Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant. (15th September 2020)
- Record Type:
- Journal Article
- Title:
- Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant. (15th September 2020)
- Main Title:
- Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant
- Authors:
- Haji Haji, Vahab
Fekih, Afef
Monje, Concepción Alicia
Fakhri Asfestani, Ramin - Abstract:
- Abstract: This paper proposes an adaptive model predictive control (AMPC) approach with online parameter estimation for a V94.2 gas turbine mounted in the Damavand combined cycle power plant (CCPP). The AMPC is designed to simultaneously maintain the speed and temperature responses of the gas turbine within their desired levels in the presence of frequency drop or change in load demand. It implements an online parameter estimation and adaptive mechanism to enable the model parameters to follow any change in the V94.2 gas turbine power plant (GTPP) model and provide the best control performance possible. The effectiveness of the AMPC approach is assessed using an estimated model of a V94.2 gas turbine mounted in the Damavand CCPP. Additional analysis is also performed via a comparison study encompassing a classical MPC, H ∞, and μ − s y n t h e s i s robust control strategies and considering reference tracking performance, transient and steady-state responses, disturbance rejection capabilities, and robustness to parameter variations. The obtained results confirmed the effectiveness of the proposed approach in improving the robust stability and dynamics of the V94.2 GTPP in the presence of measurement noise, frequency disturbance, and unmodeled power plant dynamics along with its superior performance in terms of tracking capability and disturbance rejection properties. Highlights: An adaptive model predictive control for the speed and temperature of a gas turbine. A designAbstract: This paper proposes an adaptive model predictive control (AMPC) approach with online parameter estimation for a V94.2 gas turbine mounted in the Damavand combined cycle power plant (CCPP). The AMPC is designed to simultaneously maintain the speed and temperature responses of the gas turbine within their desired levels in the presence of frequency drop or change in load demand. It implements an online parameter estimation and adaptive mechanism to enable the model parameters to follow any change in the V94.2 gas turbine power plant (GTPP) model and provide the best control performance possible. The effectiveness of the AMPC approach is assessed using an estimated model of a V94.2 gas turbine mounted in the Damavand CCPP. Additional analysis is also performed via a comparison study encompassing a classical MPC, H ∞, and μ − s y n t h e s i s robust control strategies and considering reference tracking performance, transient and steady-state responses, disturbance rejection capabilities, and robustness to parameter variations. The obtained results confirmed the effectiveness of the proposed approach in improving the robust stability and dynamics of the V94.2 GTPP in the presence of measurement noise, frequency disturbance, and unmodeled power plant dynamics along with its superior performance in terms of tracking capability and disturbance rejection properties. Highlights: An adaptive model predictive control for the speed and temperature of a gas turbine. A design aiming at mitigating frequency drops and/or changes in load demand. Implementation to a V94.2 gas turbine mounted in the Damavand CCPP. Analytical and comparison analysis between the AMPC and MPC, H∞, and μ-synthesis. … (more)
- Is Part Of:
- Energy. Volume 207(2020)
- Journal:
- Energy
- Issue:
- Volume 207(2020)
- Issue Display:
- Volume 207, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 207
- Issue:
- 2020
- Issue Sort Value:
- 2020-0207-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09-15
- Subjects:
- V94.2 gas turbine -- Adaptive model predictive control -- Robust control -- H∞ -- μ−synthesis
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2020.118259 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13734.xml