A model-based advanced control system to cope with energy fluctuations in industrial wood drying

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Abstract

The use of renewable energy and heat recovery sources (RE&R) in wood drying would help to reduce the environmental footprint of the process and dependence on volatile costs energy sources. The challenge is to adapt drying schedules to fluctuations in energy quantity and temperature. To tackle this challenge, a mechanistic model generates optimized drying conditions. A series of harmonic functions based drying condition generation module has been embedded in the computational model to generate conditions tailored to different RE&R scenarios. The simulated annealing algorithm optimizes energy renewable use. This approach is applied to a kiln dryer equipped with solar PV/T panels for drying thick beech boards. The results suggest original drying conditions that improve the final product quality and double the amount of renewable thermal energy used in the process, but often at the cost of longer drying times and higher operating costs, at least compared to cheap fossil energies.

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