Fan Energy Consumption Research Articles

A proactive 2-stage indoor CO2-based demand-controlled ventilation method considering control performance and energy efficiency

This paper presents a novel method, named proactive 2-stage demand-controlled ventilation (P2S-DCV) method, to maintain indoor air quality (IAQ) and reduce the energy consumption of multi-zone ventilation systems. The proposed P2S-DCV method applies a proactive control scheme, which predicts future indoor CO2 concentration and supplies proper ventilation to each zone. The method includes two stages. In Stage I, a DNN prediction model is established to predict the future CO2 concentration to calculate the corresponding demand airflow. In Stage II, a reinforcement learning method is designed to achieve rapid and accurate control, and further reduce the energy consumption by optimizing the fan pressure and damper positions. A 5-zone ventilation system is established to validate the proposed P2S-DCV method. The experiment verifies that: a) it can maintain comfortable IAQ via predicting the change of future indoor CO2 and applying effective ventilation control in advance; b) it can improve the control performance, the accuracy is maintained within 8 % (satisfied the ASHRAE Standards), and the control time is maintained within minutes. It can reduce the regulating time by 83.62 % compared with ASHRAE Ratio method, and up to 51.68 % compared with PID method; c) it can reduce the fan energy consumption by 16.4 % compared with ASHRAE Ratio method, and up to 21.8 % compared with PID method; d) it has good generalization ability for various IAQ requirements and ventilation systems with different topologies.

Decision-making analysis of air supply strategies for high rack cold stores

The thermal performance of a high rack cold store is related to the quality of fresh fruit and vegetable preservation. As the complex air supply strategies, a comprehensive evaluation of the thermal and airflow performance needs more than one demand. Therefore, the Z-score method was used to evaluate the thermal and airflow performance of the high rack cold store in this paper. The Z-score considered the energy utilization coefficient, non-uniformity coefficient and Air Diffusion Performance Index (ADPI). Firstly, a numerical simulation model of a high rack cold store was developed and validated. The effects of air supply form, air supply angle and air supply velocity on thermal performance and flow properties were then investigated. The velocity, temperature and pressure distribution were analyzed. Based on the previous data, the air supply strategies of the high rack cold store were evaluated with the proposed Z-score method, and the results proved that it could be utilized as the multi-indicator comprehensive analysis method for the high rack cold store. The cooling effect and the thermal uniformity of the vertical wall attached ventilation was excellent in a high rack cold store. When the air supply angle is −90°, the high rack cold store has a more uniform and reasonable temperature field. Considering the energy consumption of fans, the optimal air supply velocity was 11.7 m·s−1. Those results could provide a reference for the design of air supply form in the high rack cold store.

Optimization of supply air flow and temperature for VAV terminal unit by artificial neural network

The purpose of this paper is to optimize the supply air flow rate and temperature of the variable air volume (VAV) terminal unit by artificial neural network (ANN). In general, the setpoint of the VAV terminal unit are supply air flow rate and supply air temperature. These setpoints are determined by the design value, and are calculated by the maximum indoor heating/cooling load and the ventilation requirements. The setpoints calculated based on the design value does not cause any problems in maintaining the indoor environment. However, energy consumption cannot be optimized because it is based on the maximum design value. In order to improve the existing control method, it is important to apply the setpoints according to the real time indoor conditions. The real time indoor condition can be utilized for control through prediction model. In this study, the indoor load, indoor air quality and energy consumption were predicted and used for VAV system control. In addition, the predictive model was developed with the ANN algorithm, and the process of selecting input data and optimizing the predictive model was performed. The performance of the ANN based optimal control algorithm (suggested CASE) for the VAV terminal unit in the target building was compared with those of the dual maximum control algorithm (existing CASE), one of the VAV terminal unit control algorithms. The comparison of heating season showed that the ANN based control algorithm of VAV terminal unit reduced 16.7% of supply fan energy consumption and 19.5% of reheat coil energy consumption compared to the existing CASE using the fixed setpoint.

Optimal energy management for air cooled server fans using Deep Reinforcement Learning control method

The current study proposed the Deep Reinforcement Learning (DRL) AI control algorithm for energy-saving optimization in 1U air-cooled server mockup for different configurations and scenarios. The proposed algorithm can handle the server's complex thermal environment, including number of heat sources and their locations, type of heat sink, airflow, fan and bypass airflow. Based on the analysis and test results, it is found that controlling a single fan individually and the fans in different zones can offer the reduction of fan energy by 39–47% compared with the controlling all fans collectively. After the modification in observation characteristics, the fan usage rate was reduced by 45% compared with the single fan control model. Further, five different control models were developed and tested with experiments for different function variables and reward functions on three server configurations with different algorithmic settings for energy saving optimizations. The heat source of the three server configurations was close to the upper limit temperature and maintained stably by saving about 12% to 50% fan energy consumption. The algorithm can judge the system status and successfully provide real-time decision-making action thereby the energy consumption of the fan is significantly reduced.

Model predictive control for multi-zone Variable Air Volume systems based on artificial neural networks

In this paper, an artificial neural network (ANN) based system-level model predictive control framework is established for a variable air volume (VAV) system to improve its robustness and energy efficiency. The VAV system consists of three processes: the zone temperature process, the damper process and the supply air volume process of the air handling unit connecting the ductwork for all of the boxes. An ANN-based predictive controller is designed for the zone temperature process, and a PI controller is used for the damper process; they operate in a cascaded manner. Another ANN predictive controller tracks the total supply air volume subject to the cooling load constraints from the lower level VAV boxes and minimizes the fan energy consumption. The ANN controllers are optimized online by the Lagrange variational approach (LVA) to minimize the system cost function and implement a feedback receding horizon optimal control. With the LVA based gradient descent training algorithm, the weight convergence of the ANN predictive controllers and stability of the control system is obtained with small computational and storage needs. The modeling methodology, based on ANNs for the above processes, is developed and calibrated with actual data measured from a site. All of the data processing and control strategy implementations are based on extensive measurements collected from a laboratory building located in the campus of Beijing University of Civil Engineering and Architecture, Beijing, China. The experimental results show that an additional 6.12% energy savings is achieved. This is accomplished by introducing the fan control signal into the system cost function as the performance index of energy consumption with a 0.2 penalty coefficient. In the presence of un-modeled disturbances and modeling errors, the framework also reduces the temperature oscillation at least by approximately 60% compared with PI control.

Energy-efficient air conditioning system using a three-fluid heat exchanger for simultaneous temperature and humidity control

Room air conditioners are unable to simultaneously control the temperature and humidity of the air supply. Although temperature-regulating dehumidifiers can simultaneously control the temperature and humidity, they have complex refrigerant pipelines, and the heat exchanger exhibits air resistance when the reheat demand is low. This study proposes an air conditioning system for simultaneous temperature and humidity control, using a three-fluid heat exchanger. The supply air temperature is adjusted by changing the air volume ratio and cooling water flow rate through the three-fluid heat exchanger, which is used as the condenser. Free cooling can be realized by supplying low-temperature cooling water to treat the return air. Numerical models were built to simulate the performance of the devices in the system, and were validated by experimental results. The temperature-regulating performance and energy consumption under different conditions were numerically calculated using a case-studied air-conditioned room in Beijing. The results are summarized as follows: 1. The proposed strategy can regulate the supply air temperature over a wide range of temperatures. 2. Compared with those of the temperature-regulating dehumidifier system, the compressor and fan energy consumption of the proposed system are reduced by 19.1% and 15.5%, respectively, with a total energy-saving rate of 15.8% in the cooling season. 3. Compared with those of the room air conditioner system, the compressor energy consumption of the proposed system is reduced by 11.5%, and the energy-saving rate of the entire system is 6.3%. The initial investment of the proposed system does not increase significantly compared with conventional systems, and the refrigerant pipeline and valves can be simplified, resulting in acceptable economic performance for the proposed system.

Directions of mine ventilation development

Introduction. Underground mining is carried out under conditions of intensive development of gas from combustion-engined vehicles and blasting operations, as well as under dust pollution and workplace temperature that violate health and safety regulations. Aerological safety provision by improving mine ventilation efficiency is therefore highly relevant. Methods of research. It is reasonable to ventilate a multi-horizon mine using an automated horizon ventilation system that is responsible for the compliance of aerological conditions in workplaces with the safety requirements and consists of centralized and decentralized blocks. Research results and analysis. The centralized block redistributes air flows between entries of a horizon. The decentralized block is a set of auxiliary fans represented by intelligent mechatronic modules supplying fresh air to the workplaces. The intellectualization of the auxiliary fan places high demands on the quality of the air duct, because the efficiency of ventilation in the workplace depends on its reliable functioning. Conclusions. Air duct made of hydraulically smooth polymer units sealed with each other allows to minimize auxiliary fan energy consumption under guaranteed supply of the required amount of air into the workplace. Horizon ventilation computer-aided control and auxiliary fans with sealed polymer air ducts will make it possible to create systems with the most advantageous combination of cost and quality

Estimating Energy Consumption of Mine Fans in Underground Mines in Case of Uncertainty of Fan Influence Zones

Estimating Energy Consumption of Mine Fans in Underground Mines in Case of Uncertainty of Fan Influence Zones

Optimizing the overall performance of forced extraction systems: A multi-objective framework

A Multi-Objective Optimization (MOO) framework is proposed in this study, for optimization of the overall performance of forced extraction systems used in the kitchen environment. The target of the proposed framework is to achieve a balance (trade-off) among three conflicting objectives: minimization of discomfort, minimization of energy consumed by the extraction system fan, and minimization of the gradient in temperature and CO2 profiles, within the kitchen environment, during extraction system operation. To this end, the objectives are formulated in terms of criterion (objective) functions, using certain variables including: target/reference signals (set-points) and ambient environmental conditions. The balance between the objectives is obtained by determining the optimal values of these reference signals. A well known meta-heuristic called Non-dominated Sorting Genetic Algorithm (NSGA)-II is used for this purpose. Performance of the proposed multi-objective framework is simulated by using the best optimal values of the reference signals (i.e., the knee-point solution), evaluated by the framework, in the Computational Fluid Dynamics (CFD) model of the kitchen environment, developed using FloVENT™, which is validated against the experimental data collected from a test room (kitchen). The results of the investigation show that the optimal fan operation, is able to maintain an overall balance between the comfort, fan energy consumption and the gradient (in temperature and CO2 concentration) within the kitchen.

Fluidization Dynamics of a New Two-Staged Fuel Reactor for Chemical Looping Gasification

A new staged fuel reactor (FR), which integrates a bubbling bed and a spouted fluidized bed, is proposed in the present work with regard to lowering the pressure drop of the staged FR during chemical looping applications. In order to gain insights into the gas–solid fluid dynamics of the new design, a cold experimental setup was established. The fluidization dynamics of the staged FR was investigated based on the pressure pulsation signal analysis using time domain analysis, power spectral density analysis, wavelet analysis, and the Hurst exponent analysis by the R/S method. There are four flow types of funnel-like flow, spout-fluidization, spouting motion, and unsteady spouting motion to be classified, and the transition boundaries of the corresponding flow types were determined. The design provides a way to lower the overall pressure drop of FR and then reduces the fan energy consumption to hold the oxygen carrier particle circulation.

Safety and Energy Implications of Setback Control in Operating Rooms during Unoccupied Periods

Health care facilities are high energy-demanding buildings. The energy-saving potential is limited due to safety regulations, especially in critical care areas like operating rooms (ORs). Reducing the supply airflows during unoccupied periods, also called ventilation turndown or setback, is accepted as an energy efficiency measure as long as it does not compromise the pressure relationship. In addition, temperature and relative humidity setbacks can introduce further energy savings. This work aims at studying the effect that a setback has on the OR-positive pressure and the savings achievable in both the energy supply and CO2 emissions. Towards this target, five tests are performed in two ORs of a public hospital during the summer, winter, and midseason. A setback is applied on the basis of an occupancy sensor, and the pressure difference from the OR adjacent spaces is monitored. The outdoor and supply air conditions and airflows, as well as fan energy consumption, are measured. Punctual pressure relationship losses are observed during the occupied periods due to doors opening but not during ventilation setback operations. The energy savings achieved accounted for 75% of the natural gas consumption and 69% of the electricity in the ORs. The yearly estimations imply economic savings of near 20,000 EUR and more than 100 tons of CO2 emissions.

Calibration of building energy simulation model for a mechanically ventilated livestock facility

To enhance the productivity of livestock facilities, maintaining a comfortable indoor environment is necessary, as livestock are sensitive to indoor temperature and livestock excrement generates numerous pollutants. In most livestock facilities, the ventilation system represents a large proportion of the indoor environment. Therefore, an energy-efficient ventilation control system, which considers the performance of the ventilation fan and outdoor air conditions, is increasingly in demand. In this study, we developed a building energy simulation model for ventilation control system in a livestock facility. In addition, a polynomial equation for the part-load-factor according to the part-load-ratio was developed to calibrate the fan energy consumption. The indoor temperature prediction performance was calibrated by optimising the infiltration rate and equipment load variables. The proposed building energy simulation model is expected to contribute to energy reduction and productivity improvement of the livestock by determining the optimum fan operation schedule through simulation analysis of various factors. • A whole-building energy model for livestock facility was developed. • PLF model was applied in the energy model and showed high prediction performance. • High prediction performance for air temperature was secured by input optimization. • Daily model update better represents trend of indoor air temperature than weekly update.

Energy consumption in relation to the number of stacked packages in forced air pre‐cooling of apples

AbstractTo better investigate the effect of the number of stacked packages on the seven‐eights cooling time and the specific fan energy consumption in forced air pre‐cooling (FAC), a three‐dimensional model of FAC in the stacked packages was developed. The predicted total pressure loss was less than the product of the number of stacked packages and the pressure loss of a single package. This was due to the pressure loss of the cold air flowing through the openings in the adjacent packages accounting for the dominant proportion of the stacked packages. The difference was used to prove the overestimation of the specific fan energy consumption calculated in terms of the product of the number of stacked packages and the pressure loss of a single package. In terms of the required parameters in the pre‐cooling industry, the optimal condition of three stacked packages at the air velocity of 1.0 m/s was suggested. Compared with the other complied conditions, the specific fan energy consumption of the optimal condition was reduced by more than 50% and 0.0289–0.975$ t−1, respectively.Practical applicationsForced air pre‐cooling was an effective way to retain freshness and to improve the economic benefit of horticultural products. The quantitative relationships among the number of stacked packages, the pressure loss, and the fan energy consumption were obtained by computational fluid dynamics (CFD) simulation. Based on the results, the optimal condition in forced air pre‐cooling of apples was suggested.

Comprehensive energy and economic assessment of CRAH bypass method in air-cooled data centers

The computer room air handling (CRAH) bypass (BP) method is a method to reduce the fan energy consumption in data centers. To provide a fraction of the server airflow, CRAH BP fans typically operate across an order of magnitude lower pressure drop across floor tiles compared to that across CRAH units. However, at a higher fraction of BP airflow, CRAH units are subject to low-temperature operation, which poses an optimization problem. Earlier studies indicated the potential to reduce the total cooling energy consumption in air-cooled data centers by using the CRAH bypass method. This study provides the most comprehensive assessment of the CRAH BP method in the literature for air-cooled data centers based on detailed thermodynamic modeling using hour-by-hour annual energy simulations. The parametric modeling and optimization results in this study address energy and economics of induced and forced BP methods in open and enclosed-aisle data centers considering both economized and non-economized operations. Despite the significant energy-saving potential of the CRAH BP method, economics plays a pivotal role in the feasibility of such an investment. The results and following discussions provide design considerations for the successful application of the CRAH BP method in air-cooled data centers.

Estimating Energy Consumption of Mine Fans in Underground Mines in Case of Uncertainty of Fan Influence Zones

Estimating Energy Consumption of Mine Fans in Underground Mines in Case of Uncertainty of Fan Influence Zones

Industry-scale production of a perovskite oxide as oxygen carrier material in chemical looping

How to upscale the production of oxygen carrier particles from laboratory level to industrial level is still challenging in the field of chemical looping. The upscaled oxygen carrier must maintain its physical and chemical properties. In the present contribution, a spray drying granulation protocol was developed to produce a perovskite oxygen carrier (CaMn0.5Ti0.375Fe0.125O3-δ) at an industrial scale. The micro-fluidized bed thermogravimetric (MFB-TGA) experiments were performed to measure the oxygen uncoupling and redox reaction kinetics under the fluidization state with enhanced heat and mass transfer, and the obtained experimental data at different temperatures were fitted by a fluidized-bed reactor coupled with a semi-empirical kinetic model. The physical and chemical properties of granulates were compared with those of the same perovskite composition prepared at the laboratory level. The results show the volume fraction of particle size at 75–500 μm is greater than 90% for the upscaled granulats, and the particles show no degradation in reactivity and no agglomeration for more than 20 redox cycles at high temperatures. The heterogeneous reaction rates are high, especially for the oxidation, e.g. it only spent ∼ 5 s to achieve full oxidation. Low attrition index of 3.74 wt% was found after the five-hour attrition test. The industrial-scale particles possess similar chemical and physical properties as the laboratory-scale particles with regards to the reaction kinetics, attrition index, crystalline phase, etc. The required bed inventories and fan energy consumption were finally estimated and found to be lower than other oxygen carriers reported in the literature.

Study of heat transfer during steam condensation in the tubes of diesel radiator cores

The article contains an assumption about the practicability of using the processes of boiling and condensation of the coolant in the cooling system of a locomotive diesel in order to reduce the energy consumption of fans of the refrigerating chamber. The possibility of using of standard radiator cores of a diesel locomotive with flat tubes as steam condensers is considered. The results of the criterion equation of heat transfer from steam to a flat tube during condensation, obtained by the mathematical model of this process, are estimated. The assessment was carried out by comparison with experimental data. The influence of the initial steam velocity, the corresponding tube diameter, the working length of the tube, the physical properties of steam and condensate is considered. The comparison of the influence of these factors on heat transfer in round and flat tubes of a locomotive radiator core is carried out. The processed results of physical and numerical experiments for both circular and flat tubes are shown in the graphs and regression equations. The advantage of flat tubes over round ones in terms of heat transfer intensity during steam condensation, which can reach 24%, for a standard radiator core of a diesel locomotive was found.

Improving Building Energy Performance Using Dual VAV Configuration Integrated with Dedicated Outdoor Air System

As building systems account for almost half of the total energy consumed by the building sector to provide space heating, cooling, and ventilation, efficiently designing these systems can be the key to energy conservation in buildings. Dual VAV systems with an effective control strategy can substantially reduce the energy consumption in buildings, providing a significant scope of further research on this system configuration. This paper proposes to utilize the warm air duct of the dual VAV system as a dedicated outdoor air (DOA) unit when no heating is required, which allows the cooling load to be effectively distributed between two ducts. A specific control sequence is proposed with different supply air temperature reset strategies to estimate the heating, cooling loads, and fan power energy consumption of the proposed system. A simple two-zone office building is taken as a preliminary case study to simulate the airflow rates and fan power of a single duct VAV and proposed dual VAV systems to illustrate the concept. Finally, a larger multi-zone office building is simulated to measure the annual heating, cooling loads, and fan power energy and compare the energy savings among the systems. The results show significant fan power reduction ranging from 1.7 to 9% and notable heating energy reduction up to 76.5% with a small amount of cooling load reduction varying from 0.76 to 2.56% depending on the different locations for the proposed dual VAV systems. Further energy savings from different supply air temperature reset strategies demonstrate the opportunity of employing them according to climates and case studies. The proposed dual VAV system proves to have the potential to be adapted in buildings for the purpose of sustainability and energy savings.

Air-Cooled Loop Thermosyphon Cooling System for High Heat Load CPUs—Part I: Design and Performance Simulation

This article proposes and evaluates the thermal-hydraulic performance of a compact, lightweight, and high heat-transfer capacity cooling system for central processing unit (CPU) temperature control. The cooling loop, defined as a closed loop thermosyphon (LTS), has a passive flow driven mainly by the buoyancy in the riser. It is a self-modulated system, i.e., without heat flow ceases but it increases with increasing heat load. The LTS is a partially passive system since energy is still required to drive the fan blowing air through its condenser. The main advantage relative to conventional forced air-cooled heat spreaders is its ability to transfer much higher levels of heat while consuming less fan power. The innovative patented LTS system has two thermosyphon loops working in parallel, composed of a multimicrochannel evaporator, a multiport tube louvered fin condenser, two risers, and one downcomer. The simulations show that it is able to cool 600 W from a 50 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 50 mm CPU footprint without dryout or surpassing the critical heat flux. It was specifically simulated for a CPU of 2U server, considering a height of only 66 mm and width of 214 mm. Thus, two of these units can be installed side-by-side in a 2U server, which means a total cooling capacity of 1200 W per server. Several simulations are presented showing the high thermal-hydraulic performance of the LTS and a case study showing the reduction of fan energy consumption when comparing the proposed LTS with an actual air-cooled heat spreader system. The LTS was prototyped, experimentally tested, and its simulations successfully validated in Part II of this study.

Changes in Fan Energy Consumption According to Filters Installed in Residential Heat Recovery Ventilators in Korea

In recent years, because of outdoor ultrafine particles, residential heat recovery ventilators (HRVs) have been used with high efficiency filters by residents in Korea. However, as pre-filters are primarily used in residential HRVs, when a high-efficiency particulate air (HEPA) filter is installed, the filter pressure drop increases, reducing the airflow rate, which requires the fan to draw more power to maintain the airflow rate. Therefore, in this study, the change in power usage of HRVs installed in residential apartments in Korea with various air volumes and filters were analyzed. The results show that HEPA filters consumed 13.5–17.5% (16.1% on an average), 11.8–16.0% (13.8% on an average), and 16.8–41.3% (30.1% on an average) more power at 0.5, 1.0, and 1.5 air changes/h, respectively, than the pre-filter. These results indicate that unexpected power consumption increase could be caused if a pre-filter is replaced with a HEPA filter in residential small air-volume HRVs. This may lead to noise or failure due to fan overload. Thus, it is necessary to operate residential HRVs at the optimum air volume according to the fan performance.