Dynamic Modeling and Simulation of Deep Geothermal Electric Submersible Pumping Systems

Julian Kullick and Christoph M. Hackl
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Julian Kullick: Munich School of Engineering, Research Group “Control of Renewable Energy Systems”, Technical University of Munich, Lichtenbergstraße 4a, 85748 Garching, Germany
Christoph M. Hackl: Munich School of Engineering, Research Group “Control of Renewable Energy Systems”, Technical University of Munich, Lichtenbergstraße 4a, 85748 Garching, Germany

Energies, 2017, vol. 10, issue 10, 1-37

Abstract: Deep geothermal energy systems employ electric submersible pumps (ESPs) in order to lift geothermal fluid from the production well to the surface. However, rough downhole conditions and high flow rates impose heavy strain on the components, leading to frequent failures of the pump system. As downhole sensor data is limited and often unrealible, a detailed and dynamical model system will serve as basis for deeper understanding and analysis of the overall system behavior. Furthermore, it allows to design model-based condition monitoring and fault detection systems, and to improve controls leading to a more robust and efficient operation. In this paper, a detailed state-space model of the complete ESP system is derived, covering the electrical, mechanical and hydraulic subsystems. Based on the derived model, the start-up phase of an exemplary yet realistic ESP system in the Megawatt range—located at a setting depth of 950 m and producing geothermal fluid of 140 ? C temperature at a rate of 0.145 m 3 s ? 1 —is simulated in MATLAB/Simulink. The simulation results show that the system reaches a stable operating point with realistic values. Furthermore, the effect of self-excitation between the filter capacitor and the motor inductor can clearly be observed. A full set of parameters is provided, allowing for direct model implementation and reproduction of the presented results.

Keywords: deep geothermal; energy, system; artificial lift; electric submersible pump; ESP; simulation; model-based; condition monitoring; control; induction machine; state-space, modeling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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