Multi-objective optimization of HVAC system with an evolutionary computation algorithm

A data-mining approach for the optimization of a HVAC (heating, ventilation, and air conditioning) system is presented. A predictive model of the HVAC system is derived by data-mining algorithms, using a dataset collected from an experiment conducted at a research facility. To minimize the energy while maintaining the corresponding IAQ (indoor air quality) within a user-defined range, a multi-objective optimization model is developed. The solutions of this model are set points of the control system derived with an evolutionary computation algorithm. The controllable input variables — supply air temperature and supply air duct static pressure set points — are generated to reduce the energy use. The results produced by the evolutionary computation algorithm show that the control strategy saves energy by optimizing operations of an HVAC system.     

Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme/model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005 〈www.archenergy.com〉]. Energy savings up to 30.4% were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied.     

Cooling output optimization of an air handling unit

A data-driven optimization approach for minimization of the cooling output of an air handling unit (AHU) is presented. The models used in this research are built with data mining algorithms. The performance of dynamic models build by four different data mining algorithms is studied. A model extracted by a neural network is selected for identifying the functional mapping between specific outputs and controllable and non-controllable inputs of the AHU. To minimize the cooling output while maintaining the corresponding thermal properties of the supply air within a certain range, a bi-objective optimization model is proposed. The evolutionary strategy algorithm is applied to solve the optimization problem with the optimal control settings obtained at each time stamp. The minimized AHU’s cooling output reduces the chiller’s load, which leads to energy savings.     

A cost‐effective operating strategy to reduce energy consumption in a HVAC system

The operation of the building heating, ventilating, and air conditioning (HVAC) system is a critical activity in terms of optimizing the building's energy consumption, ensuring the occupants' comfort, and preserving air quality. The performance of HVAC systems can be improved through optimized supervisory control strategies. Set points can be adjusted by the optimized supervisor to improve the operating efficiency. This paper presents a cost‐effective building operating strategy to reduce energy costs associated with the operation of the HVAC system. The strategy determines the set points of local‐loop controllers used in a multi‐zone HVAC system. The controller set points include the supply air temperature, the supply duct static pressure, and the chilled water supply temperature. The variation of zone air temperatures around the set point is also considered. The strategy provides proper set points to controllers for minimum energy use while maintaining the required thermal comfort. The proposed technology is computationally simple and suitable for online implementation; it requires access to some data that are already measured and therefore available in most existing building energy management and control systems. The strategy is evaluated for a case study in an existing variable air volume system. The results show that the proposed strategy may be an excellent means of reducing utility costs associated with maintaining or improving indoor environmental conditions. It may reduce energy consumption by about 11% when compared with the actual strategy applied on the investigated existing system. Copyright © 2007 John Wiley & Sons, Ltd.     

Parametric study of kW-class solid oxide fuel cell stacks fueled by hydrogen and methane with fully multiphysical coupling model

Multiphysics models are important tools for the design and optimization of solid oxide fuel cells (SOFCs). The computational efficiency of a sophisticated multiphysics model is improved by a factor of 4 by symmetry utilization and grid optimization, allowing its routine use for the analysis and diagnosis of industrial-sized SOFC stacks. The predictive power of the model is tested by the experimental data. Parametric numerical studies, together with indepth theoretical analyses, on the performance characteristics of kW-class stacks fueled by H₂ and CH₄ are carried out with this accurate model. It is concluded: (1) CH₄ is advantageous for providing lower maximum temperature and temperature gradient, and higher energy efficiency. (2) H₂ is advantageous for generating more electricity and being more resistant to fuel starvation. (3) Insufficient air supply can cause high thermal gradient. (4) Fuel uniformity is critically dependent on the stack design and affects all aspects of stack performance.     

Neuro-optimal operation of a variable air volume HVAC&R system

Low operational efficiency especially under partial load conditions and poor control are some reasons for high energy consumption of heating, ventilation, air conditioning and refrigeration (HVAC&R) systems. To improve energy efficiency, HVAC&R systems should be efficiently operated to maintain a desired indoor environment under dynamic ambient and indoor conditions. This study proposes a neural network based optimal supervisory operation strategy to find the optimal set points for chilled water supply temperature, discharge air temperature and VAV system fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.     

高寒地域静冰压力对输电塔影响的数值分析

以大庆地区输电线路铁塔入冬后底部结冰致使输电塔遭到破坏为例,建立冰层—输电塔腿模型,并运用有限元分析软件ANSYS分析水结冰产生静冰压力对输电塔的影响。模拟结果表明,冰层因温度升高而膨胀从而产生静冰压力,冰层在冻结过程中对置于其中的输电塔产生横向剪切作用,致使塔材产生弯曲,从而改变了输电铁塔塔材原有的传力方式,塔腿部分在铁塔自重、风荷载与静冰压力组合作用下发生破坏和变形,严重时可导致输电塔倒塔,从而影响供电可靠性。     

Simulation and experimental research on energy conversion efficiency of scroll expander for micro‐Compressed Air Energy Storage system

A scroll expander was applied to the Micro‐Compressed Air Energy Storage system, and its energy conversion efficiency was investigated. In order to study the variation mechanism of the volume, mass, pressure and temperature of the air in different chambers, the mathematical model of the expansion process was developed on the base of the geometric model, mass conservation equation, ideal gas equation and energy conservation equation. Then, the mathematical model was implemented in Matlab, and the simulated energy conversion efficiency defined as the ratio between the output shaft power of the scroll expander and the input compressed air power was obtained. Furthermore, a test system was built in order to validate the mathematical model and study the improvement of the energy conversion efficiency. The prototypes of the scroll expander with different cross‐sectional areas of the intake port or the discharge port were fabricated and tested in the experiments. Results show that the simulated torque and energy conversion efficiency agree well with the experimental results. Also, there is a small deviation between the expansion process and the ideal isentropic process due to the gas leakage, intake and discharge loss. In addition, the air supply pressure and the cross‐sectional area ratio of the discharge port to the intake port are two important parameters for the improvement of the energy conversion efficiency. The experiments show that the energy conversion efficiency varies from 23% to 36% at the air supply pressure of 0.35 to 0.65 MPa, indicating that it is proportional to the air supply pressure. It can also be concluded from the experiments that when the air pressure is higher than 0.45 MPa, the ideal ratio range can be determined as 0.6‐0.8. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulation of a new biomass integrated gasification combined cycle (BIGCC) power generation system using Aspen Plus: Performance analysis and energetic assessment

A new biomass integrated gasification combined cycle (BIGCC), which featured an innovative two-stage enriched air gasification system coupling a fluidized bed with a swirl-melting furnace, was proposed and built for clean and efficient biomass utilization. The performance of biomass gasification and power generation under various operating conditions was assessed using a comprehensive Aspen Plus model for system optimization. The model was validated by pilot-scale experimental data and gas turbine regulations, showing good agreement. Parameters including oxygen percentage of enriched air (OP), gasification temperature, excess air ratio and compressor pressure ratio were studied for BIGCC optimization. Results showed that increase OP could effectively improve syngas quality and two-stage gasification efficiency, enhancing the gas turbine inlet and outlet temperature. The maximum BIGCC fuel utilization efficiency could be obtained at OP of 40%. Increasing gasification temperature showed a negative effect on the two-stage gasification performance. For efficient BIGCC operation, the excess air ratio should be below 3.5 to maintain a designed gas turbine inlet temperature. Modest increase of compressor pressure ratio favored the power generation. Finally, the BIGCC energy analysis further proved the rationality of system design and sufficient utilization of biomass energy.     

Optimization of fuel cell system operating conditions for fuel cell vehicles

Proton exchange membrane fuel cell (PEMFC) technology for use in fuel cell vehicles and other applications has been intensively developed in recent decades. Besides the fuel cell stack, air and fuel control and thermal and water management are major challenges in the development of the fuel cell for vehicle applications. The air supply system can have a major impact on overall system efficiency. In this paper a fuel cell system model for optimizing system operating conditions was developed which includes the transient dynamics of the air system with varying back pressure. Compared to the conventional fixed back pressure operation, the optimal operation discussed in this paper can achieve higher system efficiency over the full load range. Finally, the model is applied as part of a dynamic forward-looking vehicle model of a load-following direct hydrogen fuel cell vehicle to explore the energy economy optimization potential of fuel cell vehicles.     

Energy consumption reduction of a PEM fuel cell motor-compressor group thanks to efficient control laws

This paper deals with the energy optimization of an embedded fuel cell generator. To reach this aim, experimentally validated models of a low power 5 kW proton exchange membrane fuel cell (PEMFC) and its most power hungry ancillary (motor-compressor group) are described. All simulation results have been performed using Matlab/Simulink^® environment. Moreover, a control strategy of the air supply circuit integrated in an embedded fuel cell system is proposed. The air flow control of the air supply circuit is built around a fuzzy PD + I controller and for the air supply set point determination, a fuzzy supervision is proposed. The parameters of this fuzzy supervision have been optimized thanks to particle swarm optimization (PSO) method.     

数据机房热区内气流组织的数值模拟及优化

建立数据机房热区内气流流动和传热的物理及数学模型,利用Fluent软件模拟其热区内气流的速度、温度和压力分布,模拟值和实测值相吻合。针对模拟数据机房热区内气流组织的缺点,从节能的角度提出改善方案,再通过Fluent软件模拟分析。研究结果表明：数据机房热区内最佳空调送风风速为3.6 m/s;SUN4900服务器的最佳放置方式是全交错放置且全交错距离为0.3 m。     

特高压柔直阀厅空调喷口侧送气流组织模拟及优化

[目的]特高压柔直阀厅具有高度高、体积大、设备发热量大等特点,阀厅内空调送风方式可显著影响室内温度场、风速场、压力场,研究其送风方式对于保证阀厅内发热设备的正常运行至关重要.[方法]使用Ansys Fluent 19.2对球形喷口水平侧送方式下的阀厅进行模拟仿真,分析其温度场、风速场、压力场存在的问题.本次研究设置三种...     

Model-based optimal control of a dedicated outdoor air-chilled ceiling system using liquid desiccant and membrane-based total heat recovery

This study presents a model-based control strategy for a novel dedicated outdoor air-chilled ceiling (DOAS-CC) system with the aim of optimizing the overall system performance. The DOAS-CC system incorporates liquid desiccant dehumidification and membrane-based total heat recovery technologies. Simplified but reliable models of major components in the DOAS-CC system are firstly developed to predict the system performance. A cost function is then constructed to minimize total energy consumption while properly maintaining thermal comfort reflected by indoor air temperature and relative humidity. Genetic algorithm is used to search for optimal set-points of the supply air temperature and humidity ratio of the dedicated outdoor air subsystem as well as the supply water temperature. The performance of this strategy is tested and evaluated with different control settings in a simulated multi-zone space served by the DOAS-CC system under various weather conditions. The results show that optimized control variables produced by the optimal strategy can improve the system energy performance and maintain indoor thermal comfort.     

Numerical simulations of solar chimney power plant with radiation model

A three-dimensional numerical approach incorporating the radiation, solar load, and turbine models proposed in this paper was first verified by the experimental data of the Spanish prototype. It then was used to investigate the effects of solar radiation, turbine pressure drop, and ambient temperature on system performance in detail. Simulation results reveal that the radiation model is essential in preventing the overestimation of energy absorbed by the solar chimney power plant (SCPP). The predictions of the maximum turbine pressure drop with the radiation model are more consistent with the experimental data than those neglecting the radiation heat transfer inside the collector. In addition, the variation of ambient temperature has little impact on air temperature rise despite its evident effect on air velocity. The power output of the SCPP within the common diurnal temperature range was also found to be insensitive to ambient temperature.     

变风量空调系统中的实时优化节能控制

在对变风量空调系统局部控制的分析基础上,利用其变风量末端风门的开度作为各区域相对负荷的指示信号,提出送风静压的实时优化控制方案;同时,针对新的ＡＳＨＲＡＥ通风标准,还提出了基于室内人数检测和焓控制的新风实时优化控制方案。试验结果证明,同常规的控制方案相比,在保证室内热舒适性和空气质量的前提下,这两个方案分别有较好的节能作用。综合采用两种优化方案,系统不仅能够达到节能的目的,而且在较小负荷情况下能够提高室内空气的品质。     

Development of strategies for reducing air pollutant emissions in the European community

In view of increasing economic and environmental problems, energy supply strategies as well as air pollutant emission reduction strategies are required. These strategies should be designed in accordance with the specific development of a country or region. In the past they were mainly considered with respect to the finiteness of natural resources and the scarcity of economic resources. In recent years the ‘joint-production’ of air pollutant emissions in the energy sector has been increasingly recognized as an additional argument. As a consequence, concepts on future energy pathways, which should be efficient with respect to both economic development and environmental protection, have to be devised. For this purpose energy-environmental models such as EFOM-ENV can be used as analytic tools. The paper discusses optimal future energy supply structures that result from different strategies for air-pollution control in the countries of the European Community. The results have been obtained by applying the energy flow optimization model (EFOM), which has been extended by additional environmental modules to EFOM-ENV. The issues of the paper are based on research activities that the authors are performing for the Commission of the European Communities (CEC), Brussels, and the European Research Center for Air Pollution Control Measures (PEF), Karlsruhe, in close co-operation with research institutes in member countries of the European Community.     

太阳能等效转化利用模型及其效益研究

以能源局域网为依托,研究太阳能在转化利用过程中不同“能质”能量之间的等效转化关系及其效益模型。综合考虑负荷需求特性及当前能源消费价格因素对太阳能利用方式的影响,以太阳能利用率最大和系统运行综合效益最大化为目标,构建太阳能转化利用多目标优化模型;然后,采用量子行为的粒子群优化算法对模型进行优化求解,并与传统单一供能模式进行对比分析。结果表明,所提模型能有效提高能耗系统对太阳能的综合利用率及消纳能力,并取得更高的能售效益。验证了所提模型及其运行方式的有效性和可行性,为大规模太阳能的开发和利用提供了一个新的思路。     

A development toolchain for a pulsed injector-ejector unit for PEM fuel cell applications

The anode subsystem of PEM fuel cells has to supply hydrogen in the required temperature, pressure, mass flow and concentration range under all operating conditions. At present, several components such as valves, sensors and a recirculation pump/blower (active recirculation) secure the supply, which consumes a significant amount of energy and reduces the overall efficiency. Passive recirculation with a pulsed injector-ejector unit is a promising approach to guarantee the required supply while maintaining low energy consumption. However, high development efforts are necessary to design and optimize an injector-ejector for the entire operating range. This paper proposes a novel development toolchain consisting of simulation models and experimental validation. In addition, simulation and measurement results are within a 2% accuracy for the stoichiometric ratio at nominal power. Further, the results show that recirculation covers the entire operating range. This toolchain enables accurate design and optimization of injector-ejector units saving development time and costs.     

Survey of experimental data and assessment of calculation methods of properties for the air–water mixture

Thermodynamic properties of the air–water mixture at elevated temperatures and pressures are of importance in the design and simulation of the advanced gas turbine systems with water addition. In this paper, comprehensive available experimental data and calculation methods for the air–water mixture were reviewed. It is found that the available experimental data are limited, and the determined temperature is within 75 °C. New experimental data are needed to supply in order to verify the model further. Three kinds of models (ideal model, ideal mixing model and real model) were used to calculate saturated vapor composition and enthalpy for the air–water mixture, and the calculated results of these models were compared with experimental data and each other. The comparison shows that for the calculation of saturated vapor composition, the reliable range of the ideal model and ideal mixing model is up to 10 bar. The real model is reliable over a wide temperature and pressure range, and the model proposed by Hyland and Wexler is the best one of today. However, the reliability of the Hyland and Wexler model approved by experimental data is only up to 75 °C and 50 bar, and it is necessary to propose a new predictive model based on the available experimental data to be used up to elevated temperatures and pressures. In the calculation of enthalpy, compared to the ideal model, the calculated results of the ideal mixing model are closer to those of real model.