Hunger Games Search Algorithm for Model Order Reduction of Gas Turbine Power Plants

The installation of power plants based on various types of energy resources increases in parallel to the rise in energy demand. Following a clean and environmentally friendly policy is as important as meeting this energy need. The effect of these policies causes significant increases in the use of renewable energy sources in modern power systems. However, these energy sources have a negative effect on the power system reliability due to their intermittence nature. In recent years, as a low-polluting fossil-based energy source, natural gas has attracted increasing attention. Consequently, the role of the gas turbine power plants increases in providing reliable power supply. Like many other similar systems, gas turbine plants have a complicated structure and thus are modeled with higher-order transfer functions. In this regard, hunger games search (HGS) algorithm is proposed in this study to extract the second-order reduced-order model of gas turbine power plants that are represented with a fourth-order model in the original. The aim of this study is to overcome the computation burden in system model-based analyses by maintaining the significant characteristics of the higher-order model. The effectiveness of the proposed method is demonstrated by comparing it with Routh stability and particle swarm optimization-based methods.