Optimization Methods for Integrating Energy and Production Systems : Hardware development and applications to fuel cell materials

The key measure to mitigate climate change is the reduction of greenhouse gas emissions. Hereby, energy-intensive industry plays a key role due to its substantial greenhouse gas emissions. A substantial share of these greenhouse gas emissions is caused by energy supply. Thus, energy supply needs to be more efficient in industry. In large industrial sites, on-site energy systems often supply production systems. Both systems thereby optimize their operation with respect to an objective such as operational cost or revenue. This thesis provides optimization methods for these large industrial sites. The optimization methods reflect two relationships between both systems: Both systems can either follow the same objective or system-specific objectives. The same objective exists, e.g., if both systems belong to one company. System-specific objectives exist, e.g., if both systems belong to different companies. For the case that both systems follow the same objective, a method is presented for the integrated synthesis of both systems. For the same case, a method is presented for integrated scheduling to provide control reserve. For the case that energy and production systems have system-specific objectives, two cases are distinguished: incomplete and complete information exchange. For incomplete information exchange, an optimization method is introduced for the coordination between a single energy and a single production system. This optimization method is then extended to multiple energy and multiple production systems. For complete information exchange between the systems, a bilevel problem is formulated. For solving the bilevel problem, an existing solution algorithm is adapted. All methods presented in this thesis are applied to case studies, and advantages and disadvantages are examined. The case studies show that no method provides the optimal solution for the production system in all identified relationships between the systems. Thus, depending on the case at hand, the respective optimization method has to be applied. Overall, this thesis presents optimization methods for all identified relationships between energy and production systems. Thus, this thesis enables the selection of a suitable optimization method for all kind of production systems with decentralized energy supply.