by Dionysios Xenos, Nina F.Thornhill
Important aims of the process industries are the increase in energy efficiency and reduction in CO2. Environmental sustainability and government legislation drive the industries to modify their current operations. Energy SmartOps is a European action which focuses on energy savings in the use of rotating electro-mechanical systems.
These systems involve compressors which have a variety of responsibilities. Figure 1 shows an industrial multi-stage centrifugal compressor. They are used to transfer gas from one plant location to another, to store gases to tanks and for other very common applications in the process industries.
The reason why Energy SmartOps is investigating the operation of these machines is that compressors consume a lot of energy. In particular, compressors are one of the major energy consumers in many intensive chemical processes such as air separation. The focus of the project is to study optimization of the overall system, i.e the system in which multiple compressors operate in networks integrated with chemical process units.
Some current operational strategies are really not very efficient. The users of these machines rely on their original specifications, i.e. characteristics and performances, and they operate the compressors accordingly. Of course, it is not true that the specifications stay the same, as the performances deteriorate over time. The results is to split the load evenly among the compressors with dissimilar efficiencies. A more efficient way to use the compressors would be to shift bigger proportion of the total load to the more efficient compressors.
Another important topic which is disregarded is the maintenance strategy of the compressors. The normal practice is to maintain a compressor when a maximum number of operating hours has been reached. This is something similar to the preventive maintenance in the conventional family cars.
Therefore, the Work Package 2 (WP2) of Energy SmartOps examines novel methods to deliver more efficient operation of compressors. The use of optimization tools help to solve the problems of the optimal distribution of load and maintenance.
The optimization of compressors leads to two different types of problems: (a) Real Time Optimization (RTO) related to optimal distribution of the load of compressors with a fixed configuration and (b) optimal scheduling and maintenance of compressors considering information for long time periods. The RTO scheme analyses raw data from the process to update models of the compressors to be used in the optimization to estimate the set points of the flows of the compressors which result in a more efficient operation compared to other conventional methods. The estimation of the best set points is called optimal distribution of load and it is also known as load sharing and multi-compressor capacity optimization. By contrast, optimal scheduling, which is given the forecast of the demand and other parameters, computes the optimal configuration of the compressors. Figure 2 shows the framework of these two interacting optimisation problems.
The RTO algorithm in Figure 2 solves the problem of the optimal load sharing. After data collection and conditioning, an optimization problem employs data-driven models to estimate the optimal load sharing in the form of set points of the manipulated variables (opening of the actuators inlet guide vanes) and the controlled variables (mass flow rate). The set points are given to the control system whose role is to apply and keep these points until the next run of RTO.
The scheduling optimization problem takes into account decisions which involve discrete events (for example switching on or switching off a compressor). These decisions are used in the RTO. When the online compressors are not able to meet the requirements of the requested demand (due to disturbances coming from the customers), the scheduling optimizer updates the models and estimates a new schedule of the compressors which can satisfy the demand. The interactions between RTO and scheduling is part of the ongoing research.
Xenos et al. (2014a) presented the optimization of a compressor station with multi-stage centrifugal air compressors operating in parallel. Figures 3b and 3c show the electricity consumption of each compressor in the optimization case and the comparison of the total electricity consumption between the case of optimization and the case of equal distribution strategy. The study of the optimal distribution of load was examined for ten different cases with different demands. The results showed that the optimal distribution of load reduces the total electricity consumption compared to the case with equal split strategy.
The state-of-the-art of the scheduling of compressor networks examines the optimal operation and maintenance of compressors without considering the gradual degradation of a compressor over time. Xenos et al. (2014b) studied the scheduling and maintenance of compressor networks taking into account the deterioration of the performance of a compressor over time. An illustrative example considering the overall air separation plant (i.e. air compressors, separation units, storage tanks) compared the condition based maintenance optimization and a preventive maintenance optimization strategy. The condition-based maintenance optimization achieved 11% reduction in the overall cost, especially in the start-up, shut-down and maintenance costs compared to the benchmark preventive maintenance strategy (Fig 4).
The work was funded by the Marie Curie Marie Curie FP7-ITN project "Energy savings from smart operation of electrical, process and mechanical equipment - ENERGY SMARTOPS", PITN-GA-2010-264940, in collaboration with the EPSRC Research Project EP/G059071/1 “Design Toolbox for Energy Efficiency in the Process Industry”.
Xenos D.P., Cicciotti M., Bouaswaig A.E.F., Thornhill N.F., Martinez-Botas R., 2014a, Modeling and optimization of industrial centrifugal compressor stations employing data-driven methods, Proceedings of ASME Turbo Expo 2014: Turbine Technical Conference and Exposition GT2014, June 16-20, 2014, Dussedorf, Germany.
Xenos D.P., Kopanos G.M., Cicciotti M., Pistikopoulos E.N., Thornhill N.F., 2014b, Operational optimization of compressors in parallel considering condition-based maintenance, Proceedings of the 24th European Symposium on Computer Aided Process Engineering - ESCAPE 24, June 15-18, 2014, Budapest, Hungary.