Defrosting method adopting dual hot gas bypass for an air-to-air heat pump

A novel dual hot gas bypass defrosting (DHBD) method is developed to remove frost from the outside heat exchanger (HEX) of an air-to-air heat pump. The proposed method adopts two bypass lines of hot gas from the compressor: one is connected to the inlet of the outdoor HEX, and the other is connected to the outlet of the exchanger. We compare the dynamic performance and defrosting time of the conventional reverse cycle defrosting (RCD), hot gas bypass cycle defrosting (HGBD), and DHBD methods using a medium air-to-air 16 kW heat pump. The salient feature of the DHBD method is its ability to prevent a sharp decrease in the compressor outlet temperature at the melting frost stage after the HGBD process begins. Due to the additional bypass, the DHBD method sustained a higher compressor outlet pressure and reduced the defrosting time by 36% compared to the HGBD method. Compared to RCD, the defrosting time was comparable (126%); however, the amenity characteristics of the DHBD method were superior than those of the RCD method. The proposed DHBD method can overcome the main disadvantages of the RCD and HGBD methods, and showed excellent performance for an air-to-air heat pump in a defrosting operation.     

可实现快速制热和除霜的蓄能型空气源热泵系统的实验研究

提出一种可快速制热和除霜的蓄能型空气源热泵系统,并在室外温度约-0.7℃,相对湿度约95%的雨雪天气条件下进行实验测试,结果表明,结霜过程中蓄热器可有效阻止室内机出风温度的下降,除霜过程中新系统的压缩机出力大,效率高。除霜用时比常规除霜缩短68%,除霜能耗比常规除霜减少51.4%,除霜末期室内机出风温度为28℃,比常规系统高22℃,几乎没有吹冷风感;新系统开机快速制热效果十分显著,其6 min的制热量相当于常规开机制热10 min的制热量,新系统显著提高了空气源热泵的供热效果。     

A self-organizing power system stabilizer using fuzzyauto-regressive moving average (FARMA) model

This paper presents a self-organizing power system stabilizer (SOPSS) which use the fuzzy auto-regressive moving average (FARMA) model. The control rules and the membership functions of the proposed fuzzy logic controller are generated automatically without using any plant model. The generated rules are stored in the fuzzy rule space and updated on-line by a self-organizing procedure. To show the effectiveness of the proposed controller, comparison with a conventional controller for a one-machine infinite-bus system is presented     

Defrost improvement by heat pump refrigerant charge compensating

During winters, the air-source heat pump often operates with substantial frost formation on the outdoor heat exchanger, and the frost layer has to be melted away periodically to keep a high heat pump coefficient of performance (COP). Otherwise, the unmelted frost layer and water will become high density frost or ice layer in heating mode. However, it is difficult to melt the frost layer in the defrosting cycle, where the effective defrosting time plays an important role in improving the defrosting ability. Generally, the defrosting time can be decreased by the following ways: increasing the refrigerant flow rate effectively, and rapidly establishing the suction pressure, discharge pressure, and the compressor power. A new heat pump defrost system with a refrigerant charge compensator, instead of the accumulator which is a key component for the frosting cycle performance, is developed in this paper. Furthermore, test results showed that the improved frost system with the compensator worked as expected, and its suction and discharge pressures and the power of the compressor during the defrosting were much larger than before.     

基于模糊算法的压差变流量控制研究

采用模糊算法编制压差控制系统的内部算法,用模糊算法实现对空调水系统的智能控制,详细给出模糊控制系统的设计步骤,并通过对中央空调系统特性数据的监测,验证了该技术的可行性。     

Optimization of fuzzy-based MPPT controller via metaheuristic techniques for stand-alone PV systems

Due to the alteration of power-voltage characteristics of solar module output under multiple environmental conditions such as solar irradiation and ambient temperature, these systems hardly function at maximum power point (MPP). However, maximum power point tracking (MPPT) plays a significant role in their efficiency. On the other hand, solar module characteristics are extremely nonlinear and their slope on either side of MPP is asymmetric. Thus using a nonlinear control method which has the potential of adapting the operating point of the system to MPP seems useful. This has motivated authors to present MPPT method which maximizes PV's output power by tracking MPP continuously. In the present study, a fuzzy logic controller (FLC) is presented for MPPT in photovoltaic systems. Four optimization algorithms are presented in this paper for optimizing fuzzy membership functions (MFs) and generating proper duty cycle for MPPT. The presented algorithms include: Teaching Learning Based Optimization (TLBO), Firefly Algorithm (FFA), Biogeography based optimization (BBO), and Particle Swarm Optimization (PSO), which are all described and simulated. Finally, to validate performance of the proposed optimized FLC, it is compared with other algorithms such as symmetrical fuzzy logic controller (SFLC) and conventional Perturbation and Observation (P&O). According to the simulation results, P&O algorithm shows significant oscillations, energy loss, and in some cases, it cannot obtain MPP. Simulation results also indicate that TLBO and FFA based asymmetric fuzzy MFs not only increase MPPT convergence speed but also enhance tracking accuracy in comparison with symmetric fuzzy MFs and asymmetric fuzzy MFs based on BBO and PSO.     

应用免疫算法的联合循环余热锅炉过热汽温的优化控制

过热蒸汽温度对象具有时变性、不确定性和非线性等特点，是联合循环余热锅炉中一个较难控制的过程。借鉴免疫系统原理，提出一种新的免疫并行算法，进而运用该算法提出一种PID参数优化方法，并将其用于余热锅炉过热汽温的优化控制中。仿真结果证实了该方法的有效性。图9表1参9     

Power management strategy for vehicular-applied hybrid fuel cell/battery power system

In this paper, a control strategy for a hybrid PEM (proton exchange membrane) fuel cell/BES (battery energy system) vehicular power system is presented. The strategy, based on fuzzy logic control, incorporates the slow dynamics of fuel cells and the state of charge (SOC) of the BES. Fuel cell output power was determined according to the driving load requirement and the SOC, using fuzzy dynamic decision-making and fuzzy self-organizing concepts. An analysis of the simulation results was conducted using Matlab/Simulink/Stateflow software in order to verify the effectiveness of the proposed control strategy. It was confirmed that the control scheme can be used to improve the operational efficiency of the hybrid power system.     

Adaptive fuzzy sliding-mode control for induction servomotor systems

An adaptive fuzzy sliding-mode control design method is proposed for induction servomotor system control. The proposed adaptive fuzzy sliding-mode control system is comprised of a fuzzy controller and a compensation controller. The fuzzy controller is the main tracking controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the fuzzy controller. A tuning methodology is derived to tune the premise and consequence parts of the fuzzy rules. The online tuning algorithm is derived in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Moreover, to relax the requirement for the uncertain bound in the compensation controller, an estimation mechanism is investigated to observe the uncertain bound, so that the chattering phenomena of the control efforts can be relaxed. To illustrate the effectiveness of the proposed design method, a comparison between a conventional fuzzy control and the proposed adaptive fuzzy sliding-mode control is made. Simulation and experimental results verify that the proposed adaptive fuzzy sliding-mode control design method can achieve favorable control performance with regard to parameter variations and external disturbances.     

On-line fuzzy energy management for hybrid fuel cell systems

Fuel Cell Hybrid Vehicles (FCHV) can reach near zero emission by removing the conventional internal combustion from the vehicle powertrain. Nevertheless, before seeing competitive and efficient FCHV on the market, at market prices, different technical, economic, and social challenges should be overcome. A typical hybrid fuel cell powertrain combines a fuel cell stack and a dedicated energy storage system along with their necessary power converters. Energy storage systems are used in order to enhance the well-to-wheel efficiency and thus reducing the hydrogen consumption. An efficient management of power flows on the vehicle, allows optimizing the recovery of energy braking. Moreover, working in the fuel cell maximum efficiency leads to reduced thermal losses and thus to the downsizing of the heat exchangers. This paper presents an enhanced control of the power flows on a FCHV in order to reduce the hydrogen consumption, by generating and storing the electrical energy only at the most suitable moments on a given driving cycle. While the off-line optimization-based on dynamic programming algorithm offers the necessary optimal comparison reference on a known demand, the proposed strategy which can be implemented on-line, is based on a fuzzy logic decision system. The fine tuning of the fuzzy system parameters (mainly the membership functions and the gains), is made using a genetic algorithm and the fuzzy supervisor shows performing results for different load profiles.     

Experimental study on the performance of air source heat pump system with multiple parallel outdoor units

This paper presents a novel air source heat pump for heating of buildings named air source heat pump with multiple parallel outdoor units (ASHPMO). Multiple outdoor units were connected in parallel with the aim of realising alternate defrosting and uninterrupted heating simultaneously. An experimental apparatus of the ASHPMO system was developed. The defrosting performance was experimentally investigated under different outdoor air temperatures, outdoor air relative humidity, and condensation temperatures, among other factors. The test results showed that the novel ASHPMO system could provide continuous heating when defrosting even under an outdoor air temperature of −10°C. Variations in compressor vapour suction and discharge pressure and temperature were observed. The minimum heating capacity could still reach 60% of that without defrosting. Under the defrosting condition with outdoor air temperature −10°C, both the heating coefficient of performance (heating COP) and total energy efficiency ratio (EER) of the system can reach to 2.0 and 2.32, respectively.     

Fuzzy cascade control based on control’s history for superheated temperature

To address the characteristics of the large delay and uncertainty of superheated temperature, a new cascade control system is presented based on control’s history. Based on the analysis of the control objects’ dynamic characteristics, historical control information (substituting for the deviation change rate) is used as the basis for decision-making of the fuzzy control. Therefore, the changing trend of the controlled variable can be accurately reflected. Furthermore, a proportional component is introduced, the advantages of PID and fuzzy controllers are integrated, and the structure weaknesses of conventional fuzzy controllers are overcome. Simulation shows that this control method can effectively reduce the adverse impact of the delay on control effects and, therefore, exhibit strong adaptability by comparing the superheated temperature control system by this controller with PID and conventional fuzzy controllers.     

一种设计模糊-PID复合控制器的新方法及其在电厂控制中的应用

为提高大型火电机组过热蒸汽温度串级控制的性能，提出了一种新型模糊-PID复合控制器的设计方法。该方法可实现在偏离工作点较远的区域模糊控制中起主要控制作用，在工作点附近则主要实施PID控制，实现了两种控制的优势互补，同时还为模糊控制器提供了一种系统化设计方法。实际工业应用结果表明：采用该方法设计的过热蒸汽温度串级控制系统比常规方法设计的系统具有更强的适应能力和良好的控制品质。图9表1参6     

超临界机组协调系统的模糊增益调度预测控制

针对火电厂超临界机组多变量锅炉-汽机协调系统在大工况范围内运行具有强非线性的特点,提出了一种基于模糊增益调度的预测控制方法.通过现场试验获取多个工况点处的协调系统传递函数模型,结合增益调度和模糊逻辑推理方法建立全局自适应模糊模型,利用预测控制技术确保控制系统全局优化品质.基于模糊增益调度的预测控制方法设计火电厂超临界机...     

Solar space heating and cooling with bi-heat source heat pump and hot water supply system

This paper describes a specific heat pump system that can solve the problem of low heating capacity at a low ambient temperature—one of the largest problems in the air-source heat pump system.

In order to decrease the collector area required, the heat pump system is operated by the air-source during the daytime, but at night or at a very low ambient temperature it can be operated with hot water which has been produced by the collector in the daytime. The effect of the solar energy on the air-source heat pump system has many advantages in the moderate winter climate of Japan. The hot water supply system includes an auxiliary electric heater.

The experiment has been carried out with a prefabricated test house, which has been constructed in Nara with double glazed windows and high thermal insulation. The results of this experiment are that solar energy enhances the total electric energy savings, increases the heating capacity at low ambient temperature, and eliminates the need for reverse cycle defrosting operation, etc.     

基于反推方法的滑模自适应励磁控制

针对电力系统参数摄动和外界干扰等因素对励磁系统的影响,经过对传统模型状态变量的变换,建立了励磁控制系统模型,设计了基于backstepping方法的模糊滑模励磁控制器。该方法通过逐步构造Lyapunov函数和设计切换函数．从而得到了最终的控制规律。最后对所设计的算法进行了仿真研究,与常规PID＋PSS控制方法相比,系统在动静态响应性能上均优于PID＋PSS控制。通过仿真表明这种控制方法不仅有效而且还能达到比较满意的控制效果。     

钢球磨煤机制粉系统的优化控制

针对燃煤电站钢球磨煤机制粉系统多变量强耦合的特点，提出了基于模糊控制和预测控制的复合优化控制策略。该方案是大偏差时采用模糊控制，小偏差时采用解耦预测控制,并在稳态时进行监控优化。对某DTM－287／470型球磨机系统的仿真研究表明：提出的方法有较强的鲁棒性和抗干扰能力，稳态监控策略的实施有利于提高制粉系统的出力，达到优化运行的目的，具有重要的理论价值和实际意义。图2参5     

Multi-objective exergy-based optimization of a continuous photobioreactor applied to produce hydrogen using a novel combination of soft computing techniques

This work was aimed at proposing a flexible and reliable framework based on combination of three soft computing techniques, i.e., artificial neural network, genetic algorithm, and fuzzy systems for multi-objective exergetic optimization of continuous photobiohydrogen production process from syngas by Rhodospirillum rubrum bacterium. To this end, artificial neural network (ANN) coupled with fuzzy clustering method (FCM) to model exergetic outputs on the basis of input variables. The outputs of modeling system were then fed into a novel optimization approach developed by hybridizing additive linear interdependent fuzzy multi-objective optimization (ALIFMO) and the elitist non-dominated sorting genetic algorithm (NSGA-II). The optimization was carried out to minimize the normalized exergy destruction and maximize the rational and process exergetic efficiencies, simultaneously. The solutions of the proposed approach were also compared with conventional fuzzy multi-objective optimization procedure with independent objectives. Overall, the modeling system predicted the exergetic parameters of photobioreactor with a coefficient of determination higher than 0.90. Furthermore, the optimization approach suggested syngas flow rate of 13.35 mL/min and agitation speed of 383.34 rpm as the best operational condition by considering the preferences of process exergy efficiency, rational exergy efficiency, and normalized exergy destruction, respectively. This condition could yield the normalized exergy destruction of 1.56, process exergetic efficiency of 21.66%, and rational exergetic efficiency of 85.65%. The obtained results showed the superiority of the proposed approach over the conventional fuzzy method in optimizing the complex biofuel production systems.     

汽油机怠速模糊-PID控制系统研究与分析

为了进一步控制汽油机怠速转速波动,改善怠速控制品质,提出了怠速模糊-PID控制方法,并在Matlab/Simulink软件平台上,搭建了PID控制、模糊控制、模糊-PID三种怠速控制仿真模型,对比分析了各种怠速控制系统的控制响应特性。通过台架试验,对原机控制算法和所设计控制算法下发动机怠速转速进行了对比,验证了该算法的正确性。结果表明:模糊-PID控制系统可以显著缩小转速波动范围,且系统响应更快,载荷切换阶段的转速波动最大幅值小于30 r·min~(–1),稳态波动幅值在±15 r·min~(–1)范围内;与PID控制、模糊控制两种控制方式相比,模糊-PID控制可显著提高怠速控制品质。     

基于超平面原型聚类的水轮机调速系统模糊模型辨识

针对水轮机调速系统的辨识难题,提出了1种基于超平面原型聚类的T-S模糊模型辨识方法.基于局部模糊模型线性度的重要性,推导出1种基于超平面的模糊聚类算法.该算法以优化局部模型线性度为目标,进行模糊模型前提结构辨识,能使局部模型具有良好的线性度;它应用变尺度混沌优化方法搜索最优聚类结果,避免陷入局部极小;应用最小二乘法实现模糊模型结论参数辨识.以某水电厂水轮机调速系统为对象,采用该方法建立了T-S模糊模型,并对其进行了辨识和对比试验.结果表明:建立的T-S辨识模型具有较高的辨识精度及较强的泛化能力,提出的模型辨识方法有效可行.