Identification of synchronous machine linear parameters fromstandstill step voltage input data

This paper presents the results of a time-domain identification procedure to estimate the linear parameters of a 15 kVA salient-pole synchronous machine at standstill. A step voltage input test is performed, and the parameters of the time constant models and equivalent circuit models are estimated. The maximum likelihood algorithm is used for the estimation, and the best-fit model is selected from a set of increasing order models. The initialization values for the parameters to be estimated are determined from the operational inductances derived directly from the measured time domain data. The simulated equivalent circuit model response is validated against the measured standstill time domain and frequency domain data. In addition, simulation of the model response to an on-line small disturbance test is compared to the measured dynamic response     

Stochastic modeling of lift and drag dynamics under turbulent wind inflow conditions

We present a new approach to model the complex dynamics of aerodynamic forces on an airfoil in turbulent inflow conditions. Our ansatz is based on stochastic differential equations and aims at replacing traditional look‐up table methods used in wind turbine simulation systems by the effective response dynamics of lift and drag forces. The parameters of the model are derived directly from empirical data. Measurements were taken in the closed loop wind tunnel of the University of Oldenburg for an airfoil FX 79‐W‐151A. The turbulent inflow was generated using a fractal square grid as it is possible to generate in this way wind speed fluctuations with similar statistics as observed in nature. Forces were measured using two strain gauge force sensors at two end points of the vertically installed airfoil. The modeling is performed by applying a stochastic approach on the measured data. By estimating the first two Kramers–Moyal coefficients, a first‐order stochastic differential equation called the Langevin equation is obtained. The stochastic model achieved through this approach is extended to account for oscillation effects contained in lift and drag dynamics that probably stem from unsteady aerodynamic effects. The results are optimized by applying a χ² test on the probability density functions (PDFs) of model and measurements. With the knowledge of the Langevin equation, synthetic time series are generated. Their stationary PDFs as well as conditional PDFs show good agreement with the actual measurements. A comparison of classical averaging and the stochastic approach shows that stochastic analysis achieves additional insight into the local dynamics of lift and drag forces. Copyright © 2014 John Wiley & Sons, Ltd.     

Surrogate model for proton exchange membrane fuel cell (PEMFC)

The main goal of this work is to realize a PEMFC model that can be used efficiently for the global modelling of the fuel cell system. The modelling method proposed in the paper is an approach from an empirical point of view that allows a PEMFC model of “black-box” class to be developed. Moving least squares (MLS) have therefore been employed to approximate the cell voltage characteristics V, using an experimental dataset measured in determinate conditions. The MLS approach appears to present a good balance of response surface accuracy, smoothness, robustness, and ease of use. This kind of numerical model offers good perspectives for the systems identification, the simulation of the systems, the design and the optimization of process control, etc. The results prove that the method is suitable for predicting and describing the fuel cell behaviour in all the points of the approximation domain. The proposed model can be included in a numerical application to optimize the operation of an existing fuel cell system.     

Multi-input and multi-output neural model of the mechanical nonlinear behaviour of a PEM fuel cell system

A fuel cell system model is necessary to prepare and analyse vibration tests. However, in the literature, the mechanical aspect of the fuel cell systems is neglected. In this paper, a neural network modelling approach for the mechanical nonlinear behaviour of a proton exchange membrane (PEM) fuel cell system is proposed. An experimental set is designed for this purpose: a fuel cell system in operation is subjected to random and swept-sine excitations on a vibrating platform in three axes directions. Its mechanical response is measured with three-dimensional accelerometers. The raw experimental data are exploited to create a multi-input and multi-output (MIMO) model using a multi-layer perceptron neural network combined with a time regression input vector. The model is trained and tested. Results from the analysis show good prediction accuracy. This approach is promising because it can be extended to further complex applications. In the future, the mechanical fuel cell system controller will be implemented on a real-time system that provides an environment to analyse the performance and optimize mechanical parameters design of the PEM fuel system and its auxiliaries.     

Electrochemical parameter identification—An efficient method for fuel cell impedance characterisation

Electrochemical parameter identification (EPI) is a novel, application-oriented characterisation method for fuel cell impedances. EPI strictly works in the time domain, with a model of the fuel cell impedance and measurements of the excitation and the response in the time domain. This approach reduces the measurement time considerably in comparison to frequency domain measurements for electrochemical impedance spectroscopy. The use of a superimposed signal as system excitation leads to less interference of the fuel cell operation than a current interrupt. Short measurement time and little interference enable an online application of the method during the operation of the fuel cell. A simple discrete-time model describing the dynamic electrical behaviour of the fuel cell is depicted as an equivalent circuit which consists of a voltage source and the impedance as internal resistance. The model parameters are identified by a hybrid optimisation algorithm using the sampled excitation and response signals. A comparison of measured impedance spectra at various operation conditions with impedance models identified by EPI shows very good agreement over a wide frequency range and emphasizes the reliability of EPI.     

Short-circuit test based maximum likelihood estimation of stabilitymodel of large generators

This paper presents a time-domain statistical identification method for synchronous-machine linear parameters from the standard line-to-line short-circuit test. The measurements are recorded on a 13.75-MVA hydrogenerator at Hydro-Quebec's Rapide-des-Quinze generating station. A complete mathematical model for synchronous machine asymmetrical test analysis is proposed. An efficient algorithm is built to accurately calculate the standard equivalent circuit from time-constants and operational inductances. The maximum likelihood estimator derived from the generalized least-squares method is then used for parameter identification. Validation of the estimated model response against the measured running-time domain data confirms the effectiveness of the proposed estimation technique     

CFD modeling of two-stage ignition in a rapid compression machine: Assessment of zero-dimensional approach

In modeling rapid compression machine (RCM) experiments, zero-dimensional approach is commonly used along with an associated heat loss model. The adequacy of such approach has not been validated for hydrocarbon fuels. The existence of multi-dimensional effects inside an RCM due to the boundary layer, roll-up vortex, non-uniform heat release, and piston crevice could result in deviation from the zero-dimensional assumption, particularly for hydrocarbons exhibiting two-stage ignition and strong thermokinetic interactions. The objective of this investigation is to assess the adequacy of zero-dimensional approach in modeling RCM experiments under conditions of two-stage ignition and negative temperature coefficient (NTC) response. Computational fluid dynamics simulations are conducted for n-heptane ignition in an RCM and the validity of zero-dimensional approach is assessed through comparisons over the entire NTC region. Results show that the zero-dimensional model based on the approach of ‘adiabatic volume expansion’ performs very well in adequately predicting the first-stage ignition delays, although quantitative discrepancy for the prediction of the total ignition delays and pressure rise in the first-stage ignition is noted even when the roll-up vortex is suppressed and a well-defined homogeneous core is retained within an RCM. Furthermore, the discrepancy is pressure dependent and decreases as compressed pressure is increased. Also, as ignition response becomes single-stage at higher compressed temperatures, discrepancy from the zero-dimensional simulations reduces. Despite of some quantitative discrepancy, the zero-dimensional modeling approach is deemed satisfactory from the viewpoint of the ignition delay simulation.     

Transient response of a packed bed energy store employing a convecting gas vapour mixture

Low temperature transient operation of a packed bed thermal energy store, employing a convecting gas/vapour mixture to enhance the effective conductivity of the store, is described. Comparisons are made between the transient response of the store and predictions from a computer model which treats heat transfer through the store as a transient, one-dimensional conduction problem. Effective conductivities for the conduction model are obtained from previously measured steady state Nusselt number versus Rayleigh number data for the system. The comparisons show that (a) the simple one-dimensional transient conduction model, useful for system simulation, gives an adequate representation of store behaviour, and (b) the conductivities measured at steady state can be used in the transient model, implying that the high values achieved with gas/vapour mixtures at steady state, apply during transient operation. Further work to develop the storage system, and to improve understanding of the complex processes within it, is described.     

基于ANSYS的核电成层覆盖土场地地震响应分析

针对ANSYS软件中缺少等价线性法本构模型的问题,基于等价线性法的计算理论,通过对ANSYS软件的二次开发,实现了成层土地基的动力等价线性法模型,并将其应用于某核电站土基厂址自由场的非线性动力响应分析中。结果表明,本方法合理、有效。     

Computer modeling and experimental validation of a building-integrated photovoltaic and water heating system

A dynamic simulation model of a building-integrated photovoltaic and water heating system is introduced in this paper. The numerical model was developed based on the finite difference control volume approach. The integrated use of energy balance and fluid flow analysis allows the prediction of the system dynamic behavior under external excitations such as changes in weather, water consumption and make-up conditions. The validity of the modeling approach was demonstrated by comparing its predicted operating temperature changes and system daily efficiencies with the measured data acquired from an experimental rig at the City University of Hong Kong. The predictions from the model show good compliance with the experimental measurements.     

A Tool for Predicting the Thermal Performance of a Diesel Engine

This paper presents a thermal network model for the simulation of the transient response of diesel engines. The model was adjusted by using experimental data from a completely instrumented engine run under steady-state and transient conditions. Comparisons between measured and predicted material temperatures over a wide range of engine running conditions show a mean error of 7°C. The model was then used to predict the thermal behavior of a different engine. Model results were checked against oil and coolant temperatures measured during engine warm-up at constant speed and load, and on a New European Driving Cycle. Results show that the model predicts these temperatures with a maximum error of 3°C.     

On-line synchronous machine parameter estimation from smalldisturbance operating data

This paper presents a step-by-step system identification approach to estimate the parameters of a three-phase salient-pole synchronous machine rated at 5 kVA from online small disturbance responses. The machine equivalent circuit model linear parameters and the nonlinear saturated parameters are estimated. The estimation is performed using the maximum likelihood algorithm. Simulation studies based on the online measured small and large dynamic disturbances are performed to validate the accuracy of the identified machine model including the saturation     

Optimization of an HVAC system with a strength multi-objective particle-swarm algorithm

A data-driven approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system in an office building is presented. A neural network (NN) algorithm is used to build a predictive model since it outperformed five other algorithms investigated in this paper. The NN-derived predictive model is then optimized with a strength multi-objective particle-swarm optimization (S-MOPSO) algorithm. The relationship between energy consumption and thermal comfort measured with temperature and humidity is discussed. The control settings derived from optimization of the model minimize energy consumption while maintaining thermal comfort at an acceptable level. The solutions derived by the S-MOPSO algorithm point to a large number of control alternatives for an HVAC system, representing a range of trade-offs between thermal comfort and energy consumption.     

水库水温灰色扩散模型及其在刘家峡水库中的应用

水库水温是水库水质的一个重要的参数。本文运用灰色系统建立水库水温一维(垂向)灰色扩散模型,并应用于刘家峡水库,其结果令人满意。与经典的确定水温扩散模型比较,该模型的预测结果为垂向的一条带(一个灰色区域),而不是一条线。该模型更深刻、更确切、更实际地反映了水库热结构系统。     

Unit-response function for ground heat exchanger with parallel,series or mixed borehole arrangement

A novel approach is presented that allows to predict fluid temperatures entering a Ground Heat Exchanger (GHE) for parallel, series and mixed arrangements of boreholes. The method determines at each time step the heat transfer rates occurring at each borehole so as to reproduce the fluid temperature at the GHE inlet for a specific borehole arrangement. The analytical finite line source model is used to compute the borehole wall temperatures, whereas the fluid temperatures are assumed to vary linearly along the pipes. The method requires to solve a linear system of equations at a small number of time steps. The different systems of equations for each arrangement are determined. A comprehensive 3D finite element numerical model shows good agreement with the computed fluid temperatures. The proposed approach is computationally very efficient. The fluid temperature unit response function can be convolved with any desired heat load to estimate fluid temperatures at the GHE inlet for a wide variety of scenarios.     

Computationally efficient modeling of the dynamic behavior of a portable PEM fuel cell stack

A numerically efficient mathematical model of a proton exchange membrane fuel cell (PEMFC) stack is presented. The aim of this model is to study the dynamic response of a PEMFC stack subjected to load changes under the restriction of short computing time. This restriction was imposed in order for the model to be applicable for nonlinear model predictive control (NMPC). The dynamic, non-isothermal model is based on mass and energy balance equations, which are reduced to ordinary differential equations in time. The reduced equations are solved for a single cell and the results are upscaled to describe the fuel cell stack. This approach makes our calculations computationally efficient. We study the feasibility of capturing water balance effects with such a reduced model. Mass balance equations for water vapor and liquid water including the phase change as well as a steady-state membrane model accounting for the electro-osmotic drag and diffusion of water through the membrane are included. Based on this approach the model is successfully used to predict critical operating conditions by monitoring the amount of liquid water in the stack and the stack impedance. The model and the overall calculation method are validated using two different load profiles on realistic time scales of up to 30 min. The simulation results are used to clarify the measured characteristics of the stack temperature and the stack voltage, which has rarely been done on such long time scales. In addition, a discussion of the influence of flooding and dry-out on the stack voltage is included. The modeling approach proves to be computationally efficient: an operating time of 0.5 h is simulated in less than 1 s, while still showing sufficient accuracy.     

Experiments and modeling of the hydraulic resistance and heat transfer of in-line square pin fin heat sinks with top by-pass flow

In pin-fin heat sinks, the flow within the core exhibits separation and hence does not lend itself to simple analytical boundary layer or duct flow analysis of the wall friction. In this paper, we present some findings from an experimental and modeling study aimed at obtaining physical insight into the behavior of square, in-line pin fin heat sinks. In addition to the detailed pressure measurements, the overall thermal resistance was measured as a function of Reynolds number and by-pass height. A “two-branch by-pass model” was developed, in which a one-dimensional difference approach was used to model the fluid flow through the heat sink and its top by-pass duct. Inlet and exit pressure losses were as important as the core pressure drop in establishing the overall flow and pressure drop. Comparisons were made with the data using friction and heat transfer coefficients available in the literature for infinitely long tube bundles of circular cross-section. It was shown that there is a good agreement between the temperature predictions based on the model and the experimental data at high approach velocities for tall heat sinks, however the discrepancy increases as the approach velocity and heat sink height decrease. The validated model was used to identify optimum pin spacing as a function of clearance ratio.     

Extending thermal response test assessments with inverse numerical modeling of temperature profiles measured in ground heat exchangers

Thermal response tests conducted to assess the subsurface thermal conductivity for the design of geothermal heat pumps are most commonly limited to a single test per borefield, although the subsurface properties can spatially vary. The test radius of influence is additionally restricted to 1–2 m, even though the thermal conductivity assessment is used to design the complete borefield of a system covering at least tens of squared meters. This work objective was therefore to develop a method to extend the subsurface thermal conductivity assessment obtained from a thermal response test to another ground heat exchanger located on the same site by analyzing temperature profiles in equilibrium with the subsurface. The measured temperature profiles are reproduced with inverse numerical simulations of conductive heat transfer to assess the site basal heat flow, at the location of the thermal response test, and evaluate the subsurface thermal conductivity, beyond the thermal response test. Paleoclimatic temperature changes and topography at surface were considered in the model that was validated by comparing the thermal conductivity estimate obtained from the optimization process to that of a conventional thermal response test.     

Experimental validation of an optical and thermal model of a linear Fresnel collector system

This paper describes the design and validation of a mathematical model for a solar Fresnel collector. The function of the model is to simulate the optical and thermal dynamics of a Fresnel system for heating water. The model is validated using real data gathered from a cooling plant with double effect absorption chiller located in the School of Engineering University of Seville, Spain (Experimental cooling plant is also described in the paper). Comparison of calculated and plant measured data shows that the error is lower than 3% in the optical model and within 7% in the thermal model.The model uses a new approach to include a solar tracking mirror mechanism in one axis. This tracking has been designed to maximise the reception of available solar radiation by the absorption pipe. The thermal model used is based around classical models for solar receivers and it is validated with real operating data gathered from a supervisor system.The Fresnel model has been designed with sufficient flexibility to consider different geometries and thermal parameters, and may be used to simulate the performance of a proposed Fresnel collector system at any location.     

Anticipatory Control of Wind Turbines With Data-Driven Predictive Models

The concept of anticipatory control applied to wind turbines is presented. Anticipatory control is based on the model predictive control (MPC) approach. Unlike the MPC method, noncontrollable variables (such as wind speed) are directly considered in the dynamic equations presented in the paper to predict response variables, e.g., rotor speed and turbine power output. To determine future states of the power drive with the dynamic equations, a time series model was built for wind speed. The time series model was fused with the dynamic equations to predict the response variables over a certain prediction horizon. Based on these predictions, an optimization model was solved to find the optimal control settings to improve the power output without incurring large rotor speed changes. As both the dynamic equations and time series model were built by data mining algorithms, no gradient information is available. A modified evolutionary strategy algorithm was used to solve a nonlinear constrained optimization problem. The proposed approach has been tested on the data collected from a 1.5 MW wind turbine.