Abstract
This paper presents a control strategy for the optimization of artificial lift systems (ALS) with electrical submersible pumping (ESP), executing a nonlinear model-based predictive control (NMPC) to manipulate the operating frequency of the pump and control the flow rate through the well, including specific restrictions over the system and considering its present and future behavior. The controller was designed according to a practical approach, considering the field implementation limitations and requirements. It provides significant efficiency and safety features, maximizing the revenue and operating the system in the optimal range, while respecting the system constraints and taking into account its predicted behavior. The control proposal includes the system modelling and its dynamic identification, the design of the NMPC controller, and its configuration and tuning in a simulation environment. The results of the simulation of the control system performance for an existing well are shown.
Original language | English |
---|---|
Title of host publication | 2018 IEEE ANDESCON, ANDESCON 2018 - Conference Proceedings |
Editors | Jose David Cely Callejas |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538683729 |
DOIs | |
State | Published - 5 Dec 2018 |
Event | 9th IEEE ANDESCON, ANDESCON 2018 - Cali, Colombia Duration: 22 Aug 2018 → 24 Aug 2018 |
Publication series
Name | 2018 IEEE ANDESCON, ANDESCON 2018 - Conference Proceedings |
---|
Conference
Conference | 9th IEEE ANDESCON, ANDESCON 2018 |
---|---|
Country/Territory | Colombia |
City | Cali |
Period | 22/08/18 → 24/08/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- artificial lift systems
- electrical submersible pumping
- model based predictive control
- optimal control
- system identification