A multi-energy building real-time energy management optimization method

Abstract

The invention provides an optimization method for real-time energy management of a multi-energy building. The method comprises the following steps: establishing a multi-energy building management optimization model; dividing upper and lower limit intervals of the historical electricity price into a plurality of sub-intervals, extracting data points from the plurality of sub-intervals to form a source task input sample, and obtaining an initial memory matrix corresponding to the source task input sample; Machine learning is carried out on the source task input samples and the corresponding initial memory matrixes, and an optimal memory matrix corresponding to each source task input sample is obtained according to the multi-energy building management optimization model; obtaining the currentreal-time electricity price, calculating the similarity between the current real-time electricity price and the source task input sample, calculating to obtain the initial memory matrix of the current real-time electricity price according to the optimal memory matrix corresponding to the source task input sample with the highest similarity, carrying out machine learning, and calculating to obtainthe output scheme of the multi-energy building management optimization system. According to the method, the output scheme of the multi-energy building system can be quickly obtained under the mechanism of real-time electricity price.

Description

technical field [0001] The invention relates to the technical field of energy management of multi-energy buildings, in particular to a method for optimizing real-time energy management of multi-energy buildings. Background technique [0002] In the context of the current huge consumption of fossil energy and the growing problems of greenhouse gas emissions and air pollution, the penetration rate of distributed power generation equipment is also increasing, and more and more distributed power generation equipment is installed on the side of commercial buildings. It has been integrated, and with the emergence of commercial building models including combined cooling-heating-power supply, the multi-energy building energy management system can effectively manage and utilize various energy sources to reduce energy consumption costs. In addition, commercial buildings that include combined cooling-heating-power supply also need to consider the user’s temperature comfort. By effectiv...

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Problems solved by technology

However, the general intelligent optimization algorithm takes a long time to calculate, and it is difficult to meet the time requirements of real-time energy management in buildings.

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