Nuclear power plant steam turbine—Modeling for model based control purposes

The nature of the processes taking place in a nuclear power plant (NPP) steam turbine is the reason why their modeling is very difficult, especially when the model is intended to be used for on-line optimal model based process control over a wide range of operating conditions, caused by changing electrical power demand e.g. when combined heat and power mode of work is utilized. The paper presents three nonlinear models of NPP steam turbine, which are: the static model, and two dynamic versions, detailed and simplified. As the input variables, the models use the valve opening degree and the steam flow properties: mass flow rate, pressure and temperature. The models enable to get access to many internal variables describing process within the turbine. They can be treated as the output or state variables. In order to verify and validate the models, data from the WWER-440/213 reactor and the 4 CK 465 turbine were utilized as the benchmark. The performed simulations have shown good accordance of the static and dynamic models with the benchmark data in steady state conditions. The dynamic models also demonstrated good behavior in transient conditions. The models were analyzed in terms of computational load and accuracy over a wide range of varying inputs and for different numerical calculation parameters, especially time step values. It was found that the detailed dynamic model, due to its complexity and the resultant long calculation time, is not applicable in advanced control methods, e.g. model predictive control. However, the introduced simplifications significantly decreased the computational load, which enables to use the simplified model for on-line control.     

Modelling and simulation of steam turbine processes: individual models for individual tasks

Within power plants, several physical, chemical and mechanical processes are conducted to transfer the energy, stored in fossil fuel, into electrical energy. This energy conversion is divided into several stages. Hitherto, the largest conventional power plants employ steam turbines as prime movers to drive a generator. Hence, a steam turbine is one module to convert heat energy into mechanical energy. And thus it is one link in the chain of energy conversions with the aim of generating electrical energy. Today, steam turbine industry faces numerous challenges concerning efficiency, commissioning time, start-up times, operation, availability, safety, cost-effectiveness, etc. Many of these tasks can be supported by simulating the transient operational behaviour of the turbine in advance. For example, the commissioning time can be shortened if the turbine controllers are initialized with well-tuned pre-set parameters; cost-effectiveness can be increased by setting aside unnecessary devices and exactly determining material specifications; safety may be increased by predicting the impacts of failures and thus taking the necessary precautions. Different tasks require different details regarding the employed turbine simulation model. Thus, the turbine controller may be well tuned with less complex simulation models of turbine, generator and electrical grid, whereas detailed studies of failures, mainly the transient behaviour which may lead to serious damages, may require detailed modelling of the turbine-internal thermodynamic processes. Here, a brief overview of models which simulate the transient thermodynamic behaviour of a steam turbine is presented. Three different approaches will be introduced and compared with respect to different operating situations. Also, special attention is directed towards the time dependence of critical states, mainly turbine speed and pressure development in certain areas. The first model is based on a simple, linear approach and is suitable of giving a quick overview. The second one incorporates more details and is useful if the operating point is close to the design point. Finally, the last model incorporates mass and energy balances as well as the major non-linearities. Hence it depicts the turbine behaviour over a large range of operating points.     

Stall-delay modelling of wind turbine blades

Most aerodynamic design tools for horizontal-axial wind turbines are based on the blade-element momentum theory (BEM). Due to the nature of this theory, the design tools need 2-D steady sectional lift and drag curves as an input. In practice, flow over a wind turbine rotor blade is neither two-dimensional nor steady, and is affected by rotation. Pioneering experiments have identified a consequence: at inboard rotor blade sections stall is delayed. This so-called Himmelskamp effect [1] gives a larger lift than predicted and, as a result, a higher power and loading than expected. Consequently, an aerodynamic model is needed to explain and predict sectional lift and drag under rotating conditions. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Spatial dependencies of wind power and interrelations with spot price dynamics

Wind power has seen strong growth over the last decade and increasingly affects electricity spot prices. In particular, prices are more volatile due to the stochastic nature of wind, such that more generation of wind energy yields lower prices. Therefore, it is important to assess the value of wind power at different locations not only for an investor but for the electricity system as a whole. In this paper, we develop a stochastic simulation model that captures the full spatial dependence structure of wind power by using copulas, incorporated into a supply and demand based model for the electricity spot price. This model is calibrated with German data. We find that the specific location of a turbine – i.e., its spatial dependence with respect to the aggregated wind power in the system – is of high relevance for its value. Many of the locations analyzed show an upper tail dependence that adversely impacts the market value. Therefore, a model that assumes a linear dependence structure would systematically overestimate the market value of wind power in many cases. This effect becomes more important for increasing levels of wind power penetration and may render the large-scale integration into markets more difficult.     

Modelling the clogging of gas turbine filter houses in heavy-duty power generation systems

ABSTRACT

A prognostic approach based on a MISO (multiple inputs and single output) fuzzy logic model was introduced to estimate the pressure difference across a gas turbine (GT) filter house in a heavy-duty power generation system. For modelling and simulation of clogging of the GT filter house, nine real-time process variables (ambient temperature, humidity, ambient pressure, GT produced load, inlet guide vane position, airflow rate, wind speed, wind direction and PM10 dust concentration) were fuzzified using a graphical user interface within the framework of an artificial intelligence-based methodology. The results revealed that the proposed fuzzy logic model produced very small deviations and showed a superior predictive performance than the conventional multiple regression methodology, with a very high determination coefficient of 0.974. A complicated dynamic process, such as clogging phenomenonin heavy-duty GT system, was successfully modelled due to high capability of the fuzzy logic-based prognostic approach in capturing the nonlinear interactions.     

Dynamic modelling and design of various robust sliding mode controls for the wind turbine with estimation of wind speed

The main propose of this paper is extracting the maximum efficiency from variable speed wind turbine, which is modelled as an electromechanical system with two masses dynamics. The maximum efficiency can be obtained by tracking the optimal rotor speed, which is controlled by the generator torque as the input. One of the most important information that is required for designing of the control system is the measurement of the effective wind velocity. In this paper, a new ANFIS-based method for estimating the effective wind velocity is developed. The aerodynamic torque has a direct relationship with the power coefficient. So in this paper, power coefficient of WindPACT 1.5 MW turbine as a function of tip speed ratio (TSR) and blade pitch angle is considered. Then, three control methods based on high order sliding mode controllers are examined. The rotor speed and the wind velocity are the only variables required in the design of second and third order sliding mode controllers. FAST (Fatigue, Aerodynamics, Structures and Turbulence) is valid software that offers a fairly complete model of the wind turbine. Results of this paper are validated using FAST. Performance of the designed controllers is compared in terms of the generator torque and desired rotor speed tracking. Finally, the doubly fed induction generator (DFIG) is controlled such that the objectives of reactive power minimization and tracking the desired generator torque are achieved. Two main hindrances in designing the control systems are the uncertainties and the lack of sufficient information on measurements. Therefore robust performance of designed controllers against the model uncertainties is investigated.     

Scheduling electric power production at a wind farm

We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization algorithm with a small world network structure to solve the model. The solution generated by the algorithm defines the operational status of wind turbines for a scheduling horizon selected by a decision maker. Different operational scenarios are constructed based on time series data of electricity price, grid demand, and wind speed. The computational results provide insights into management of a wind farm.     

Status of large scale wind turbine technology development abroad?

To facilitate the large scale (multi-megawatt) wind turbine development in China, the foreign e?orts and achievements in the area are reviewed and summarized. Not only the popular horizontal axis wind turbines on-land but also the o?shore wind turbines, vertical axis wind turbines, airborne wind turbines, and shroud wind turbines are discussed. The purpose of this review is to provide a comprehensive comment and assessment about the basic work principle, economic aspects, and environmental impacts of turbines.     

Evaluation and enhancement of dynamic performance of a microgrid including PV and wind generation systems

Large participation of renewable energy sources with rapidly varying inputs can affect the performance of a microgrid system. This article develops a detailed non-linear and small-signal dynamic model of a microgrid that includes photovoltaic (PV), wind and conventional small-scale generation along with their power electronics interfaces and the filters. The role of the extent of generation mix of the distributed generators (DGs) for satisfactory operation of the system has been investigated through small-signal dynamic model. It was observed that there exist critical values of PV and wind power above which the microgrid performance degrades. The enhancement of performance of the microgrid through various control inputs have been evaluated through decomposition techniques. Simulation studies showed that an energy storage system-based central supervisory controller and also control of PV system can improve transient performance when violations of proper generation mix of the DGs occur.     

Two Way Coupled Micro/Meso Scale Method for Wind Farms

Wind turbines extract energy from the approaching flow field resulting in reduced wind speeds, increased turbulence and a wake downstream of the wind turbine. The wake has a multitude of negative effects on downstream wind turbines. This includes reduced efficiency and increased unsteadiness resulting in vibrations and potentially in material fatigue. Moreover, the maintenance can increase compared to non-interfering wind turbines. The simulation of these effects is challenging. Computational fluid dynamics (CFD) simulations of these large and complex geometries requires exceedingly large computational resources. With present Reynolds Averaged Navier-Stokes (RANS) or Large Eddy Simulation (LES) based CFD methods it is virtually impossible to perform such simulations of the interaction between individual wind turbines in a complete wind turbine farm. Coupling to the mesoscale accounting for local weather situations becomes yet more challenging. This is due to the wide range of length and time scales that have to be considered for these simulations and therefore the tremendous computational power needed to perform such simulations. To investigate these effects we propose to combine ideas from existing methods, the Coarse-Grid-CFD (CGCFD) ( [1]) developed at the KIT and the meso-/ micro scale method developed at the University of Thessaloniki ( [2]). Goal of the proposed methodology is to provide a numerical method that allows to implement a wind farm in a meso-scale weather simulation which includes two-way coupling. Thus both the micro and the meso scale wind and energy production of wind farms can be addressed. This proposed multi scale coupling strategy can also be applied in two hierarchies reducing the numerical effort of the global approach yet more. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An airfoil optimization technique for wind turbines

Optimization algorithms coupled with computational fluid dynamics are used for wind turbines airfoils design. This differs from the traditional aerospace design process since the lift-to-drag ratio is the most important parameter and the angle of attack is large. Computational fluid dynamics simulations are performed with the incompressible Reynolds-averaged Navier–Stokes equations in steady state using a one equation turbulence model. A detailed validation of the simulations is presented and a computational domain larger than suggested in literature is shown to be necessary. Different approaches to parallelization of the computational code are addressed. Single and multiobjective genetic algorithms are employed and artificial neural networks are used as a surrogate model. The use of artificial neural networks is shown to reduce computational time by almost 50%.     

Advanced Control Design for Wind Turbines

In this contribution, the concept of a general design platform for control system of wind turbines is proposed. Different models of wind turbine systems are summarized, a novel control strategy for wind turbine control is proposed as a general platform for control system design. Simulation results are presented demonstrating the success of the proposed control method based on one of the chosen models for the design platform. A benchmark model (NREL) is chosen for the platform in order to adjust the control system design. Finally, the design process of control system based on the general platform is given and explained. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Aeroelastic analysis of large horizontal wind turbine baldes?

A nonlinear aeroelastic analysis method for large horizontal wind turbines is described. A vortex wake method and a nonlinear ?nite element method (FEM) are coupled in the approach. The vortex wake method is used to predict wind turbine aero-dynamic loads of a wind turbine, and a three-dimensional (3D) shell model is built for the rotor. Average aerodynamic forces along the azimuth are applied to the structural model, and the nonlinear static aeroelastic behaviors are computed. The wind rotor modes are obtained at the static aeroelastic status by linearizing the coupled equations. The static aeroelastic performance and dynamic aeroelastic responses are calculated for the NH1500 wind turbine. The results show that structural geometrical nonlinearities signi?cantly reduce displacements and vibration amplitudes of the wind turbine blades. Therefore, structural geometrical nonlinearities cannot be neglected both in the static aeroelastic analysis and dynamic aeroelastic analysis.     

The impact of wind uncertainty on the strategic valuation of distributed electricity storage

The intermittent nature of wind energy generation has introduced a new degree of uncertainty to the tactical planning of energy systems. Short-term energy balancing decisions are no longer (fully) known, and it is this lack of knowledge that causes the need for strategic thinking. But despite this observation, strategic models are rarely set in an uncertain environment. And even if they are, the approach used is often inappropriate, based on some variant of scenario analysis—what-if analysis. In this paper we develop a deterministic strategic model for the valuation of electricity storage (a battery), and ask: “Though leaving out wind speed uncertainty clearly is a simplification, does it really matter for the valuation of storage?”. We answer this question by formulating a stochastic programming model, and compare its valuation to that of its deterministic counterpart. Both models capture the arbitrage value of storage, but only the stochastic model captures the battery value stemming from wind speed uncertainty. Is the difference important? The model is tested on a case from Lancaster University’s campus energy system where a wind turbine is installed. From our analysis, we conclude that considering wind speed uncertainty can increase the estimated value of storage with up to 50 % relative to a deterministic estimate. However, we also observe cases where wind speed uncertainty is insignificant for storage valuation.     

Stochastic Modelling of Wind Speed Power Production Correlations

Based on measurements we investigate the velocity-power characteristic of a 2 MW wind turbine. We apply a stochastic analysis where we describe the evolution of the power output with a Langevin equation, with special respect to short-time fluctuations in wind speed. Standard procedures, such as the IEC 61400-12 standard, are limited due to the fact that only mean values over several minutes of wind speed and power output are considered. According to this, short-time dynamics of wind and power fluctuations are usually not taken into account. We introduce an improved method which enables us to extract these dynamics of the power characteristic from the measured data. In particular, we get the response dynamics of the power L (u (t)) via the estimation of Kramers-Moyal coefficients, describing its evolution in time (t) with a Langevin equation where we separate the power output into a relaxation and a noise part. A fixed-point analysis provides the required power characteristic. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A numerical investigation on the dynamic stall of a vertical axis wind turbine

In the last years, for home user, the wind turbine with vertical axis (VAWT) began to be more attractive due benefits in exploitation. In terms of aerodynamics, when the wind speed approaches the speed of operation (low value of tip speed ratio -TSR) the blade airfoil exceeds the critical angle of incidence for static conditions. Angle of incidence varies quickly across blade and the blade works in dynamic stall condition. The goal of the present work is to investigate the two-dimensional dynamic stall phenomenon around the NACA 0012 airfoil at relatively low Reynolds. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Wind energy prediction using a two-hidden layer neural network

The power generated by wind turbines changes rapidly because of the continuous fluctuation of wind speed and air density. As a consequence, it can be important to predict the energy production, starting from some basic input parameters. The aim of this paper is to show that a two-hidden layer neural network can represent a useful tool to carefully predict the wind energy output. By using proper experimental data (collected from three wind farm in Southern Italy) in combination with a back propagation learning algorithm, a suitable neural architecture is found, characterized by the hyperbolic tangent transfer function in the first hidden layer and the logarithmic sigmoid transfer function in the second hidden layer. Simulation results are reported, showing that the estimated wind energy values (predicted by the proposed network) are in good agreement with the experimental measured values.     

An Investigation of the Separate Flow and Stall-delay for Horizontal-Axis Wind Turbine

The flow characteristics and stall delay phenomenon of a stall regulated wind turbine rotor due to blade rotation in steady state non-yawed conditions are investigated. An incompressible Reynolds-averaged Navier-Stokes solver is applied to carry out the separate flow cases at high wind speeds from 11 m/s to 25 m/s with an interval of 2 m/s. The objective of the present research effort is to validate a first-principles based approach for modeling horizontal axis wind turbines (HAWT) under stalled flow conditions using NREL/Phase VI rotor data. The computational results are compared with the predicted values derived by a new stall-delay model and blade element momentum (BEM) method. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

农村小型风力发电机的控制与并网仿真

设计了双馈风力发电机组的定子磁链矢量控制系统,构造了容量为9MW的风力发电系统;通过MATLAB软件,分别在变风速和恒定风速两种情况时,对风力发电系统并网进行仿真.仿真结果表明,利用矢量变换技术的控制方法,风力发电系统可以实现有功功率和无功功率的快速解耦并且动态响应快,跟随性能好.