Nonlinear model predictive control for a heavy-duty gas turbine power plant

A nonlinear model predictive control (NMPC) scheme is applied to a 166 MW a heavy-duty gas turbine power plant for frequency and temperature control. This scheme is compared to a classical PID/logic based control scheme and is found to provide superior output responses with smaller settling times and less oscillatory behavior in response to disturbances in electric loads. The NMPC solution is obtained by applying orthogonal collocation on finite elements to convert the dynamic problem to a set of algebraic equations, which can be solved as a nonlinear programming (NLP) problem. This NLP problem is then solved using analytical derivatives and an interior-point algorithm to ensure fast solution times. The computation time at each control step was sufficiently faster than the sampling rate (1 sec), allowing real-time implementation of NMPC for the gas turbine power plant.

I. Introduction

Recently, natural gas-fired turbines have found widespread use because of their higher efficiencies, lower capital costs, shorter installation times, abundance of natural gas supplies, lower greenhouse gas emissions compared to other energy sources, and fast start-up capability, which enables them to be used as peaking units that respond to peak demands [1]. Due to their special characteristics, natural gas-fired turbines are installed in numerous places in the world and have become an important source for power generation.