Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

Abstract This paper introduces a model predictive control (MPC) approach to construction of a controller for balancing power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in an effort to perform reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the l 1 -norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current implementation consisting of a distributed PI controller structure, both in terms of minimising the overall cost but also in terms of the ability to minimise deviation, which is the classical objective.