Heat exchange station heat exchange amount artificial intelligence analysis method and device based on weather and community heat loss

Abstract

The invention relates to a heat exchange station heat exchange amount artificial intelligence analysis method and device based on weather and community heat loss, electronic equipment and a storage medium. The method comprises the steps that indoor temperature is collected through indoor temperature and humidity sensing equipment, and indoor use heat is calculated; heat exchange quantity is obtained through a heat meter and an indoor heat loss proportion is calculated; with the indoor heat loss ratio and the historical outdoor air temperature as input, a prediction analysis model is established through nonlinear regression analysis, and an air temperature influence index is generated; and based on the air temperature influence index, a heat exchange amount plan is generated according to the weather forecast information, and the heat exchange amount is adjusted according to the heat exchange amount plan. Through application of the artificial intelligence technology, prediction of user side heat load changes can be realized, sufficient data mining is performed, production of a heat source is guided, and a basis is provided for heat exchange setting of a heat exchange station.

Description

Technical field [0001] The present disclosure relates to the field of energy, and in particular to an artificial intelligence analysis method, device, electronic equipment, and computer-readable storage medium for heat exchange station heat exchange based on weather and heat loss in a cell. Background technique [0002] In recent years, the rapid development of urban central heating, and the number of heat users has doubled, which puts forward higher requirements for the operation and management of the heating system. Improving the automation level of my country's central heating system and realizing an appropriate amount of heating is not only a requirement for improving the competitiveness of heating enterprises, but also an important link in achieving building energy conservation and emission reduction. Accurate urban heating is a key link to achieve proper heating control. Thermal power companies store a large amount of historical data during operation. However, due to the la...

AI Technical Summary

Problems solved by technology

Accurate urban heating is the key link to achieve appropriate heating control. The heating companies store a large amount of historical data during operation, but due to the lack of suitable data mining methods, these data have not been fully utilized in the adjustment of heating operation

[0003] For centralized heating, traditional energy companies adopt hot spots co-generation as heat source, build heat exchange stations in the community, exchange (or extract) part of the heat from the primary pipe network of the heat source, and supply it to the owners of the community. The amount of heat exchange is often based on past experience, which is not scientific enough, easily causes energy waste, and makes it difficult to achieve precise heating

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