Regression method and device for load rate-efficiency curve of boiler

Abstract

The invention discloses a regression method for a load rate-efficiency curve of a boiler. The method comprises the following steps: S1, obtaining a load rate-efficiency data set according to operationdata of the boiler; s2, performing weighted polynomial fitting on data points in the load rate-energy efficiency data set according to a local regression algorithm to obtain corresponding regressiondata points; and S3, forming a regression curve of the boiler load rate-efficiency curve through all the regression data points. The invention further discloses a regression device for the boiler loadrate-efficiency curve. The device comprises a data acquisition module, a regression fitting module and a curve forming module. According to the method, the load rate-energy efficiency curve of the gas-fired boiler is regressed by utilizing a local weighted regression algorithm, so that the influence of abnormal data on a fitting curve can be well reduced, and a more accurate regression curve is obtained. Therefore, a better fitting effect is obtained in a practical problem processing process.

Description

technical field [0001] The invention relates to the technical field of digital energy, in particular to a regression method and device for a boiler load rate-efficiency curve. Background technique [0002] Gas boilers consume natural gas to produce hot water or hot steam. Its load rate (average over a period of time) refers to (actual load / maximum load) × 100%, and the energy efficiency of a boiler (average over a period of time) refers to the quality of hot water or hot steam produced by consuming a unit volume of natural gas (Unit: ton / cubic meter). If the load rate is X and the energy efficiency is Y, then the load rate-energy efficiency curve of the gas boiler can be formed (similarly, if the energy efficiency is X, and the load rate Y is used, the energy efficiency-load rate curve of the gas boiler can be formed). The boiler load rate-energy efficiency curve has important guiding significance for the high-efficiency use of boilers and the optimal scheduling of multipl...

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Problems solved by technology

[0003] However, the load rate-energy efficiency curve is often extracted from the actual operating data of the boiler (such as using fitting, interpolation, or regression algorithms), because the boiler operation is suddenly affected by many external factors, or errors occur in the data collection process , so that the actual load rate-energy efficiency data has many outliers, and these outliers will introduce a large error when fitting the data

[0004] At present, in the fitting problem of the gas boiler load rate-energy efficiency curve, a relatively big problem is that the actual collected load rate-energy efficiency data itself has a lot of noise, especially when the load rate of the gas boiler is lower than 50%.

Therefore, using the existing conventional regression method will make the fitted curve not accurate enough

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