@article{gueddar2011novel,
title={Novel model reduction techniques for refinery-wide energy optimisation},
author={Taoufiq Gueddar and Vivek Dua},
journal={Applied Energy},
volume={89},
number={1},
pages={117--126},
year={2012},
publisher={Elsevier}
}
1 selection of the crudes
2 rigorous simulation
3 Data generation and scaling
4 NLP network training
minimize the SSE (sum of squared errors)
5 MINLP node reduction: minimize the number of nodes, while keeping the training error under the chosen tolerable error for step 4.
6 MINLP interconnection reduction: minimize the sum of the interconnection binary variables from the inputs to the hidden layer nodes and from the hidden layer to the outputs.
7 NLP training with the optimized structure
8 steps 6 and 7 carried out in a loop to choose the best run.
Fig. 2. LP techniques used in the industry to model the CDU.
Clear illustration.
@article{robertson2011multi,
title={A multi-level simulation approach for the crude oil loading/unloading scheduling problem},
author={Robertson, G. and Palazoglu, A. and Romagnoli, JA},
journal={Computers and Chemical Engineering},
volume={35},
number={5},
pages={817--827},
year={2011},
publisher={Elsevier}
}
