Disruptions and Malfunction Control in ORC using Spiral Predictive Model
American Journal of Electrical Power and Energy Systems
Volume 2, Issue 6, November 2013, Pages: 144-148
Received: Nov. 3, 2013; Published: Nov. 20, 2013
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Authors
Fareed ud Din, Faculty of Engineering and Technology, Lahore, Pakistan
Abdul Rehman Raza, Faculty of Engineering and Technology, Lahore, Pakistan
Muhammad Azam, Faculty of Engineering and Technology, Lahore, Pakistan
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Abstract
This paper provides a critical and analytical assay in the process vicinity of an Organic Rankine Cycle (ORC) resulting in a representation of a controlling model named as Spiral Model as the best approach to implement for an efficient Plant Management (PM) and Risk Mitigation Planning (RMP), focusing on the robust and elegant energy production. There have been so many predictive and sensing process models presented for a gist and substantial control of the ORC plant in recent years but the proposed Spiral Predictive Model (SPM), eliminating all the limitation of all previously implemented models, provides the robustness by performing all the roles in increments; e.g. in the changing controllers, complex time-frequency characteristics, fault detectors for turbines against disruptions and the multi-switching techniques needs to be cascaded ahead of time with predictive and detective techniques. The proposed model optimizes the performance of ORC by response tracking and recursive correction which relegates the errors and sudden disturbance in the process flow. Fast response and recursive correction nicely handles Demand Response (DR) and parameters variations at different working modules which ultimately provide the dynamic performance capability. This study will be elaborating efficient model design and implementation to conjure up a well-designed working flow in an ORC plant.
Keywords
Spiral Predictive Model (SPM), Organic Rankine Cycle (ORC), Demand Response (DR), Plant Management (PM), Risk Mitigation Planning (RMP)
To cite this article
Fareed ud Din, Abdul Rehman Raza, Muhammad Azam, Disruptions and Malfunction Control in ORC using Spiral Predictive Model, American Journal of Electrical Power and Energy Systems. Vol. 2, No. 6, 2013, pp. 144-148. doi: 10.11648/j.epes.20130206.14
References
[1]
Main-Steam Temperature Control for Ultra- Supercritical Unit Using Multi-Model Predictive Strategy, Ding Li, Hong Zhou, 978-1-4673-4584-December 2012 IEEE
[2]
V. Maizza*, A. Maizza, Unconventional working Fluids in organic Rankine-cycles for waste energy recovery systems (2000)
[3]
Samuel Sami, A concept of power generator using wind turbine hydrodynamic retarder, and organic Rankine cycle drive, Journal Of Renewable And Sustainable Energy 5, 023123 (2013)
[4]
B. Boukhezzar, H. Siguerdidjane, and M. Maureenhand, "Nonlinear control of variable-speed wind turbines for generator torque limiting and power optimization," J. Sol. Energy Eng. 128(4), 516–530 (2006).
[5]
I. Daubechies, Ten Lectures on Wavelets (Society for Industrial and Applied Mathematics, Philadelphia, PA, 1992).
[6]
A. Kusiak, Z. Song, and H. Zheng, "Anticipatory control of wind turbines with data-driven predictive models," IEEE Trans. Energy Convers. 24(3), 766–774 (2009).
[7]
Gang Zhao, Dongxiang Jiang, Jinghui Diao, Lijun Qian, "Application of wavelet time-frequency analysis On fault diagnosis for steam turbine, Surveillance 5CETIM Senlis2004
[8]
R. Cori and C. Maffezzoni, "Practical optimal control of a drum boiler power plant," Automatica, vol. 20, pp.163-173, 1984.
[9]
G. Pellegrinetti and J. Bentsman, "H Controller design for boilers, Int. J. Robust Nonlinear Control," vol. 4, pp.645-671, 1994.
[10]
B. W. Hogg and N. M. Ei-Rabaie, "Multivariable generalized predictive control of a boiler system," IEEE Trans. Energy Convers, vol. 6, pp. 282-288, June. 1991.
[11]
Un-Chul Moon and Kwang Y. Lee, "An Adaptive Dynamic Matrix Control With Fuzzy-Interpolated Step-Response Model for a Drum- Type Boiler-Turbine System," IEEE Trans. Energy Convers, vol. 26, pp. 393-401, June. 2011.
[12]
Xiangjie Liu, Xuewei Tu, Guolian Hou and Jihong Wang, "The Dynamic Neural Network Model of a Ultra Super-critical Steam Boiler Unit," American Control Conference on O'Farrell Street, San Francisco CA, USA, June 29-June 01,2011.
[13]
Adarsha Swarnakar, Horacio Jose Marquez and Tongwen Chen, "New Scheme on Robust Observer-Based Control Design for Interconnected Systems With Application to an Industrial Utility Boiler," IEEE Transactions on control systems technology, vol.16, pp. 539-547, May.2008.
[14]
Shaoyuan Li, Hongbo Liu, Wen-Jian Cai, Yeng-Chai Soh and Li-Hua Xie, "New Coordinated Control Strategy for Boiler-Turbine System of Coal-Fired Power Plant," IEEE Transactions on control systems technology, vol.13, PP. 943-954, Nov.2005.
[15]
Kang Y. Lee, Joel H. Van Sickel, Jason A. Hoffman, Won-Hee Jung and Sung-Ho Kim, "Controller Design for a Large-Scale Ultrasupercritical Once-Through Boiler Power Plant," IEEE Trans. Energy Convers, vol. 25, pp. 1063-1070, Dec 2010.
[16]
Ajay Gautam, Yun-Chung Chu and Yeng Chai Soh, "Optimization Dynamic Policy for Receding Horizon Control of Linear Time-Varying Systems with Bounded Disturbances," IEEE Trans. Autom. Control, vol. 57, PP. 973-988, April 2012.
[17]
Y.I.Lee and B.Kouvaritakis, "Receding horizon output feedback control for linear systems with input saturation," IEE. Proc.-Control Theory Appl., Vol. 148, pp. 109-115, March 2001.
[18]
Wang, W.J., McFadden, P.D., "Early Detection of Gear Failure by Vibration Analysis–I. Calculation of the Time-Frequency Distribution", Journal of Mechanical Systems and Signal Processing, 1993,7(3):193-203.
[19]
Katshuhiko Shibata, Atsushi Takkahashi, Takuya Shira "Fault Diagnosis of Rotating Machinery Through Visualization of Sound Signals", journal of Mechanical Systems and Signal Processing, 2000 14(2): 229-241.
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