地表水水源热泵输配系统优化模型的研究

以输配能耗最小为目标,室内舒适和建筑节能相关要求为约束条件,利用MATLAB的优化工具箱,对地表水水源热泵输配系统的优化模型进行研究,确定影响地表水水源热泵输配系统能耗的主要因素。应用此方法对水源热泵实验系统进行了应用分析,得到了系统随负荷率变化的冷却水和冷冻水变流量优化运行方案。对于大部分时间处于部分负荷运行的系统,优化运行比定流量运行可减少能耗10%以上。该优化模型能方便地应用于实际工程,为输配系统的设计和运行提供最佳参数,实现随负荷变化的流量调控,从而有效降低水源水输配能耗,提高系统能效。     

一次泵变频调速变流量系统的节能优化

以一定制冷量时的冷却水泵、冷冻水泵和冷水机组总能耗最小为最优化目标，选取冷却水流量率、冷冻水出口温度和冷冻水流量率为优化参数，建立了一次泵变频调速变流量系统总能耗的优化模型，并利用MATLAB（Matrix laboratory）为平台编制了数学模型解算程序。以一负荷率为80％的实际制冷系统为例进行分析，结果表明，当负荷减少时，合理减少水泵流量、降低水泵能耗可以使空调系统的运行费用大大降低。     

化纤厂节能问题探讨

根据化纤厂暖通空调系统是企业能耗大户的特点，对热力系统冷凝水回收利用与采暖耗能、冷冻系统制冷机组本身性能优化及工艺运行调节、冷冻水和冷却水系统的水质控制及循环冷却塔的性能优化、空调系统过渡季节节能等方面进行分析，总结出耗能原因，并提出相应的节能措施。     

一次泵变频调速变流量系统的节能优化

以一定制冷量时冷却水泵、冷冻水泵和冷水机组总的能耗最小为最优化目标，选取冷却水流量率、冷冻水出口温度和冷冻水流量率为优化参数，建立了一次泵变频调远变流量系统总能耗的优化模型，利用MATLAB（Matrix laboratory）为平台编制了数学模型解算程序。以一负荷率为80%的实际制冷系统为例进行分析，结果表明，当负荷减少时，合理减少水泵流量、降低水泵能耗可以使空调系统的运行费用大大降低。     

数据中心冷冻水系统高效安全与节能优化

数据中心设计的首要目标是通过冗余设计来确保系统的可靠性。对目前的制冷系统策略而言,确保系统可靠性的关键途径是确保制冷设备能切实维持精确的环境条件(温度和湿度)。CRAC机组持续采用制冷、加湿和制热系统相互协作,共同维持关键环境条件的策略,造成过度能源消耗。即使CRAC机组内置EC风机(电子控制自动启/停切换风机),通常在旁路或手动模式下风机仍全速运转。随着数据中心的节能设计优化可以预见数据中心设备的能效将呈现越来越高的趋势,基于变速设备和优化的控制装置的高效冷冻水系统技术及制冷系统冷冻水系统中的所有运转设备(包括冷冻机、泵、风机)采用变速控制技术和一体化控制策略,降低数据中心碳排放量将成为数据中心设备发展的新目标。     

一次泵变速变流量系统的最优化运行

以冷却泵、冷冻泵和冷水机组总能耗最小为最优化目标,取冷却水流量率、冷水出口温度和冷水流量率为优化参数,建立一次泵变速变流量系统总能耗优化模型,利用MATLAB编制了负荷率为80%的某实际制冷系统的优化程序。结果表明,负荷减少时合理控制运行参数可降低空调系统运行费用。     

空调冷冻水系统的微机控制

本文通过分析空调耗能量与自然环境的关系,应用控制原理,提出了一种用微机来控制冷冻水系统的方法。最后,以某办公大楼空调冷冻水系统为例,进行了微机控制系统的分析。     

大温差空调冷冻水系统的节能分析

以单位冷量空调总能耗为目标函数,对大温差空调冷冻水系统方案进行了优化计算,得出了空调冷冻水系统最佳供回水温差为7.2℃,探讨了大温差空调水系统方案的适用场合.     

基于NSGA-II的多效蒸发海水淡化系统优化研究

热压缩多效蒸发(MEE-TVC)海水淡化系统在工程中易于实现大型化应用,因此装置的优化设计极为必要。基于热力学第一、二定律,建立系统能质平衡模型和■分析模型。基于总收益需求法,建立系统经济性模型。以造水比最大(GOR_(max))/比■耗最小(e_(d, min))和单位造水成本最低(c_(p, tot, min))为目标,建立系统多目标优化模型,利用带有精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)求解得到Pareto最优解集,并将单目标和多目标优化方案进行对比分析。结果表明:与初始方案相比,热力性能单目标优化方案(e_(d, min)或GOR_(max))的单位造水成本增加约20%,而多目标优化方案则对三个目标均有改善。优化结果显示,所采用的优化方法可满足工程设计精度要求,且可为决策者提供基于不同偏好的优化方案。     

冷冻水变流量系统节能性分析

空调冷冻水变流量系统主要有一次泵变流量和二次泵变流量系统。用eQuest软件模拟某实际工程,空调冷冻水系统分别采用一次泵变流量和二次泵变流量时的能耗。通过对比得出一次泵变流量系统能更进一步降低空调系统的能耗,是一种更优化的空调水系统设计方案。     

An entransy dissipation-based optimization principle for building central chilled water systems

The recently developed entransy theory is introduced in this paper to tackle the heat transfer processes in building central chilled water systems so as to improve their energy efficiency. We first divide the irreversible heat transfer processes into four categories: (1) air mixing processes; (2) heat transfer processes between chilled water and air; (3) chilled water mixing processes; and (4) heat transfer processes between chilled water and refrigerant. The formulas of entransy dissipation rates for each irreversible process are derived, and then the total entransy dissipation rate in the whole chilled water systems is obtained, which connects the geometrical structures of each heat exchanger and the operating parameters of each fluid directly to the demands of users and the supply of refrigerating unit. Based on the formula of entransy dissipation rate together with the conditional extremum method in mathematics, two optimization equation groups are deduced theoretically. Simultaneously solving such equation groups will easily find the optimal central chilled water system with the highest energy efficiency. Finally, a simple building central chilled water system with two users is taken as an example to illustrate the applications of the newly proposed optimization principle.     

An online adaptive optimal control strategy for complex building chilled water systems involving intermediate heat exchangers

This paper presents an adaptive optimal control strategy for online control of complex chilled water systems involving intermediate heat exchangers to enhance operation and energy performances. This optimal control strategy determines the optimal settings of the heat exchanger outlet water temperature (hot side) and the required operating number of heat exchangers and pumps in order to minimize the total energy consumption of pumps under varying working conditions. Adaptive method is utilized to update the key parameters of the proposed models online. A simulated virtual platform representing a chilled water system in a super high-rise building was established to validate and evaluate the proposed optimal strategy. Test results show that the strategy has enhanced control robustness and reliability, particularly in avoiding deficit flow problem. Significant energy of chilled water pumps is saved when compared with conventional methods.     

Numerical simulation of closed wet cooling towers for chilled ceiling systems

A numerical technique for evaluating the performance of a closed wet cooling tower for chilled ceiling systems is presented. The technique is based on computational flow dynamics (CFD) for the two-phase flow of gas and water droplets. The eulerian approach is used for the gas phase flow and the lagrangian approach for the water droplet phase flow, with two-way coupling between two phases. Numerical simulation indicates that CFD can be used to predict the performance of a closed wet cooling tower, given the appropriate rate of heat generation from the heat exchanger. The technique is suitable for optimization of the design and operation of the cooling tower for chilled ceilings.     

Application of genetic algorithm to the optimal‐chilled water supply temperature calculation of air‐conditioning systems for saving energy

The values of chilled water supply temperatures of chillers indicate their load distributions due to the chilled water return temperatures of all chillers being the same in a decoupled air‐conditioning system. This study employs genetic algorithm (GA) to find out the chilled water supply temperatures of chillers for solving optimal chiller loading (OCL) problem. GA overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW‐PLR (partial load ratio) curves include non‐convex functions. This study uses the chilled water supply temperature as the variable to binary code chromosomes, and execute reproduction, crossover and mutation operation. After analysis and comparison of the case study, it has been concluded that this method not only solves the problem of Lagrangian method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air‐conditioning systems. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimal chilled water temperature calculation of multiple chiller systems using Hopfield neural network for saving energy

The values of chilled water supply temperatures in chillers indicate the load distributions as the chilled water return temperatures in all chillers are the same in a decoupled air-conditioning system. This study employs the Hopfield neural network (HNN) to determine the chilled water supply temperatures in chillers, which are used to solve the optimal chiller loading (OCL) problem. A linear input–output model is utilized as a substitute for the sigmoid function, which eliminates the shortcoming of the conventional HNN method. Notably, HNN overcomes the flaw in the Lagrangian method in that the latter cannot be utilized for solving the OCL problem as its power-consumption models include non-convex functions. The chilled water supply temperatures are used as variables to be solved for a decoupled air-conditioning system and solve the problem using the HNN method to overcome the defect in the Lagrangian method. After analysis of the case study and comparison of results using these two methods, we conclude that the HNN method solves the problem of the Lagrangian method, and produces highly accurate results. The HNN method can be applied to the operation of air-conditioning systems.     

基于ADMM的风场两级分布式无功优化方法

由于风机的无功耗变,电网电压稳定性随着风力渗透的增加而降低.针对风电场接入的配电网系统无功优化调度问题,本文提出了一种基于ADMM算法的两级无功优化调度方法.与现有的无功优化控制方法相比,该方法采用两阶段优化结构实现分布式无功优化调度.此外,在分区概念下,不需要一致性协议来解决优化问题.该方法在控制设计中也考虑了各个风...     

Optimization of energy plants including water/lithium bromide absorption chillers

In this paper a methodology for the optimal integration of water/lithium bromide absorption chillers in combined heat and power plants is proposed. This method is based on the economic optimization of an energy plant that interacts with a refrigeration cycle, by using a successive linear programming technique (SLP). The aim of this paper is to study the viability of the integration of already technologically available absorption chillers in CHP plants. The results of this alternative are compared with the results obtained using the conventional way of producing chilled water, that is, using mechanical vapour compression chillers in order to select the best refrigeration cycle alternative for a given refrigeration demand. This approach is implemented in the computer program XV, and tested using the data obtained in the water/LiBr absorption chiller of Bayer in Tarragona (Catalonia, Spain). The results clearly show that absorption chillers are not only a good option when low‐cost process heat is available, but also when a cogeneration system is present. In this latter case, the absorption chiller acts as a bottoming cycle by using steam generated in the heat recovery boiler. In this way, the cogeneration size can be increased producing higher benefits than those obtained with the use of compression chillers. Copyright © 2000 John Wiley & Sons, Ltd.     

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.     

Evaluation of optimal discharge current profile for planar electrodes to maximize the utilization

In this paper, optimization of operating conditions for electrochemical energy sources is attempted using a dynamic optimization approach. This rigorous approach is demonstrated using a nonlinear diffusion equation that governs the mass transport limitation from/to the planar electrode. The resulting differential-algebraic model is solved using piecewise constant control vector iteration method that uses vectorized discharge current. The results obtained using the optimal control profile is compared with constant current discharge method and also with another trial and error approach that uses linear current control. It is found that the optimal control method achieves 12% more state of discharge against constant current discharge method with better energy efficiency and battery use. The proposed approach can be extended to complex systems such as operating electrochemical energy sources in hybrid environments that require proper control of energy distribution among the hybrid components.     

Cycle Optimization on Reheat Adsorption Cycle Applying Fixed Chilled Water Outlet Temperature

This study investigated the cycle optimization of four-bed, silica gel–water adsorption with reheat cycle, where the desorber (upper bed) and adsorber (lower bed) always interact with the condenser and evaporator, to exploit a low heat-source temperature. In a previous study, the performance of a reheat cycle with chilled water outlet temperature fixed at 9°C was observed without considering the cycle optimization. Maintaining a constant chilled water outlet temperature is also of equal importance to improve the conversion efficiency so that maximum cooling capacity can be derived. In this paper, a simulation model of reheat adsorption cycles is developed to analyze the optimization of the cycle time, including adsorption/desorption time, mass recovery time, and preheating/precooling time, with chilled water outlet temperature fixed. The reheat working principle is also introduced. The proposed cycle is compared with the four-bed versison without reheat cycle in terms of coefficient of performance (COP) and cooling capacity. The result shows that the performance of a reheat cycle is superior to that of four-bed version without reheat, especially for low heat-source temperature. For low heat-source temperature (55–65°C) both COP and cooling capacity of the reheat cycle with optimization were raised significantly compared to the high heat-source temperature (70–80°C).