Research Papers: Gas Turbines: Electric Power

Model Predictive Control of Offshore Power Stations With Waste Heat Recovery

[+] Author and Article Information
Leonardo Pierobon

Department of Mechanical Engineering,
Technical University of Denmark,
Kongens Lyngby 2800, Denmark
e-mail: lpier@mek.dtu.dk

Richard Chan

Industrial Learning Systems, Inc.,
Pittsburgh, PA 15101
e-mail: khchan@ilsystems.net

Xiangan Li

Department of Chemical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15213
e-mail: lixiangan05572@gmail.com

Krishna Iyengar

Department of Chemical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15213
e-mail: krishna@alumni.cmu.edu

Fredrik Haglind

Associate Professor
Department of Mechanical Engineering,
Technical University of Denmark,
Kongens Lyngby 2800, Denmark
e-mail: frh@mek.dtu.dk

Erik Ydstie

Department of Chemical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15213
e-mail: ydstie@cmu.edu

1Corresponding author.

Contributed by the Electric Power Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received March 15, 2015; final manuscript received October 23, 2015; published online February 9, 2016. Assoc. Editor: Rakesh K. Bhargava.

J. Eng. Gas Turbines Power 138(7), 071801 (Feb 09, 2016) (13 pages) Paper No: GTP-15-1093; doi: 10.1115/1.4032314 History: Received March 15, 2015; Revised October 23, 2015

The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive control (MPC) coupled with a steady-state performance optimizer has been developed in the simulink language and is documented in the paper. The test case is the regulation of a power system serving an oil and gas platform in the Norwegian Sea. One of the three gas turbines is combined with an organic Rankine cycle (ORC) turbogenerator to increase the energy conversion efficiency. Results show a potential reduction of frequency drop up to 40% for a step in the load set-point of 4 MW, compared to proportional–integral control systems. Fuel savings in the range of 2–3% are also expected by optimizing on-the-fly the thermal efficiency of the plant.

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Fig. 4

Transfer function model of the gas turbine on the simulink block-diagram environment as provided by the engine manufacturer

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Fig. 3

Top-level scheme of the gas turbine connected to the ORC power module on the simulink block-diagram environment

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Fig. 2

Saturation curve of cyclopentane in a T–s diagram, showing the thermodynamic cycle state points of the ORC system

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Fig. 1

Simplified layout of the power system on the Draugen offshore oil and gas platform; the exhaust gases of one engine feed the ORC module. The two remaining gas turbines are not shown.

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Fig. 5

Heat exchanger discretized model

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Fig. 10

Dynamic response of the combined cycle unit in normal operation and after a 15% deterioration of the overall heat transfer coefficient induced by fouling in the tubes of the OTB: (a) frequency, (b) valve position, (c) degree of superheating, (d) rotational speed of the pump, (e) shaft power of the gas turbine, and (f) shaft power of the ORC unit

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Fig. 11

Dynamic response of the combined cycle unit for two different control modes, i.e., operation at peak efficiency and constant stack temperature

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Fig. 12

Duration curve of the electric load in 2012 on the Draugen oil and gas platform

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Fig. 6

Effect of the pump speed on the performance of the combined cycle unit and points of maximum thermal efficiency. The curves are given for four load set-points of the combined cycle plant.

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Fig. 8

Dynamics of the (a) frequency and (b) valve position as delivered by the controller of the gas turbine manufacturer and by the MPC system for a load step of 4 MW

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Fig. 9

Comparison of the dynamic metrics given by the controller of the gas turbine manufacturer and by the MPC system: (a) frequency undershooting and (b) rise time

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Fig. 7

(a) Degree of superheating T6−T5 and (b) stack temperature T11 as a function of the combined cycle load. The rotational speed of the pump is set to the optimal value, see Fig. 6.




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