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Due to the increasing integration of renewable energy sources in the existing power grid the conventional power plants have to set their focus more on flexibility and grid stabilization than supplying the base load. Since this task was not foreseeable when designing the currently existing power plants, they will have to suffer completely different load scenarios than expected. Dynamic modelling of complete steam cycles is a promising way to study the power plant operation of various future scenarios. To adapt the model to real power plant behaviour, especially with a focus on control events, the implementation of effects due to steam blown into the gasside part of the boiler in order to detach soot from the heating surfaces (soot blowing) seem to bring great efforts concerning model validity. Furthermore special control optimizations can be done, for example on spray injection at soot blowing events. In this study temperature measurement data is used in combination with a highly detailed boiler model of a 550 MW hard coal fired power plant to build a mathematical model of soot blowing influence on the different heat exchangers.

The increasing share of fluctuating renewable energy sources leads to changing requirements for conventional power plants. The changing characteristics of the residual load requires the conventional fleet to operate with higher load gradients, lower minimum load at improved efficiency levels as well as faster start-ups and provision of ancillary services. Despite the requirements from the electricity market, the value of improving those flexibility parameters is hard to evaluate for power plant operators. In order to quantify the additional benefit that can be achieved by improving flexibility parameters on a certain power plant in a changing market environment, an adjustable load dispatch model has developed for that purpose. Using past electricity market data, the model is validated for typical coal and a typical gas fired power plants by reproducing their operational schedule. In the next step, the model is used to apply parameter changes to the power plants specifications and economic effects are demonstrated. General statements are derived on which flexibility parameter needs to be improved on each power plant type. Furthermore, specific economic evaluations are shown for the reference power plants in order to present the ability of the developed tool to support investment decisions for modernization projects of existing power plants.

In many parts of the world, the impact of renewable energy, especially from intermittent sources as wind and solar is continuously increasing. In Germany, the share of renewable energy in electricity production is believed to increase from 32.5% in 2015 to 50% in 2030. In order to operate an electrical system and control the mains frequency, the power supply must match the consumption at any time. Ancillary services like primary and secondary control are used to balance the system on a time-scale of several seconds up to 15 minutes. Those control reserves are usually provided by thermal power plants. Particularly in times of high shares of fluctuating renewable feed-in, thermal power plants are turned off or operated at minimum load to avoid electricity production at low electricity prices. However, an amount of about 3000 MW of fast responding primary control need to be provided in the European network of transmission system operators for electricity grid to maintain stable operation even in case of two simultaneous large unit outages. This requirement leads to situations, where thermal power plants are operated in minimum load below their marginal cost to provide control reserves even if there is a surplus of energy in the grid. Operation in low load while at the same time providing control reserves leads to new challenges. As the relation between energy production and the thermal storage capacities provided by the metal and fluid mass in the boiler is decreasing with the load, the ability of responding to control demands is naturally slowed down. Dynamic simulation of the thermodynamic power plant process turned out to be an efficient method to investigate such operational modes. Using comprehensive process models coupled with a control system model, equipment adaptions or control system updates can be evaluated in order to provide faster responses. By increasing the specific amount of ancillary services per unit, the number of units necessary to provide the total amount of primary and secondary control could be reduced in situations with energy surplus.