Energy management apparatus and energy management method

Abstract

An energy management apparatus and an energy management method are provided. The energy management apparatus receives a plurality of first operation data and environment data, derives a plurality of simulated energy data through energy simulation based on the first operation data and the environment data, calculates an error value between a real environment value and a simulated environment value of the simulated energy data, decides a simulation objective value according to the error value, and decides a plurality of second operation data through energy simulation based on a search algorithm and the simulation objective value. The first operation data correspond to a first time interval, each of the first operation data corresponds to one of a plurality of devices, and the second operation data correspond to a second time interval, and each of the second operation data corresponds to one of the devices.

Description

technical field [0001] The present invention relates to an energy management device and an energy management method; more specifically, the present invention relates to an energy management device and an energy management method based on dynamic energy simulation. Background technique [0002] In today's increasingly scarce resources and rising energy prices, energy management has gradually become a topic of public concern. By measuring, recording and analyzing the past energy consumption situation, and then changing the way of energy consumption according to the analysis results (for example: for a building, changing the operation mode of the equipment in it), this is the basic operating concept of the energy management mechanism . [0003] The known energy management mechanisms only analyze the energy consumption of a single type of equipment, and use the energy consumption data collected over a long period of time (for example: one year) to establish a regression equatio...

AI Technical Summary

Problems solved by technology

When the parameters considered are incomplete, the results predicted by conventional energy management mechanisms will be inaccurate

In addition, due to the use of the technique of establishing regression equations, the conventional energy management mechanism is not scalable, so it is not flexible in application

Furthermore, the conventional energy management mechanism ignores some factors that determine the behavior of electricity consumption (for example: the electricity consumption behavior of large-scale users mainly depends on factors such as ambient temperature, season, and building body design), which also leads to the conventional The results predicted by the energy management mechanism will be inaccurate

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