Photovoltaic refrigerator system controlled based on load prediction and demand response of neural network

Abstract

The invention discloses a photovoltaic refrigerator system controlled based on the load prediction and demand response of a neural network. A city power grid is connected with a control circuit, a photovoltaic cell panel is connected with an inverter circuit through the control circuit, and the inverter circuit is connected with a refrigerator. A load prediction module is used for building a refrigerator load prediction model according to the meteorological data of Meteorological Bureau, historical load information, refrigerator storing capacity, the types of stored goods and refrigerating temperature and predicting the future load of the refrigerator. An energy management center module is used for making an operation strategy and carrying out control through photovoltaic generation power, the predicted load of the refrigerator and the comparison and analysis of photovoltaic generation on-grid power price and city power price. The photovoltaic refrigerator system can realize the effective combination of photovoltaic generation and the refrigerator, solves the matching problem of photovoltaic generation and the refrigerator through load prediction, reduces fluctuation caused by photovoltaic generation to the power grid, and can not only meet the requirements of users but also realize energy saving and emission reduction.

Description

Technical field [0001] The invention relates to a photovoltaic cold storage, in particular to a photovoltaic cold storage system based on neural network load prediction and demand response control. Background technique [0002] With the improvement of people's living standards, people are increasingly dependent on frozen and refrigerated food, and the frozen and refrigerated food industry is showing a momentum of rapid development. According to statistics, the total amount of cold storage in the country reached 33.2 million tons in 2014, equivalent to 83 million cubic meters, an increase of 36.9% compared with 24.11 million tons last year. As the main link of cold chain logistics, the demand for energy consumption is also increasing year by year. A large number of cold storages consume huge amounts of electric energy, which has caused a shortage of electricity in cities and put huge pressure on the power grid. These electric energy also consume a lot of coal resources. [0003] I...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a photovoltaic cold storage system based on neural network load forecasting and demand response control to solve the matching problem between photovoltaic and cold storage, reduce the system battery configuration capacity, reduce system costs, and reduce photovoltaic power generation as much as possible The fluctuations generated by the power grid, and the most economical operation strategy for the user is given

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