Abstracts IFAC 2017 - Adaptive Pricing for Optimal Resource Allocation in Industrial Production Sites

Improved energy and resource efficiency by better coordination of production in the process industries

Published on: 
Tuesday, 22 August, 2017

S. Wenzel, R. Paulen, B. Beisheim, S. Krämer, S. Engell, Adaptive Pricing for Optimal Resource Allocation in Industrial Production Sites

Keywords: Control of distributed systems, Industrial applications of process control, Control of large-scale systems

Abstract: In large integrated production sites, an optimal allocation of the shared resources among different possibly competing production plants is key to a resource and energy efficient operation of the overall site. Typically, a large integrated production site can be regarded as a physically coupled system of systems (SoS), since it comprises many different physically linked production plants with a certain degree of autonomy in respect to the individual operating conditions where the plants tend to pursue their own economic goals and interests. In order to improve the overall operation of the production site, a centralized optimization for the shared resource allocation within the site is favored. However, a centralized solution cannot always be realized due to various technical or managerial reasons. One of the reasons is the limited amount of information about the individual subsystems that a central site management can access, because the subsystems want to preserve a high level of confidentiality. In this contribution, we present the application of price-based coordination subgradient-based price updates and the Alternating Direction Method of Multipliers, ADMM) to the case study of the integrated petrochemical production site of INEOS in Köln. We discuss the requirements of the price-based coordination for industrial applicability in the case of limited sharing of information. In a simulation study, we show how the central site management uses price incentives to steer the individual productions plants towards a site-optimal operation and thus is able to react to changing conditions such as capacity changes.