Multi-objective optimization for advanced superheater steam temperature control in a 300 MW power plant

Abstract

Control of superheater steam temperature (SST) is critical for the safety and efficiency of the coal-fired power plant. However, the conventional cascaded PI controller is faced with great challenges in regulating the SST within a satisfactory range in the environment of extensive load changes, which is inevitably becoming even worse due to the growing integration of the intermittent renewables. To this end, this paper introduces advanced control and multi-objective optimization (MOO) to improve the SST control performance and thus to enable the load being quickly adjusted in a wider range. The inner-loop PI controller parameters are optimized based on the tracking and regulation performance objectives subject to a robustness constraint. The improvement of the outer-loop controller involves two steps, (i) the outer-loop PI controller is upgraded to active disturbance rejection controller (ADRC) in order to eliminate the sluggish response to the external load disturbances; (ii) a mathematical algorithm is developed to depict the stable region for the ADRC parameters, serving as the MOO search space. Comparative simulations show the advantage of the proposed strategy, which is confirmed by a field test in an in-service 300MW power plant. It shows that the proposed strategy leads to a much smaller temperature deviation in both constant-load and load-varying conditions than the conventional control, making it less sensitive to the external disturbances. Furthermore, the load demand can be shifted more flexibly in a wide range (from 10MW to 15MW) while the SST is strictly confined within the allowable range, indicating a promising prospect of the proposed strategy in a power grid with high renewables penetration.