Flexibility improvement of 1000 MW ultra-supercritical unit under full operating conditions by error-based ADRC and fast pigeon-inspired optimizer

Abstract

The flexible operation capacity of ultra-supercritical (USC) unit under full operating conditions must be promoted to adapt a larger-scale renewable energy integrated into the power grid. To this end, a flexible operation method fusing the error-based ADRC and fast pigeon-inspired optimizer is designed and employed to USC unit to achieve deep peak shaving and rapid load regulation. Firstly, the urgency of the proposed method is illustrated via analyzing the control difficulties of USC unit under flexibility requirements. Then, the error-based ADRC scheme which adopts a broader sense of disturbances in control loops is formulated for USC unit. Thanks to the error-based ADRC, all the unknown uncertainties in unit are precisely estimated and compensated in real-time which is conducive to its precise load regulation. Furthermore, the fast pigeon-inspired optimizer combined with the two-stage optimization and bi-quantum parallel search is used to attain the optimal parameters of error-based ADRC. A multi-criteria optimization function composes the load tracking error and smoothness of manipulated variable is established to guide the unit to flexible operation. The integrated control scheme effectively blends the features of rapid load tracking, exactly disturbance rejection and fast parameters tuning. Finally, the effectiveness of the proposed controller is successfully confirmed based on a 1000 MW USC unit. The simulation results reveal that the flexible operation capacity of USC unit under full operating conditions is promoted by the error-based ADRC approach. The average load tracking error of unit is reduced from 4.22 MW to 2.45 MW, and the settling time is simultaneously shortened from 188.52s to 158.80s compared to the ADRC method. Hence, the integrated error-based ADRC method provides a practical reference for the flexibility improvement of 1000 MW USC unit under full operating conditions.