Abstract The traditional approach to modelling complex power plants often leads to cumbersome, expensive and inefficient models. This paper is concerned with the development of a systematic, hierarchical and modular modelling procedure and advanced control system design for large power plants. The system component defined by a generic nonlinear dynamic structure is arranged in a hierarchical structure with the appropriate communication interface. The nonlinear dynamic model is then employed to produce steady-state models and linear models, which can be used to investigate the transient characteristics, stability behaviour and control requirements. Advanced control methods are then proposed to optimally implement a desired set point change whilst satisfying operational variable constraints. In common with many process control applications, it is not possible to move from one power plant operating condition to another instantaneously. Previous ad-hoc methods to automate the transition usually involve ramping the set point over some pre-determined time horizon and implicitly satisfying the operational and safety constraints. The design of optimal methods for the implementation of future set points trajectories is addressed here using the techniques of Model Based Predictive Control (MBPC) for large-scale systems. A generic unit of Combined Heat and Power (CHP) unit is employed as an example.
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