Method for determining consumption difference analysis optimized target value system of circulating fluidized bed unit

Abstract

The invention discloses a method for determining a consumption difference analysis optimized target value system of a circulating fluidized bed unit. The method comprises the steps of clustering collected sample operation parameters by using a K-means algorithm to obtain K data clusters; selecting a data cluster with the minimum arithmetic mean value according to the arithmetic mean value of each data cluster; and then determining a parameter corresponding to a clustering center of the selected data cluster as an optimized target value. Due to the adoption of the method for determining the consumption difference analysis optimized target value of the circulating fluidized bed unit, the real-time performance and the accuracy are improved; the complex calculation amount and test cost can be reduced; and manpower and material resources are greatly saved. The method for determining the consumption difference analysis optimized target value system of the circulating fluidized bed unit can be widely used in the field of consumption difference analysis of power stations.

Description

technical field [0001] The invention relates to a method for determining an optimization target value of consumption difference analysis, in particular to a method for determining an optimization target value system for consumption difference analysis of a circulating fluidized bed unit. Background technique [0002] Circulating fluidized bed boiler combustion technology is a clean coal-fired power generation technology with high efficiency, low pollution, strong variable load capacity, and wide fuel adaptability. Therefore, it has been vigorously developed in the installed capacity of the power grid in recent years. With the in-depth development of energy saving and emission reduction and the gradual maturity of the power market, it is an inevitable measure for thermal power units to actively promote the optimal economic operation of the production process to improve economic benefits, competitiveness, and reduce production costs, and this is an inevitable measure for circul...

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Problems solved by technology

At present, there is no uniform method for determining the optimization target value, and different methods also have some shortcomings, for example: 1. Modeling based on the design value, but this method will be aging with the operation of the unit, and the design value is no longer It is representative; 2. Carry out the unit optimization adjustment test to determine the optimization target value, but this method does not have many test points, and it is time-consuming and laborious; 3. The unit changes the working condition to calculate the benchmark value, but this method requires a large amount of calculation , and the accuracy is low

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