Application of model predictive control to optimal dynamic dispatch of generation with emission limitations

Reducing emission from fossil-fueled electric power generating plants has received considerable attention in recent years in both regulated and deregulated power markets. Under regulated power systems, utilities solve the dynamic economic dispatch problem to determine the optimal scheduling of the committed unit's output at minimum fuel cost while satisfying a set of constraints. In this paper, we introduce the following problems where the emission effects are included in the mathematical model: (1) dynamic economic emission dispatch and (2) emission constrained dynamic economic dispatch. Under deregulated markets, the generation company can determine the optimal amounts of energy to be sold in the market by running profit-based dynamic economic dispatch problem to maximize its own profit. To take into account the emission limitations we introduced two problems: (1) profit-based dynamic economic emission dispatch problem and (2) profit-based emission constrained dynamic economic dispatch problem. In this paper we applied the model predictive control (MPC) approach proposed recently to the dynamic dispatch problems in both regulated and deregulated systems. The convergence and robustness of the MPC algorithms are demonstrated through the application of MPC to these problems with a six-unit system.

► In this paper we introduced optimal dynamics dispatch problems in both regulated and deregulated power markets. ► The emission effects of gaseous pollutants are included in the mathematical model of the problems. ► We applied a model predictive control (MPC) approach for these problems. ► The convergence and robustness of the MPC algorithms are demonstrated through the application of MPC to these problems with a six-unit system.