TY  - JOUR
AU  - Schäfer, Pascal
AU  - Schweidtmann, Artur M.
AU  - Lenz, Philipp H. A.
AU  - Markgraf, Hannah M. C.
AU  - Mitsos, Alexander
TI  - Wavelet-based grid-adaptation for nonlinear scheduling subject to time-variable electricity prices
JO  - Computers & chemical engineering
VL  - 132
SN  - 0098-1354
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2020-02285
SP  - 106598 -
PY  - 2020
AB  - Using nonlinear process models in discrete-time scheduling typically prohibits long planning horizons with fine temporal discretizations. Therefore, we propose an adaptive grid algorithm tailored for scheduling subject to time-variable electricity prices. The scheduling problem is formulated in a reduced space. In the algorithm, the number of degrees of freedom is reduced by linearly mapping one degree of freedom to multiple intervals with similar electricity prices. The mapping is iteratively refined using a wavelet-based analysis of the previous solution. We apply the algorithm to the scheduling of a compressed air energy storage. We model the efficiency characteristics of the turbo machinery using artificial neural networks. Using our in-house global solver MAiNGO, the algorithm identifies a feasible near-optimal solution with  < 1% deviation in the objective value within  < 5% of the computational time compared to a solution considering the full dimensionality.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000498396100021
DO  - DOI:10.1016/j.compchemeng.2019.106598
UR  - https://juser.fz-juelich.de/record/877550
ER  -