Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant

摘要: Abstract This paper presents a model predictive control (MPC) strategy for efficient energy production in BioGrate boiler. In addition to compensating the main disturbances caused by variations fuel quality such as moisture content, and feed, this models water evaporation, controls bed height of grate. Usually, combustion power furnace have been estimated utilizing oxygen consumption. There is however need more accurate prediction power, which greatly affected content. It shown that evaporation thermal decomposition dry can be soft-sensor consumption calculations respectively. As result, primary air adjusted produce necessary output boiler accurately predicted. enables stabilization plant operations. To verify model, experiments were performed at BioPower 5 CHP plant, utilizes technology enable use wet biomass fuels with content high 65%. Then MPC was compared currently used strategy. Finally, results are presented, analyzed, discussed.