Intelligent scheduling system based on Internet of Things and load scheduling method thereof

Abstract

The invention relates to an intelligent scheduling system based on the Internet of Things, and the system comprises a first data processing module which is configured to monitor a distributed power supply and carry out the evaluation of an output prediction value of the distributed power supply; a second data processing module which is configured to monitor a load source and evaluate a load prediction value of the load source; a third data processing module which is configured to monitor the use states of a plurality of mobile energy-consuming devices in the scheduling network, and evaluate the schedulable capability of the mobile energy-consuming device in the first use state and the first power demand of the mobile energy-consuming device in the second use state; and an intelligent scheduling module which is configured to determine a first power grid load scheduling instruction based on a first evaluation result obtained by the first data processing module, a second evaluation result obtained by the second data processing module and a third evaluation result obtained by the third data processing module.

Description

technical field [0001] The invention relates to the technical field of electric energy management, in particular to an intelligent dispatching system based on the Internet of Things and a load dispatching method thereof. Background technique [0002] The Internet of Things (IoT) is the application extension and evolution of the Internet and mobile communication networks, and is known as the third wave of global informatization after personal computers, the Internet and mobile communication networks. Wu Hequan, academician of the Chinese Academy of Engineering, concluded that the current application fields of the Internet of Things mainly include smart grid, smart transportation, smart logistics, ecological monitoring, electronic health care, smart home, production and operation safety monitoring, etc. The rapid development and popularization of Internet of Things technology has brought about major changes in the production and lifestyle of human society, especially in the fi...

AI Technical Summary

Problems solved by technology

[0006] The above technical solution comprehensively considers the environmental factors that affect actual driving, the driving habits of the driver and the battery characteristics of the electric vehicle, so as to predict and prompt the charging demand of the electric vehicle. However, it analyzes the environmental factors, driving habits and battery characteristics What is obtained is only the consumption prediction of battery energy. In fact, different users have different sensitivities to electricity and charging cost requirements. Therefore, only predicting battery energy consumption cannot truly reflect the charging demand, and it does not propose the charging and discharging process of electric vehicles. Solutions for reasonable regulation

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