Modeling knowledge for user-centric energy cost analysis of industrial automation systems

The gap between conventional electrical energy generation capabilities and electrical energy demand steadily increases. In consequence, energy costs raise and become an increasingly decisive factor in economy and society. A challenge that still is remaining is electrical energy analysis of complex systems during their operation time. During operation time these system reside in unique situations and are operated according to individual requirements of their users. Hence, in addition to complexity of the systems individuality and dynamic variability of their surroundings during operation time complicate identification of goal-oriented optimization measures. In this paper a model-based user-centric approach for automated energy analysis is proposed. It enables the users to reduce their energy costs by automatically generating optimization proposals that meet their individual situation and requirements. First prototypical implementations have shown promising results and are used for illustration purposes.