Open AccessModel order reduction of heavy duty gas turbine power plants with field test parameters
Author(s) -
Mohamed Iqbal Mohamed Mustafa,
Sarumathi Sankar,
Jothi Kovilvazhkai Rajappa,
Brindadevi Arunachalam
Publication year - 2019
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2703
Subject(s) - heavy duty , gas turbines , reduction (mathematics) , test (biology) , power (physics) , automotive engineering , reliability engineering , order (exchange) , field (mathematics) , turbine , environmental science , engineering , computer science , aerospace engineering , mechanical engineering , mathematics , business , physics , thermodynamics , paleontology , geometry , finance , pure mathematics , biology
Summary Frequent load fluctuation and set point variations are the major issues in grid connected heavy duty gas turbine power plants. It may affect the stability of the plant and may lead to inevitable shutdown. Dynamic stability analysis of higher order heavy duty gas turbine in real‐time environment would be tedious and expensive. Various model order reduction techniques namely clustering technique‐Pade approximation (CT‐PA), modified clustering technique‐Pade approximation (MCT‐PA), and Mihailov criterion‐Pade approximation (MC‐PA) are proposed for identifying the reduced order model of 18.2 MW industrial heavy duty gas turbine with field test parameter. The step response of gas turbine plant against the load disturbance and set point variations is obtained using the reduced order models and compared with that of higher order system. The time domain specifications and error criteria have witnessed that the MC‐PA‐based reduced order model retains the original characteristics and yields an improved transient and steady‐state responses. Therefore, MC‐PA‐based reduced order model is identified as an effective reduced order model for the higher order gas turbine plant. The proposed reduced order model would be useful for analysing the behaviour of latest derivative speedtronic controlled gas turbine plant.