Publication

Economic model predictive control for optimal operation of combined heat and power systems

Conference Article

Conference

IFAC Conference on Manufacturing Modeling, Management and Control (MIM)

Edition

2019

File

Download the digital copy of the doc pdf document

Authors

Abstract

The use of decentralized Combined Heat and Power (CHP) plants is increasing since the high levels of efficiency they can achieve. Hence, to determine the optimal operation of these systems in the changing energy market, the time-varying price profiles for both electricity as well as the required resources and the energy-market constraints should be considered into the design of the control strategies. To solve these issues and maximize the profit during the operation of the CHP plant, this paper proposes an optimization-based controller, which will be designed according to the Economic Model Predictive Control (EMPC) approach. The proposed controller is designed considering a non-constant time step to get a high sampling frequency for the near instants and a lower resolution for the far instants. Besides, a soft constraint to met the market constraints for the sale of electric power is proposed. The proposed controller is developed based on a real CHP plant installed in the ETA research factory in Darmstadt, Germany. Simulation results show that lower computational time can be achieved if a non-constant step time is implemented while the market constraints are satisfied.

Categories

predictive control.

Author keywords

Combined heat and power systems, Profit maximization, Economic model predictive control, Mixed Integer Linear Programming

Scientific reference

J.L. Diaz, T. Weber, N. Panten, C. Ocampo-Martínez and E. Abele. Economic model predictive control for optimal operation of combined heat and power systems, 2019 IFAC Conference on Manufacturing Modeling, Management and Control , 2019, Berlin, to appear.