Modelling and Designing The Model Predictive Control System of Turbine Angular Speed at Hydropowerplant UBP Saguling PT Indonesia Power
Abstract
Saguling Generation Business Unit (GBU) is one of hydro powerplants under PT. Indonesia Power which has vital role to produce and distribute electricity in Indonesia. The demand for electricity in Indonesia, which is fluctuative, force the plant to operate in immediate and responsive pattern. Saguling need 2 minute to connect to the transmission system from its non operating state. Plant response is controlled by manipulating guide vane opening so the water entering the turbine chamber can be maintained. 5.6 % maximum overshoot still occurs in start up process due to manual mechanism. This paper provide a design of control system using Model Predictive Control (MPC) to optimize the plant performance which is indicated by faster response time and reduced overshoot. Neural Network with Back Propagation algorithm is used to model the turbine with guide vane opening as input variable and turbine angular speed as output variable. The model is then used in MPC algorithm to compute the optimum control signals.
Keywords: Neural Network, Model Predictive Control, Guide Vane, Cost Function.
Published
How to Cite
Issue
Section
An author who publishes in the Jurnal Otomasi Kontrol dan Instrumentasi agrees to the following terms:
- The author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- Author can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgement of its initial publication in this journal.