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Mohamed O, Wang J, Khalil A, et al. Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency. Springerplus. 2016;5(1):980doi: 10.1186/s40064-016-2679-2.
Mohamed, O., Wang, J., Khalil, A., & Limhabrash, M. (2016). Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency. SpringerPlus, 5(1), 980. https://doi.org/10.1186/s40064-016-2679-2
Mohamed, Omar, et al. "Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency." SpringerPlus vol. 5,1 (2016): 980. doi: https://doi.org/10.1186/s40064-016-2679-2
Mohamed O, Wang J, Khalil A, Limhabrash M. Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency. Springerplus. 2016 Jul 04;5(1):980. doi: 10.1186/s40064-016-2679-2. eCollection 2016. PMID: 28443216; PMCID: PMC5396491.
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Springerplus. 2016 Jul 04;5(1):980. doi: 10.1186/s40064-016-2679-2. eCollection 2016.

Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency.

SpringerPlus

Omar Mohamed, Jihong Wang, Ashraf Khalil, Marwan Limhabrash

Affiliations

  1. Department of Electrical Engineering, Princess Sumaya University for Technology, P.O. Box 1438, Al-Jubaiha, 11941 Jordan.
  2. School of Engineering, University of Warwick, Coventry, CV4 7AL UK.
  3. Department of Electrical Engineering, University of Benghazi, P.O. Box 9476, Benghazi, Libya.
  4. Production Department, General Electric Company of Libya, Tripoli, Libya.

PMID: 28443216 PMCID: PMC5396491 DOI: 10.1186/s40064-016-2679-2

Abstract

This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load-frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.

Keywords: Gas turbines; Model predictive control (MPC); Natural gas industry; Subspace identification

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