Optimisation of the Operation of an Industrial Power Plant under Steam Demand Uncertainty

The operation of on-site power plants in the chemical industry is typically determined by steam demand production plants. This uncertain due to deviations from plan and fluctuations uncertainty can result an inefficient plant a surplus or deficiency that needed balance network. In this contribution, it proposed use two-stage stochastic programming on moving horizon cope with uncertainty. each iteration scheme, model parameters are updated according new information acquired optimisation re-executed. Hedging against results reduction fuel consumption more economic generation electric power, which significant savings operating cost plant. Moreover, unplanned load reductions lack be avoided. application approach demonstrated for INEOS Köln, reported exemplary simulations.