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Thesis
Home   /   Thesis   /   Optimal Control of Hybrid Solar Heat and Power Systems based on MPC and AI methods

Optimal Control of Hybrid Solar Heat and Power Systems based on MPC and AI methods

Engineering sciences Mathematics - Numerical analysis - Simulation Thermal energy, combustion, flows

Abstract

Industrial processes use heat in the 50-1500°C temperature range, and heat accounts for around 70% of industrial energy consumption. Heat consumption in industry is generally classified into three temperature ranges: low (400°C), which can be addressed by different solar collector technologies. Concentrating solar technologies are needed to produce solar heat at T>150°C. The central issue of integrating solar heat into industrial processes is addressed in the SHIP4D project (PEPR SPLEEN programme).In this thesis, the work will focus on the high-level optimal control of hybrid solar systems for producing heat and electricity for industrial processes. The control tools will be developed in PEGASE, and applied to a simulator of the LACTOSOL power plant supplied by NEWHEAT. The thesis work will also serve as a basis for the European INDHEAP project (Optimal Solar Systems for Industrial Heat and Power), coordinated by the CEA, and starting in January 2024.

Laboratory

Département Thermique Conversion et Hydrogène (LITEN)
Service Système Energétique Territoire et Industrie
Laboratoire des technologie thermodynamqiues et solaires
INSA Lyon
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