evolved solution is implemented. In this work, we apply three evolutionary multi-objective algorithms: Non-dominated Sorting Genetic Algorithm (NSGA-II), Micro-Genetic Algorithm (Micro-GA) and Strength Pareto Evolutionary Algorithm (SPEA2). The results obtained are analyzed under different scenarios and models of the cooling system’s equipment, allowing for the selection of the best algorithm and best equipment’s model to achieve energy efficiency of the studied refrigeration system. Full article

In this present work, the air-conditioning test performance of an ejector refrigerator-based air-conditioner (ERAC) was proposed. The ERAC was operated as the water chiller to produce the cooling load up to 4.5 kW. The chilled water temperature was later supplied to the fan-coil unit for producing the thermal comfort condition. The cooling water used to cool the condenser was achieved from the cooling tower which was operated under the hot and humid ambient. This is to demonstrate the feasibility of using the ERAC in real working conditions. The cooling load supplied to the air-conditioned space was applied by the air heater. The ERAC could efficiently be operated to produce the thermal comfort condition which was driven by the hot water temperature (T_hot) of 90–98 °C. The system performance could vary with the heat source temperatures, cooling load, primary nozzle, and air-conditioned space temperature. The optimal performance was determined when varying the T_hot, and, hence, the optimal T_hot was indicated. The optimal T_hot varied significantly with variations in the working condition. The test results demonstrated high potential to further using the ejector refrigeration system in the actual air conditioning application. Full article

The shift from fossil fuel to more renewable electricity generation will require the broader implementation of Demand Side Response (DSR) into the grid. Utility processes in industry are suited for this, having a large thermal time constant or buffer, and large electricity consumption. A widespread utility system in industry is an induced draft evaporative cooling tower. Considering the safety aspect, such a process needs to maintain cooling water temperature within predefined safe boundaries. Therefore, in this paper, two modelling methods for the prediction of the basin temperature of an induced draft evaporative cooling tower are proposed. Both a white box and a black box methodology are presented, based on the physical principles of fluid dynamics and adaptive neuro-fuzzy interference system (ANFIS) modelling, respectively. By analysing the accuracy of both models with a focus to cooling tower fan state changes, i.e., DSR purposes, it is shown that the white box model performs best. Fostering the idea of using such a system for DSR purposes, the concept of design for flexibility is also touched upon, discussing the thermal mass. Pre-cooling, where the temperature of the cooling water basin is lowered before a fan switch off period, was simulated with the white box model. It was shown that beneficial pre-cooling (to lower the temperature peak) is limited in time. Full article

To minimize the total energy consumption of a cooling tower-assisted heat pump (CTAHP) system in cooling mode, a model-based control strategy with hybrid optimization algorithm for the system is presented in this paper. An existing experimental device, which mainly contains a closed wet cooling tower with counter flow construction, a condenser water loop and a water-to-water heat pump unit, is selected as the study object. Theoretical and empirical models of the related components and their interactions are developed. The four variables, viz. desired cooling load, ambient wet-bulb temperature, temperature and flow rate of chilled water at the inlet of evaporator, are set to independent variables. The system power consumption can be minimized by optimizing input powers of cooling tower fan, spray water pump, condenser water pump and compressor. The optimal input power of spray water pump is determined experimentally. Implemented on MATLAB, a hybrid optimization algorithm, which combines the Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm with the greedy diffusion search (GDS) algorithm, is incorporated to solve the minimization problem of energy consumption and predict the system’s optimal set-points under quasi-steady-state conditions. The integrated simulation tool is validated against experimental data. The results obtained demonstrate the proposed operation strategy is reliable, and can save energy by 20.8% as compared to an uncontrolled system under certain testing conditions. Full article

Heated moist air from a cooling tower forms a visible plume and needs to be predicted, not only for the performance design of the cooling tower, but also for environmental impact assessments. In this study, a computational fluid dynamics analysis is conducted to predict the scale of a visible plume rising from a cross flow cooling tower with mechanical draft (provided by a rotating fan). The results of computational fluid dynamics analysis are verified by comparing predictions with an actual observed plume. The results show that the predicted visible plume represents the observed plume in an error range of 15%–20%, which is permissible for designing a cooling tower. Additionally, the mixing condition of heated dry air and moist air under dry and wet combined operation is examined, and the condition is thought to affect the scale of the visible plume. It is found that, in the case of a mechanical-draft cooling tower, the fan has a mixing function which performs the complete mixing of wet and dry air, and this suggests that the generation of the plume can be determined by the intersection of the operation line and saturation line. Additionally, the effect of external wind on the scale of the visible plume is large, especially for dry and wet combined operation. Full article

A vertical axis wind turbine (VAWT) was positioned at the discharge outlet of a cooling tower electricity generator. To avoid a negative impact on the performance of the cooling tower and to optimize the turbine performance, the determination of the VAWT position in the discharge wind stream was conducted by experiment. The preferable VAWT position is where the higher wind velocity matches the positive torque area of the turbine rotation. With the proper matching among the VAWT configurations (blade number, airfoil type, operating tip-speed-ratio, etc.) and exhaust air profile, the turbine system was not only able to recover the wasted kinetic energy, it also reduced the fan motor power consumption by 4.5% and increased the cooling tower intake air flow-rate by 11%. The VAWT had a free running rotational speed of 479 rpm, power coefficient of 10.6%, and tip-speed-ratio of 1.88. The double multiple stream tube theory was used to explain the VAWT behavior in the non-uniform wind stream. For the actual size of a cooling tower with a 2.4 m outlet diameter and powered by a 7.5 kW fan motor, it was estimated that a system with two VAWTs (side-by-side) can generate 1 kW of power which is equivalent to 13% of energy recovery. Full article