Multi-model intelligent optimizing prediction control method for boiler loads under low-load condition

Abstract

The invention discloses a multi-model intelligent optimizing prediction control method for boiler loads under the low-load condition. The method specifically comprises the steps that first, load points are selected to establish a controlled object model; second, a prediction controller is designed at all the load points according to the controlled object model, and thus the optimum control increment of the prediction controller is obtained; third, if the optimum control increment in the second step meets the constraint conditions, no treatment is required; and if not, a particle swarm algorithm needs to be adopted to search for the optimum control increment; and fourth, multi-model prediction control is adopted, and an improved recursive Bayesian weighting algorithm is used for weighing the output of all sub controllers according to deviation of the output of all sub models and the actual output. Through the self-adaptation intelligent optimizing control technology, stable and safe operation of a unit under the low-load coal supply economical blending combustion condition is achieved.

Description

technical field [0001] The invention relates to a boiler load control method, in particular to a multi-model intelligent optimization prediction control method for boiler load under low load. Background technique [0002] The contradiction between supply and demand in the power market in Northeast China is very prominent. Especially in Liaoning Province, due to the high proportion of heating units, the peak-shaving capacity of the power grid during the heating period is seriously insufficient, and it is urgently required that the units can achieve deep peak-shaving. Under such circumstances, the 350MW subcritical unit of Huaneng Dandong Power Plant took the lead in completing the transformation of deep peak regulation in the country. The minimum load under AGC control mode can reach 90MW. However, based on the actual needs of the power grid in Liaoning, it is hoped that the minimum load can be further reduced. , to further improve the peak-shaving capability of the power gri...

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Problems solved by technology

However, when the minimum load of the unit is further reduced, there are two bottleneck problems: First, under the low load condition of the boiler, boiler combustion is very sensitive to coal fineness, coal uniformity, air volume deviation and powder volume deviation, and the current To reduce production costs, enterprises have increased the economical blending of coal supply. At this time, how to effectively ensure the stable combustion of the boiler is particularly important; second, under the low load condition of the boiler, the dynamic characteristics of the controlled object of the unit will change greatly, and the controlled process The hysteresis and inertia will increase significantly, and the conventional control scheme composed of PID controller is difficult to control this process

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