Dynamic Power Plant Modeling

CFPP Flexibilization by Feedwater Repowering

To integrate renewable sources with conventional thermal power plants, operational flexibility needs to be enhanced to respond to the change in supply and demand and reduce renewable energy curtailment. One effective method is feedwater repowering, which modifies the feedwater heating system to enhance efficiency and improve the plant’s load-following capability. Our research utilizes advanced dynamic power plant modeling to simulate this process, employing tools such as Dymola, AVEVA, and MATLAB to analyze transient behavior, control strategies, and overall performance improvements.

Through dynamic simulations, we assess how feedwater repowering influences key operational factors like ramp rates, thermal efficiency, and startup/shutdown flexibility. By optimizing heat integration and control logic, we aim to reduce response times, increase part-load efficiency, and minimize energy losses, ensuring that CFPPs can better support grid stability in fluctuating energy markets. By bridging simulation-based analysis with real-world implementation, we contribute to a more adaptive and resilient power generation sector, supporting the transition to a sustainable and balanced energy mix.

Dynamic Power Plant with Thermal Energy Storage

Integrating thermal energy storage (TES) into power plants is a key strategy for enhancing grid flexibility and improving energy efficiency. By storing excess thermal energy during low-demand periods and utilizing it during peak loads, TES enables faster ramp-up times, better load-following capabilities, and reduced fuel consumption. Our research focuses on dynamic power plant modeling to analyze the integration of TES in coal-fired power plants (CFPPs) and other thermal generation systems.

Through dynamic simulations, we evaluate the impact of TES on transient operations, heat recovery efficiency, and system stability under varying grid conditions. By optimizing storage capacity, heat exchanger configurations, and control strategies, we aim to improve plant flexibility, reduce emissions, and enhance overall performance. This research is particularly relevant as power grids transition to higher shares of renewables, requiring conventional plants to operate more dynamically.

Thesis Posters

Coming Soon!