AUTOMATIC CONTROL OF STEAM FLOW IN ELECTRICITY GENERATION

Abstract

The efficient operation of thermal power plants hinges on precise control of steam flow, a critical parameter that impacts performance, safety, and economic efficiency. Steam, as the primary working fluid, drives turbines to convert thermal energy into electrical power. This article examines the principles, technologies, and challenges of automatic steam flow control in electricity generation. It highlights the role of feedback control systems, such as proportional-integral-derivative (PID) controllers, and advanced strategies like model predictive control (MPC). The integration of digital technologies, including the Industrial Internet of Things (IIoT) and artificial intelligence (AI), is explored for enhancing control precision and predictive maintenance. Challenges such as nonlinearity of steam dynamics, equipment wear, and economic trade-offs are analyzed. The article underscores the importance of optimized steam flow for energy efficiency and environmental sustainability, particularly in the context of integrating renewable energy sources. Findings suggest that advanced control systems enhance reliability and flexibility, contributing to sustainable power generation.