A novel real-time based phasor and frequency estimator capable of measurements under transient conditions

Author(s):  
Abouzar Rahmati
2013 ◽  
Vol 93 (5) ◽  
pp. 1392-1397 ◽  
Author(s):  
Ljubiša Stanković ◽  
Miloš Daković ◽  
Thayananthan Thayaparan

Author(s):  
Elias Tsoutsanis ◽  
Moussa Hamadache ◽  
Roger Dixon

Abstract Recent expansion of renewable power plants have transformed the role and operation of gas turbines to a great extent. From the base load operation era we are moving into a flexible and dynamic engine operation of gas turbines. In particular, aero derivative engines that have the capacity to start up, shut down in a short time frame are becoming quite popular for both hybrid power plant arrangements and distributed electricity generation. Advances in computational intelligence, such as digital twins, have amplified the importance of condition monitoring, diagnostics and prognostics capabilities in the face of gas turbine operation. Given the dynamic operating profile of the gas turbines, it is of paramount importance to develop, tune and deploy engine models that are accurate and robust to accommodate their nonlinear behavior. Performing diagnostics in transient conditions has recently gained attention, since the gas turbines are acting as partners of renewables and they have a supporting role. Among a family of diagnostics methods, one that has real time capabilities is based on zero-dimensional engine models. This paper present a novel diagnostic approach for determining the health of a gas turbine when it works in conjunction with a wind farm in hybrid power plant. In contrary to our earlier works, where we have mathematically modeled component maps to derive the health of an engine, in this paper we propose a model-based diagnostic method without reconstructing component maps according to their degradation. Once the engine model is initially adapted to its clean condition, it is subsequently tuned in real time to reflect the changes in both the operation and degradation with respect to a benchmark engine model. Time evolving multiple component degradation scenarios for a gas turbine operating in conjunction with a wind farm, are simulated to test the accuracy and efficiency of the proposed method. From a bank of simulated measurements, data trending is performed which facilitates the detection of degradation and provides useful conclusions about the health state of the engine. This diagnostic method is suitable for gas turbines that spend most of their life time in part-load and transient operation and it forms a simple and useful tool for operators in planning their assets maintenance in a computational efficient and accurate manner.


Author(s):  
Yong Lu ◽  
Jian Li ◽  
Dongyan Hou ◽  
Lixian Miao

Abstract Fully variable valve technology of diesel engine can change the movement parameters of valve flexibly, and then the performance of engine can be improved. But the actual valve movement can’t track the optimal valve profile due to the nonlinear characteristics of hydraulic system in transient work conditions, which make the engine performance be deteriorated. To solve the problem, the paper introduced the idea of dynamic programming (DP) into the control of FVVA system. Firstly, the paper presented a new electro-hydraulic FVVA system. To verify the FVVA system, the GT-suite models of FVVA system and engine were built. Secondly, for the purpose of achieving optimal performance, based on the NSGA-II genetic algorithm, we got the database of the optimal valve profile movement parameters using modeFRONTIER platform. In database, there are multiple feasible solutions for one work condition. To achieve the optimal engine performance in every cycle, according to the real-time valve movement profile, the controller will choose different solutions with DP method in one cycle based on the database obtained before. The DP controller can make the engine performance to be optimal according to the real-time valve profile in transient conditions. In steady conditions, optimal valve profiles can be reached by a PID controller. Thirdly, the DP controller and PID controller were designed with Simulink separately. The DP controller will adjust valve control parameters in one cycle and the PID controller will adjust the parameters cycle by cycle. At last, the DP-PID controller was compared with the single PID controller which adjust control parameters once in one cycle. The simulation results show that the performance of engine with DP-PID controller is improved compared to the PID controller especially in transient conditions. The average brake power can be improved by 3.3% to 4.7% compared to single PID controller.


Author(s):  
S. M. Saqib ◽  
R. J. Urbanic

To understand the different aspects of the laser cladding (LC) process, process models can be of aid. Presently, the correct parameter settings for different manufacturing processes, such as machining and casting, are based on simulation tools that can evaluate the influence of the process parameters for different conditions. However, there are no comprehensive, focused simulation process planning tools available for the LC process. In the past, most of the research has focused on the experimentally based optimization strategies for a process configuration, typically for a single track bead in steady-state conditions. However, an understanding of realistic transient conditions needs to be explored for effective process planning simulation tools and build strategies to be developed. A set of cladding experiments have been performed for single and multiple bead scenarios, and the effects of the transient conditions on the bead geometry for these scenarios have been investigated. It is found that the lead-in and lead-out conditions differ, corner geometry influences the bead height, and when changing the input power levels, the geometry values oscillate differently than the input pulses. Changes in the bead geometry are inherent when depositing material; consequently, real-time adjustments for the process setting are essential. The dynamic, time varying heating and solidification, for multiple layer scenarios, leads to challenging process planning and real-time control strategies.


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