Low-energy-consumption smart home system capable of predicting energy regeneration

Abstract

The invention provides a low-energy-consumption smart home system capable of predicting energy regeneration. The system comprises an intelligent control module, an energy prediction module, a sensor network module, a video monitoring module, an execution module, an energy module and a monitoring module. The intelligent control module is used for controlling and managing energy, a lighting system,a home theater, a security alarm and doors and windows. The energy prediction module is used for predicting the production capacity of renewable energy sources. The sensor network module is used for environmental data monitoring, the video monitoring module is used for environmental image acquisition. The execution module comprises household appliances, audios and videos, doors and windows and thelike. The energy module comprises an energy storage unit, a household wind turbine and a photovoltaic array, and the monitoring module comprises a mobile phone, a local display screen and a householdnetwork server. The system is characterized in that the energy production capacity is predicted through the energy prediction module, the corresponding energy working mode is selected, and thereforemaximization of energy benefits is achieved.

Description

technical field [0001] The invention relates to the field of intelligent monitoring, in particular to an energy monitoring system based on the combination of wavelet transform and ARIMA model. Background technique [0002] A smart house is defined as a modern induction house with various integrated systems capable of remote control and mutual communication, and in recent years, energy saving has become a concern of smart houses, and people aim to build a building with zero energy consumption, but there is no Focus on the concept of energy management. [0003] The present invention proposes a low-energy smart home system that can predict energy regeneration. The system inputs historically generated and used energy as samples to the energy management module to output predictions. The module uses wavelet decomposition to remove sample disturbances, and differentially integrates moving average The autoregressive model ARIMA outputs prediction, and the ARIMA model prediction res...

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Problems solved by technology

[0002] A smart house is defined as a modern induction house with various integrated systems capable of remote control and mutual communication, and in recent years, energy saving has become a concern of smart houses, and people aim to build a building with zero energy consumption, but there is no Focus on the concept of energy management

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