Elvira Marie B. Aske
Statoil
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Featured researches published by Elvira Marie B. Aske.
Computers & Chemical Engineering | 2008
Elvira Marie B. Aske; Stig Strand; Sigurd Skogestad
Abstract In many cases, economic optimal operation is the same as maximum plant throughput, which is the same as maximum flow through the bottleneck(s). This insight may greatly simplify implementation. In this paper, we consider the case where the bottlenecks may move, with parallel flows that give rise to multiple bottlenecks and with crossover flows as extra degrees of freedom. With the assumption that the flow through the network is represented by a set of units with linear flow connections, the maximum throughput problem is then a linear programming (LP) problem. We propose to implement maximum throughput by using a coordinator model predictive controller (MPC). Use of MPC to solve the LP has the benefit of allowing for a coordinated dynamic implementation. The constraints for the coordinator MPC are the maximum flows through the individual units. These may change with time and a key idea is that they can be obtained with almost no extra effort using the models in the existing local MPCs. The coordinator MPC has been tested on a dynamic simulator for parts of the Karsto gas plant and performs well for the simulated challenges.
international conference on control applications | 2014
Alexey Pavlov; Dinesh Krishnamoorthy; Kjetil Fjalestad; Elvira Marie B. Aske; Morten Fredriksen
In this paper we describe control challenges related to operation of oil wells equipped with Electric Submersible Pumps (ESP) and formalize them in a control problem setting in the language of control system engineers. Then we present a simple dynamic model of an oil well equipped with ESP. This model can be used for controller development. To solve this problem, we propose a Model Predictive Control (MPC) strategy and present experimental results of an MPC controller successfully tested in a large scale test facility with a full scale ESP, live crude oil in an emulated oil well.
IFAC Proceedings Volumes | 2007
Elvira Marie B. Aske; Sigurd Skogestad; Stig Strand
Abstract In many cases, optimal operation for a plant is the same as maximum throughput. In this case a rigorous model for the plant is not necessary if we are able to identify the bottleneck. Optimal operation is the same as maximum throughput in the bottleneck. If the bottleneck does not move, this can be realized with singleloop controller from the throughput manipulator to the bottleneck. However, if the bottleneck moves, single-loop control would require reassignment of loops which is undesirable. A better approach is then to use a multivariable coordinator controller since input and output constrains are directly included in the problem formulation.
Computer-aided chemical engineering | 2009
Elvira Marie B. Aske; Sigurd Skogestad
To realize maximum throughput, tight control of the bottleneck unit(s) is necessary. Dynamic degrees of freedom can be used to obtain tighter bottleneck control. Here, “dynamic” means that the degree of freedom has no steady-state effect on plant operation, like most inventories (levels). Nevertheless, temporary changes of inventories can allow for dynamic changes in the flow through the bottleneck that keeps the process closer to its bottleneck constraint and increase the throughput.
IFAC Proceedings Volumes | 2005
Elvira Marie B. Aske; Stig Strand; Sigurd Skogestad
Abstract Model predictive control (MPC) is implemented on several distillation columns at the Karsto gas processing plant, Norway. The paper describes the procedure in the implementation of MPC at a deethanizer using the SEPTIC * MPC tool, including design, estimator development, model development and tuning. For the deethanizer, the variance in the product quality has been reduced with about 50%. The number of flaring episodes has also been reduced. An increase in impurities has not been challenged yet, so the average reflux flow and steam consumption to feed ratios are almost unaltered. * SEPTIC: Statoil Estimation and Prediction Tool for Identification and Control
Computer-aided chemical engineering | 2006
Elvira Marie B. Aske; Stig Strand; Sigurd Skogestad
In this paper we suggest a “coordinator MPC” to perform dynamic real-time optimization (DRTO) on a plant. We consider the case where the plant economic criteria can be simplified to maximize the throughput in the plant. A measure for the distance to the bottleneck is formulated for a distillation column and the responses from feed to remaining capacity are expressed by experimental step-response models. The coordinator is demonstrated on a dynamic simulator and performs well for the simulated challenges.
IFAC Proceedings Volumes | 2009
Elvira Marie B. Aske; Stig Strand; Sigurd Skogestad
This thesis discusses plantwide control configuration with focus on maximizing throughput. The most important plantwide control issue is to maintain the mass balances in the plant. The inventory control system must be consistent, which means that the mass balances are satisfied. Self-consistency is usually required, meaning that the steady-state balances are maintained with the local inventory loops only. We propose the self-consistency rule to evaluate consistency of an inventory control system. In many cases, economic optimal operation is the same as maximum plant throughput, which corresponds to maximum flow through the bottleneck(s). This insight may greatly simplify implementation of optimal operation, without the need for dynamic optimization based on a detailed model of the entire plant. Throughput maximization requires tight bottleneck control. In the simplest case when the bottleneck is fixed to one unit, maximum throughput can be realized with single-loop control. The throughput manipulator should then be located at the bottleneck unit. This gives a short effective delay in the control loop. Effective delay determines the necessary back off from constraints to ensure feasible operation. Back off implies a reduction in throughput and an unrecoverable economic loss and should therefore be minimized. We obtain a rough estimate of the necessary back off based on controllability analysis. In some cases it is not desirable to locate the throughput manipulator at the bottleneck. To reduce the effective time delay in the control loop from the throughput manipulator to the bottleneck unit, dynamic degrees of freedom, like most inventories, can be used to reduce the effective time delay. In larger plants there may be several independent feeds, crossovers and splits that should all be utilized to obtain maximum throughput. The proposed coordinator MPC both identifies the bottlenecks and implements the optimal policy. A key idea in the coordinator MPC is to decompose the plantwide control problem by estimating the remaining capacity for each unit using models and constraint in the local MPC applications. The coordinator MPC is demonstrated by dynamic simulation and by implementation on a large-scale gas processing plant.
Industrial & Engineering Chemistry Research | 2009
Elvira Marie B. Aske; Sigurd Skogestad
Spe Production & Operations | 2014
Kalpesh Patel; Elvira Marie B. Aske; Morten Fredriksen
Archive | 2013
Jan Richard Sagli; Elvira Marie B. Aske; Kalpesh Patel