Weather forecast data preprocessing method for building load prediction

Abstract

The invention discloses a weather forecast data preprocessing method for building load prediction, which comprises the following steps of 1, collecting the historical data, and determining an input variable of a load prediction model by analyzing the historical data, and 2, analyzing an error distribution rule of an error between the weather forecast data at a prediction moment and a historical record of the real-time weather data; 3, performing error random sampling simulation on the weather forecast data at the prediction moment according to an error distribution rule, inputting the corrected weather forecast data into the building load prediction model, and correcting the weather forecast input parameters related to the prediction moment, so that the building load prediction model is realized. The method can effectively solve the problem of uncertainty of the weather forecast data, and the weather forecast data is corrected by analyzing the error distribution law of the weather forecast data and the actual weather data, so that the method is used for predicting the building load.

Description

technical field [0001] The invention relates to the technical field of building load forecasting, in particular to a method for preprocessing weather forecast data for building load forecasting based on Monte Carlo random sampling. Background technique [0002] Heating, ventilation and air conditioning (HVAC) systems account for around 40% of a building's energy consumption, which means it has great potential for energy savings. However, the operation and management level of such systems is usually low, and the cooling capacity of the equipment does not match the actual demand, resulting in high energy consumption. Accurate load forecasting technology is the basis of HVAC system operation optimization, which is conducive to formulating operation strategies according to load changes, and lays a theoretical foundation for improving the thermal comfort of buildings and reducing energy consumption. [0003] With the rapid development of modern computer technology, many load for...

AI Technical Summary

Problems solved by technology

When using load forecasting technology, in order to predict the load of the building at a certain time in the next 24 hours in advance, it is necessary to use weather forecast data. The weather forecast data and real-time weather data often have deviations, which will cause the use of weather forecast data. There is also a certain error in the predicted load

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