A short-term load prediction method considering somatosensory temperature and radiation intensity

Abstract

The invention discloses a short-term load prediction method considering somatosensory temperature and radiation intensity. The short-term load prediction method comprises the following steps of 1) inquiring sample data such as historical load and weather; 2) calculating historical somatosensory temperature data and a daily load level; 3) selecting an optimal'mode similar day 'from the historical sample data set on the basis of the day type information and meteorological data of the to-be-predicted day, and finally calculating to obtain a normalized load curve; 4) establishing a neural networkprediction model considering the somatosensory temperature and the sunlight intensity to obtain the load level of the to-be-predicted day; and 5) calculating load data of the to-be-predicted day through the normalization curve and the load level. According to the method, the influence on the somatosensory temperature of the load and the sunlight intensity of the distributed photovoltaic power generation are fully considered, the change rule of the historical load is fully considered, the load level and the load mode are separately predicted, the input dimension of the neural network is reduced, the network training load is reduced, and the calculation efficiency is improved.

Description

technical field [0001] The invention relates to a short-term load forecasting method considering body temperature and radiation intensity, and belongs to the technical field of power system load forecasting. Background technique [0002] At present, short-term load forecasting is the basis for power grid companies to prepare power generation plans and carry out real-time operation control work. Through accurate load forecasting, it is possible to economically arrange the start-up and shutdown of generating units, and reasonably arrange planned maintenance of generating units, ensuring the stability and reliability of the power grid While supplying power, it can effectively reduce the cost of power generation and improve the overall economic benefits of society. [0003] With the continuous improvement of residents' living standards and quality of life, the proportion of residential electricity load in the grid load is also increasing, the most obvious is summer air condition...

AI Technical Summary

Problems solved by technology

However, how to comprehensively consider meteorological factors such as temperature and humidity and the impact of distributed photovoltaics on short-term load forecasting has not been effectively resolved.

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