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The increased impact from fluctuating energy sources like wind and photovoltaics significantly affects the operational regime of conventional power plants. In the near future, even former base load power plants such as the large-scale lignite plants in Germany will need to start and shut down to balance the electricity system. As frequent starts were not in the focus of optimisation in the past, an extensive potential can be expected to reduce start-up costs and environmental impacts. In order to investigate such optimisation potentials, a comprehensive dynamic simulation model has been developed including process components such as boiler and water-steam cycle but also the power plants control system along with start-up sequence control. After successfully reproducing a reference start of the power plant, the model has been used to identify restrictions for faster start-ups, less fuel consumption and less emission while keeping the thermal and mechanical stress, caused by higher ramp rates, within acceptable bounds. [ABSTRACT FROM AUTHOR]

This paper describes a method to decrease the additional measurement effort during a model calibration/verification to create reliable models for plant optimisation. The method is based on the deterministic processes creating the dry weather inflow to municipal treatment plants, which can be described by a simple influent composition model. This method was applied to two wastewater treatment plants of Lippeverband and the usability is indicated by the good correlation between routine online effluent measurements and simulation results. This paper presents one of these applications, the case study WWTP Dorsten. The resulting model is used to analyse the current plant performance, to analyse bottlenecks and to develop future improvements of operation and control of this plant. A selection of control options is demonstrated. [ABSTRACT FROM AUTHOR]