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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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
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.
Fareed ud Din,
Abdul Rehman Raza,
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.
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