Model predictive control and the optimization of power plant load while considering lifetime consumption

Abstract

This paper describes a decision support system that indicates to a power plant operator the effect of daily operation on plant lifetime consumption and maintenance costs, and recommends a short-term operating strategy that optimizes plant economic performance efficiency. The recommended operating strategy is based on the optimization of an objective function that includes terms for revenues from energy sales, penalties, production costs and plant aging. Plant aging is based on models that are directly load dependent and incorporate a memory aspect, a feature that is missing from common lifetime modeling techniques. The optimization results in a tradeoff between maximization of immediate profits (i.e., earnings achieved by selling heat and power) and minimization of lifetime consumption. A model predictive control (MPC) and mixed logical dynamic (MLD) approach are used to solve the posed optimization problem and optimize this tradeoff and support the plant operator.