Demand-Side Management for Industrial Production Processes

In the context of demand-side management the industry as a large consumer of energy is supposed to contribute to the stability of the power gird by adjusting their consumption according to requirements of the grid. To compensate the costs of adjustments for the companies, financial rewards for the flexibilization are provided. The decision of a company to participate actively in the stabilization of the grid is usually based on economic considerations. Thereby, the company has to balance rewards from participating in demand-side management with their actual production goals and quality requirements. To strictly ensure the compliance of the system service with the production goals, the company needs to be able to predict their production amounts under different production speeds as well as the resulting power consumptions in the near future. This requires substantial models of all the different machines involved in the production process. Typically, the dynamical behavior of the machines can be described by ordinary differential equations or in case of spatially extensive machines by partial differential equations. With the help of these models, the financial cost for power consumption, the gains by selling their product and the rewards from the demand-side management of the company can be optimized using a model predictive control algorithm. In this approach the requirements from production can be integrated as constraints in a rather natural form. The application of a model predictive control thereby is capable of reacting to demands from the grid in realtime.

• Development of models for different machines in the production process,which  are  able  to  describe  the  dynamical  behavior  as  well  as  the corresponding output of products and the power consumption.
• Design of economically optimal control problems to maximize benefits from demand-side management, while considering the constraints from production.
• Implementation of the derived control schemes and validation in simulation studies.
• Industrial application an beverage production process.

Demand-side management
System service
Economical optimization
Model predictive control
Beverage production

Prof. Naim Bajcinca
Gottlieb-Daimler-Str. 42
67663, Kaiserslautern
Phone: +49 (0)631/205-3230
Fax: +49 (0)631/205-4201
naim.bajcinca@mv.uni-kl.de

Bundesministerium für Wirtschaft und Energie

Jul., 2019 – Jun., 2022

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