燃气机热泵的制冷性能

燃气机热泵(GEHP)是一种节能环保的空调装置。通过理论分析和实验测试研究了燃气机热泵部分负荷制冷性能。结果表明:燃气机热泵系统制冷量随着燃气机转速、蒸发器进水流量和蒸发器进水温度的提高而增加。制冷性能系数(COP)和一次能源利用率(PER)随着燃气机转速的增加而减少,随着蒸发器进水温度和进水流量的增加而增加。在考虑余热回收的情况下,燃气机热泵的一次能源利用率在1.29~1.67之间。     

以污泥为原料污水为冷热源的燃气机热泵系统设计与分析

提出以污水、污泥为原料以及采用自然工质的燃气机热泵系统.在该系统中,污水处理厂的污泥生成沼气,沼气在燃气机中燃烧带动压缩机运转;处理后的污水作为热泵系统的冷(热)源向建筑物提供冷(热)量.对该系统做了分析,讨论了循环流程和几个关键部分,建立了计算模型,采用了当量冷凝温度分析法,以自然工质CO2和R290作为热泵系统的工质做了对比分析.通过提出污水污泥以及利用自然工质的燃气机热泵系统,以充分利用可再生资源达到节能环保的目的,为环保的可持续发展提供一些思路.     

空气源燃气机热泵空调系统的应用研究

对燃气机热泵进行热力学第一定律分析、（火用）分析和能级分析,结果表明燃气机热泵具有高的热力学完善性,能量利用过程也比较合理。阐述了空气源燃气机热泵的容量确定,并对机组在我国的应用进行探讨。认为机组在东北地区应采用燃气锅炉进行辅助加热,并采用交替运行方式,在黄河流域应用应按供热工况设计,在长江流域应用应按空调工况设计,在华南地区应用则可以缓解夏季电力紧张。     

燃气机热泵系统电子膨胀阀流量控制的研究

本文通过理论分析及实验测试,研究燃气机热泵系统启动过程和大范围变容量调节过程中系统流量特性,提出了适合于燃气机热泵系统的电子膨胀阀流量控制策略.结果表明文中所提出的模糊自适应PID控制方法和模糊PID控制方法的控制性能要优于常规的PID控制方法.     

燃气机热泵的热电冷三联供系统分析

提出了一个燃气机热泵的热电冷三联供系统，并介绍其组成．为分析燃用不同气体燃料的系统热力学完善程度，提出了标准气耗的概念．对热电冷三联供系统的分析结果表明，该系统的一次能源利用率可达１．４９，比热电冷分供高一倍，标准气耗则降低一半左右．     

燃气热泵(GHP)系统制冷工况的数值模拟与分析

通过建立天然气发动机驱动热泵系统的数学模型,研究了制冷工况下,点火提前角、压缩比、过量空气系数,发动机转速等参数对天然气发动机及整个热泵系统运行性能的影响,为天然气发动机的优化设计提供一定的理论依据,并且预测了燃气热泵的性能,证明了该系统具有较好的部分负荷特性.     

燃气压缩式热泵空调系统的实验研究

对采用燃气机驱动的压缩式热泵空调系统进行安装、改造及运行实验,实验的内容主要包括发动机系统的运行特性、热泵系统、整体系统的性能特性。实验结果表明,燃气机热泵是一项高效节能技术,在实验条件下其平均一次能源利用率PER为1.42;而且部分负荷特性好,可以良好的实现变速调节。     

新型热电热泵冷风机的性能研究

设计了一种新型热电热泵冷风机,建立了基于热阻网络法和换热器理论的热电热泵冷风机的数学模型,推导得出了能够有效表征该热电风机制冷性能的多参数耦合方程,并利用该模型分析了制冷片工作电流、散热热阻和新风流量的影响。然后以最大效率和最大制冷量、最小制冷片冷热端温差为综合最优为目标,对以上影响因素提出了最优控制方案,并进一步讨论了热电热泵风机的性能优化方法。该多参数耦合分析方法,对于热电冷风机的研究具有很好的参考价值。     

内燃机拖动地源热泵系统的实验研究

随着天然气能源的大力开发,燃气热泵的应用也相应得到关注,为了研究燃气热泵的性能,本文建立了实验装置,通过实验分析了内燃机拖动地热源热泵系统的性能,及其应用研究和经济性分析。燃气热泵系统一次能源利用率比燃气锅炉及燃气吸收式冷温水机组高,同时由于以土壤为热源,技术上保证了热泵系统使用不受地理环境气候的限制,可在冬季及夏季使用。由此又能够缓解电力供应矛盾,平衡供气负荷。对电力及天然气的生产成本降低及可靠性提高有很大帮助。燃气热泵系统有良好的变速性能,能很好的与实际负荷匹配,降低能耗进而得出燃气热泵系统的应用优势,为今后进一步开发研究提供参考。     

基于遗传算法混合工质热泵多参数优化

本文将人工智能之一的遗传算法应用于混合工质热泵系统,在对热泵进行模拟的基础上构造了系统性能函数,对冷凝压力、蒸发压力以及回热度进行了多参数的优化,得到了使系统COP最大时的各参数的最佳值。发现在进行制冷/热系统多参数组合优化时,遗传算法全局寻优以及收敛能力与传统的优化方法相比,性能有了较大的提高。     

Multi-Objective Optimization and Performance Assessments of an Integrated Energy System Based on Fuel,Wind and Solar Energies

The integrated energy system (IES) is an efficient method for improving the utilization of renewable energy. This paper proposes an IES based on fuel, wind and solar energies, following an optimization study focused on determining optimal device capacities. The study included gas turbines, wind turbines, solar photovoltaic panels, ground source heat pumps, absorption chillers/heaters, batteries, and thermal storage. Objectives were incorporated into the optimization model for the overall performance of the IES; these included the primary energy saving rate, annual cost-saving rate, and carbon dioxide emission reduction. Then, the nondominated sorting genetic algorithm II was employed to solve the optimization problem for multiple objectives. Ultimately, the verification and sensitivity analyses of the optimization method were achieved by a case study of hospital buildings in Harbin. The optimization results indicated a primary energy saving rate, annual cost saving rate, and carbon dioxide emission reduction rate of 17.3%, 39.8%, and 53.8%, respectively. The total installed capacity for renewable energy generation accounted for 64.5% of performance optimization. Moreover, the price of natural gas affected the economic indicators of the IES–but failed to impact energy consumption indicators.     

耦合太阳能和地热能的冷热电联供系统优化

天然气和可再生能源互补是一种并行解决环境污染和克服可再生能源不稳定的有效方式,本文提出一种耦合太阳能和地热能的混合冷热电联供(CCHP)系统。基于以电定热(FEL)和以热定电(FTL)运行策略,提出了地源热泵出力比依照逐时电价和季节而变化的运行模式;以一次能源节约率、费用年值节约率以及二氧化碳减排率为目标函数,建立CCHP系统优化模型,运用多目标遗传算法对系统配置及运行策略进行了寻优求解。结果表明:该混合CCHP系统在FEL模式能够实现最优的综合性能.     

基于混合群智能优化算法的混沌系统参数估计

混沌系统的未知系统参数估计是实现混沌控制和同步的首要问题,通过构造一个合理的适应度函数,可将其转化为一个多维搜索空间的优化问题.提出一种融合改进骨干粒子群算法与改进差分进化算法的混合群智能优化方法来解决上述优化问题.对骨干粒子群算法中的粒子位置更新机制以及差分进化算法中的变异操作、交叉操作、交叉概率因子的设计等进行改进,有效兼顾了种群的多样性与算法的收敛性.在此基础上,讨论骨干粒子群优化算法与差分进化的融合优化策略,实现两个算法的协同进化,进一步提高算法的综合优化性能.用6个基准测试函数以及Lorenz混沌系统为例进行仿真实验,结果表明该方法具有全局寻优能力强、收敛速度快、搜索精度高、稳健性好等优点.     

Optimization of apodization functions in terahertz transient spectrometry

A quadratic programming optimization procedure for designing asymmetric apodization windows tailored to the shape of time-domain sample waveforms recorded using a terahertz transient spectrometer is proposed. By artificially degrading the waveforms, the performance of the designed window in both the time and the frequency domains is compared with that of conventional rectangular, triangular (Mertz), and Hamming windows. Examples of window optimization assuming Gaussian functions as the building elements of the apodization window are provided. The formulation is sufficiently general to accommodate other basis functions.     

一类求解箱式约束优化问题的自适应引力搜索算法

为了改进引力搜索算法求解箱式约束优化问题的性能,提出了一类自适应引力搜索算法,新算法定义了算法停滞系数,当算法陷入停滞时,可以自适应的修改引力参数,帮助算法跳出停滞状态;定义了个体相似系数,当种群陷入局部最优时,通过变异策略改善种群的多样性。数值试验结果表明,新算法有效的平衡了全局开发和局部搜索能力,具有更强的全局寻优能力,适于求解复杂优化问题。     

Level set-based topology optimization for anti-reflection surface

We present a level set-based topology optimization method to model anti-reflection surfaces (ARSs). An objective functional is defined as an integration of scattering intensity of an electric field, and the ARSs are optimally designed by minimizing reflections at the air-dielectric interface. During the topology optimization, geometric constraints are controlled by adjusting a regularization parameter. The performance of the ARSs improves as the value of the regularization parameter becomes small. Level set functions are used to express dielectric structures, and dielectric boundaries are interpreted as lines on the iso-surface of the level set functions.     

A damage identification technique based on embedded sensitivity analysis and optimization processes

A vibration based structural damage identification method, using embedded sensitivity functions and optimization algorithms, is discussed in this work. The embedded sensitivity technique requires only measured or calculated frequency response functions to obtain the sensitivity of system responses to each component parameter. Therefore, this sensitivity analysis technique can be effectively used for the damage identification process. Optimization techniques are used to minimize the difference between the measured frequency response functions of the damaged structure and those calculated from the baseline system using embedded sensitivity functions. The amount of damage can be quantified directly in engineering units as changes in stiffness, damping, or mass. Various factors in the optimization process and structural dynamics are studied to enhance the performance and robustness of the damage identification process. This study shows that the proposed technique can improve the accuracy of damage identification with less than 2 percent error of estimation.     

The emergence of scaling laws search dynamics in a particle swarm optimization

This paper investigates the search dynamics of a fundamental particle swarm optimization (PSO) algorithm via gathering and analyzing the data of the search area during the optimization process. The PSO algorithm exhibits a distinct performance when optimizing different functions, which induces the emergence of different search dynamics during the optimization process. The simulation results show that the performance is tightly related to the search dynamics which results from the interaction between the PSO algorithm and the landscape of the solved problems. The Lévy type scaling laws search dynamics emerges from the process in which the PSO algorithm shows good performance, while the Brownian dynamics appears after the algorithm has stagnated due to the premature convergence. The Lévy dynamics characterized by a large number of intensive local searches punctuated by long-range transfers is an indicator of good performance, which allows the algorithm to achieve an efficient balance between exploration and exploitation so as to improve the search efficiency.     

Passive vehicle suspensions employing inerters with multiple performance requirements

This paper investigates passive vehicle suspensions with inerters by considering multiple performance requirements including ride comfort, suspension deflection and tyre grip, where suspension deflection performance is novelly considered which is formulated as a part of objective functions and a constraint separately. Six suspension configurations are analyzed and the analytical solutions for each performance measure are derived. The conditions for each configuration to be strictly better than the simpler ones are obtained by presenting the analytical solutions of each configuration based on those of the simpler ones. Then, two stages of comparisons are given to show the performance limitations of suspension deflection for passive suspensions with inerters. In the first stage, it is shown that although the configurations with inerters can improve the mixed performance of ride comfort and tyre grip, the suspension deflection performance is significantly decreased simultaneously. In the second stage, it is shown that for passive suspensions with inerters, suspension deflection is the more basic limitation for both ride comfort and tyre grip performance by doing comparisons among mixed ride comfort and suspension deflection optimization, mixed ride comfort and tyre grip optimization, and mixed suspension deflection and tyre grip optimization. Finally, the problem of mixed ride comfort and tyre grip performance optimization with equal suspension deflection is investigated. The limitations of suspension deflection for each configuration are further highlighted.