adaptive dynamic models for maintenance-on_demand and process optimization of combined heat and...

ADAPTIVE DYNAMIC MODELS FOR MAINTENANCE-ON_DEMAND AND PROCESS OPTIMIZATION OF COMBINED

HEAT AND POWER PLANTS (ADMADE)

Prof Erik DahlquistMalardalen University

erik.dahlquist@mdh.se

Objectives

• The aim of this application is to build a foundation of mathematical tools for application in the future energy sector, including renewable energy as well as intelligent energy.

• Secondly we need more information on moisture and heating value of different fuels, to optimize the performance.

• Measured process data will be analysed and utilised for process optimization, and not only be collected and stored as is often the case today.

Project

• In the project we will develop the mathematical modeling foundation for doing these type of diagnostics and optimizations for later implementation in different power plant and process industries generally.

• - Physical models will be combined with statistical models in a systematic way to make it possible to adapt the models as conditions change, and to follow effect of new fuels.

• - A hierarchical structure will be introduced for • 1) measurement of fuel properties using NIR and RF together with statistical

models like PLS, • 2) process diagnostics comparing simulations to measurements in the

process combined with Bayesian Nets and • 3) production planning including when maintenance has to be done. • 4) on-line control and optimization using model based, multivariable control.

This includes both the production and district heating system.

Partners

• Mälarenergi AB• Eskilstuna Energy and Environment• ENA Energy• Vattenfall