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RIS citation export for MO3AO06: Energy Consumption Optimisation by Using Advanced Control Algorithms

TY  - CONF
AU  - Ghawash, F.
AU  - Blanco Viñuela, E.
AU  - Schofield, B.
ED  - Schaa, Volker RW
ED  - Götz, Andy
ED  - Venter, Johan
ED  - White, Karen
ED  - Robichon, Marie
ED  - Rowland, Vivienne
TI  - Energy Consumption Optimisation by Using Advanced Control Algorithms
J2  - Proc. of ICALEPCS2023, Cape Town, South Africa, 09-13 October 2023
CY  - Cape Town, South Africa
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 19
LA  - english
AB  - Large industries operate energy-intensive equipment and energy efficiency is an important objective when trying to optimize the final energy consumption. CERN utilizes a large amount of electrical energy to run its accelerators, detectors and test facilities, with a total yearly consumption of 1.3 TWh and peaks of about 200 MW. Final energy consumption reduction can be achieved by dedicated technical solutions and advanced automation technologies, especially those based on optimization algorithms, have revealed a crucial role not only in keeping the processes within required safety and operational conditions but also in incorporating financial factors. MBPC (Model-Based Predictive Control) is a feedback control algorithm which can naturally integrate the capability of achieving reduced energy consumption when including economic factors in the optimization formulation. This paper reports on the experience gathered when applying non-linear MBPC to some of the contributors to the electricity bill at CERN: the cooling and ventilation plants (i.e. cooling towers, chillers, and air handling units). Simulation results with cooling towers showed significant performance improvements and energy savings close to 20\% over conventional heuristic solutions. The control problem formulation, the control strategy validation using a digital twin and the initial results in a real industrial plant are reported together with the experience gained implementing the algorithm in industrial controllers. 
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 145
EP  - 152
KW  - controls
KW  - operation
KW  - PLC
KW  - MMI
KW  - simulation
DA  - 2024/02
PY  - 2024
SN  - 2226-0358
SN  - 978-3-95450-238-7
DO  - doi:10.18429/JACoW-ICALEPCS2023-MO3AO06
UR  - https://jacow.org/icalepcs2023/papers/mo3ao06.pdf
ER  -