Efficient operation of an industrial combined heat and power plant under demand uncertainty

The European process industry strives to remain competitive in the global market. This is challenging considering the higher prices of feedstock and energy compared to many other parts of the world and the political and societal expectations on increasing the sustainability of their processes. Therefore, it is vital for the European industry to increase the resource efficiency of their processes. This thesis addresses this topic from two angles. First, a method to calculate performance baselines for the resource efficiency of the operation of a process from recorded data is proposed and the performance of the method is compared to an analysis based on a detailed rigorous model using real production data of INEOS in Köln. The baseline serves to indicate the resource efficiency to the operators to stimulate them to improve their way to run the processes. Secondly, the improvement of the efficiency of an on-site power plant is addressed. The operation of on-site power plants in the chemical industry is typically determined by the steam demand of the production plants. The steam demand of the plants on a site is affected by several factors and deviates from the most resource efficient or average operation. Thus, the steam demand is uncertain which can result in an inefficient operation of the power plant, causing a surplus or deficiency of the steam that is required to balance the steam network. Hedging against steam demand uncertainty can result in significant savings and helps to stabilize the balance of the steam network. In this work, a comprehensive approach to the optimization of the operational schedule of power plants to cope with the demand uncertainty is proposed and its application is demonstrated using simulations of the on-site power plant of INEOS in Köln.