Optimization methods for minimum energy usage at process plantscale has been a topic of R&D for the last ten years. Although the techniques are not always very well understood or have not been sufficiently disseminated, there is a big interest and need in site scale energy usage optimisation in industry : indeed there are enough arguments that show that the biggest benefits can only be achieved if the problems are tackled at that large scale. This project is a step in a long term R&D aiming to respond to this need. The objective is to develop a methodology to optimise site-scale energy usage in the process industry. Process plant and utility distribution network (heat, power, cooling) combined models will be linked with different optimisation methods to solve real industrial problems.
Mathematical models for process plants and energy supply systems will be built, assembled, and tuned on reconciled measurement data. New targeting techniques will be developed for energy network operation based on total site target concept.
Optimisation criteria will be stated to account for uncertainty at the operational level and in energy management. Several optimisation methods will be used and compared: mixed integer non linear programming, sequential quadratic programming, genetic algorithms. Existing software will be used as much as possible, prototype software for optimisation of site-scale energy usage will be developed. Implementation of a development environment will be started for integrated modelling, for stochastic optimisation, and for genetic algorithms based optimisation. All these aspects and techniques will be implemented in a new unified methodology. Industrial case studies will be conducted to validate the new methodology.
Funding SchemeCSC - Cost-sharing contracts
SW7 2BY London
M60 1QD Manchester