Adaptive power plant start-up scheduling: simulation test results

Abstract

Power plant start-up scheduling is aimed at minimizing the start-up time while limiting maximum turbine-rotor stresses. A shorter start-up time not only reduces fuel and electricity consumption during the start-up process, but also increases its capability of adapting to changes in electricity demand. This scheduling problem is, however, highly nonlinear with a number of local optima within a wide search space. In our previous research, we proved that the optimal schedule stays on the edge of the feasible space, and provided an adaptive enforcement operation based on a theoretical setting equation. The adaptive enforcement operation used with GA is applied to compel the search along the edge of the feasible space, so as to increase the search efficiency. We give a brief description of the theoretical proof and present simulation test results with a range of hard-to-search stress limit sets to verify the search efficiency of the theoretically-proved search model.