A dynamic optimal control system for complex compressed air networks
type: CreativeWork
description: Mines use large compressed air networks to supply shafts and processing plants with compressed air. These networks can be complex where multiple compressors are located at different locations. To add to the complexity of the network, each end user of compressed air is a separate business entity - each following its own schedule and usage requirements. Some mines have general guidelines controlling these schedules. Most mines still use static compressor control on compressed air networks. Advanced control strategies are based on simulation results of typical usage patterns. These static controls only work when all the end users use compressed air according to the data on which the control strategy was devised. If one end user deviates from this plan, the strategy becomes non-optimal. This happens almost on a daily basis. Previous work into dynamic control of compressed air networks was only based on basic networks where compressors were stationed close together. As soon as compressors are stationed further apart, there is a noticeable pressure drop. Due to this effect, the controller could select compressors too far away from the demand and the system would not provide a viable solution. The Dynamic Compressor Controller (DCC) discussed in this thesis solves this problem. The DCC accomplishes this by calculating multiple compressed air set points - one for each individual compressor. These set points take the location and demand of the compressed air network into account. The operating and trimming compressor are selected dynamically. In order to reduce cycling of compressors, the future airflow is predicted to ensure sufficient compressed air supply. The above-mentioned factors are combined to simulate the compressed air network state and propose an optimal solution for controlling the network. The solution prescribes optimal operating compressor schedules as well as pressure set points for all compressors. The prescribed pressure set point is the minimum supply pre…
abstract: Mines use large compressed air networks to supply shafts and processing plants with compressed air. These networks can be complex where multiple compressors are located at different locations. To add to the complexity of the network, each end user of compressed air is a separate business entity - each following its own schedule and usage requirements. Some mines have general guidelines controlling these schedules. Most mines still use static compressor control on compressed air networks. Advanced control strategies are based on simulation results of typical usage patterns. These static controls only work when all the end users use compressed air according to the data on which the control strategy was devised. If one end user deviates from this plan, the strategy becomes non-optimal. This happens almost on a daily basis. Previous work into dynamic control of compressed air networks was only based on basic networks where compressors were stationed close together. As soon as compressors are stationed further apart, there is a noticeable pressure drop. Due to this effect, the controller could select compressors too far away from the demand and the system would not provide a viable solution. The Dynamic Compressor Controller (DCC) discussed in this thesis solves this problem. The DCC accomplishes this by calculating multiple compressed air set points - one for each individual compressor. These set points take the location and demand of the compressed air network into account. The operating and trimming compressor are selected dynamically. In order to reduce cycling of compressors, the future airflow is predicted to ensure sufficient compressed air supply. The above-mentioned factors are combined to simulate the compressed air network state and propose an optimal solution for controlling the network. The solution prescribes optimal operating compressor schedules as well as pressure set points for all compressors. The prescribed pressure set point is the minimum supply pre…
author: Van Heerden, Schalk Willem
language: en
keywords: Dynamic compressor control, Dynamic compressor system, DSM, Energy management, Mine compressor, Compressed air ring, Compressed air supply, Compressor control
date published: 2016
date modified: 2026-07-24T03:33:37Z
provider: North-West University (South Africa)
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: North-West University (South Africa) , Potchefstroom Campus

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10394/21202