Deep Learning Algorithms to Predict Output Electrical Power of an Industrial Steam Turbine

Steam Turbine Steam System

Constrained Model Predictive Control of Low-power Industrial Gas Turbine

Nowadays, extensive research has been conducted for gas turbine engines control due to growing importance of gas turbine engines for different industries and the need to design a suitable control system for a gas turbine as the heart of the industry. In order to design gas turbine control system, various control variables can be used, but in the meantime, fuel flow inserting into combustion cha...

Integration of remote sensing and meteorological data to predict flooding time using deep learning algorithm

Accurate flood forecasting is a vital need to reduce its risks. Due to the complicated structure of flood and river flow, it is somehow difficult to solve this problem. Artificial neural networks, such as frequent neural networks, offer good performance in time series data. In recent years, the use of Long Short Term Memory networks hase attracted much attention due to the faults of frequent ne...

Steam Turbine Configuration

Most electric power is produced by steam turbines. This is because the steam cycle is well suited to the conversion of heat to work and steam turbines can be built in a wide range of capacities up to about 1500 MW. Steam turbines are basically very simple having fixed blades to accelerate the steam and moving blades to absorb the resulting kinetic energy. The moving blades are mounted on a rota...

Steam turbine model

In order to characterize the transient dynamics of steam turbines subsections, in this paper, nonlinear mathematical models are first developed based on the energy balance, thermodynamic principles and semi-empirical equations. Then, the related parameters of developed models are either determined by empirical relations or they are adjusted by applying genetic algorithms (GA) based on experimen...