Condensate Throttling Based Coordinated System Optimization with Improved Simplex Method for an 1000-MW USC Power Unit

In order to absorb more new energy power sources, regional load dispatch center puts up very high requirement for the operation flexibility, load fast-following and deep peak load regulation ability of an ultra-supercritical (USC) power unit. Therefore, it is very significant to adopt advanced control strategies to optimize the Coordinated Control System (CCS). In this work, the load prediction neural network model considering `condensate throttling' and the main steam pressure prediction model are developed by taking a 1000MW ultra-supercritical power unit as the object investigated. Based on the established models, a classic optimization theory-improved simplex method is selected as the CCS optimization algorithm. An intelligent coordination optimization scheme with condensate throttling is designed, and the real-time optimization program is developed with MATLAB software. Detailed simulation tests are carried out in the full-scope simulator of the 1000MW power unit. Simulation results indicate that the proposed scheme can effectively improve the coordinated control quality with faster load response, less main steam pressure fluctuation during dynamic load-changing process.