A predictive dynamic model of a smart cogeneration plant fuelled with fast pyrolysis bio-oil

Small-scale biomass-based cogeneration has the potential to contribute significantly to a clean, flexible, secure, and cost-efficient energy system. It provides flexibility to future energy systems by balancing variable intermittent renewable energy sources. A smart control unit is needed to exploit its flexibility. A dynamic system model is required to enable smart control of a cogeneration unit and to determine its optimal working points. This study aims to develop, parameterise and tune a dynamic model of a cogeneration plant fuelled with fast-pyrolysis bio-oil. The system is a hybrid diesel generator/flue gas boiler plant for electricity generation and water/space heating. The plant has two unique features: (i) pyrolysis bio-oil is the new fuel for both engine and boiler and influences their operation and emissions, (ii) power and heat generation are partially decoupled and hence nonlinearly correlated. The paper presents the integration of the components ' dynamic models into a system model. The model is parameterised and partially validated using measurements from a turbocharged four-cylinder diesel engine and a swirl burner, both running on fast-pyrolysis bio-oil. Preliminary controls are designed and evaluated. The applicability and usefulness of the model for cogeneration system analysis and control design evaluation are also illustrated. Results show that the feasible operation region area of the hybrid engine/boiler system is 100% larger than that of the CHP engine. The hybrid plant can achieve energy efficiencies above 85% in response to fluctuating load demand of a hospital.