Martin Nygaard Kragelund

On Propagating Requirements and Selecting Fuels for a Benson Boiler

In this paper, the problem of optimal choice of sensors and actuators is addressed. Given a functional encapsulating information of the desired performance and production economy the objective is to choose a control instrumentation from a given set to comply with its minimum. The objective of the work is twofold: reformulation of the business objectives into mathematical terms and providing solution to the given optimization. Commonly, there exist overall business objectives which dictate how a plant should be instrumented and operated either directly or indirectly. The work shows how to propagate a global objective to local subsystems. Particular focus is on a boiler in a power plant operated by DONG Energy - a danish energy supplier. The business objectives have been propagated to the actuator level to allow for selection of an actuator configuration.

Optimal production planning of a power plant

This paper addresses the problem of planning the usage of actuators optimally in an economic perspective. The objective is to maximize the profit of operating a given plant during 24 hours of operation. Models of two business objectives are formulated in terms of system states and the monetary value of these objectives is established. Based on these and the cost of using the different actuators a profit function has been formulated. The optimization of the profit is formulated as an optimal control problem where the constraints include the dynamics of the plant as well as a requirement to reference tracking. A power plant is considered in this paper, where the fuel system consists of three different fuels; coal, gas, and oil.

Performability measure for a power plant

This paper considers the problem of economical optimization of the power production in a power plant capable of utilizing three different fuel systems. The considered fuel systems are coal, gas, and oil; each has certain advantages and disadvantages e.g. gas is easier to control than coal but it is more expensive. A profit function is stated and an analysis of the optimal fuel configuration is performed based on the Hamiltonian from the maximum principle. The analysis leads to the introduction of a performability measure, which, when the value is above a confidence threshold, indicates that a change of fuel systemusage is beneficial. That is, the performability measure determines when an increase of performance is possible

Optimal input strategy for plug and play process control systems

This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined part of the plant where the commodities (outputs) are produced. A profit function with a certain regular structure is defined for such a plant. Then the profit is maximized subject to tracking of a given reference production. The work shows whether a new input ought to be included in the system to improve the performance of the plant. The results are applied to a coal fired power plant where an additional new fuel system, gas, becomes available.

A Robust Controller Structure for Pico-Satellite Applications

Abstract This paper describes the development of a robust controller structure for use in pico-satellite missions. The structure relies on unknown disturbance estimation and use of robust control theory to implement a system that is robust to both unmodeled disturbances and parameter uncertainties. As one possible application, a satellite mission with the purpose of monitoring shipping routes for oil spills has been considered. However, it is the aim of the control structure to be widely applicable and adaptable for a wide variety of pico-satellite missions. The robust control structure has been evaluated using Monte Carlo simulations.