Joint scheduling method for air conditioner load and electric vehicle charging load

A technology for electric vehicles and charging loads, applied in data processing applications, special data processing applications, forecasting, etc., can solve problems such as optimization, less joint optimization, and ignoring thermodynamic processes

Pending Publication Date: 2021-07-09
TIANJIN UNIV
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Problems solved by technology

[0003] However, at present, the air conditioning load or the electric vehicle load is managed separately, and there are few studies on the joint optimization of the two demand response resources.
In the existing joint optimization studies, most either do not consider the thermodynamic process, ignore the time-varying characteristics of the air-conditioning load, and only regard

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  • Joint scheduling method for air conditioner load and electric vehicle charging load
  • Joint scheduling method for air conditioner load and electric vehicle charging load
  • Joint scheduling method for air conditioner load and electric vehicle charging load

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Embodiment Construction

[0094] The present invention will be further described below through specific embodiments and accompanying drawings. The embodiments of the present invention are for better understanding of the present invention by those skilled in the art, and do not impose any limitation on the present invention.

[0095] Such as figure 1 As shown, this embodiment provides a day-ahead optimization method for joint scheduling of air-conditioning and electric vehicle charging loads, including the following steps:

[0096] Step 1: Establish a day-ahead forecasting model of total building electricity load considering electric vehicle charging load.

[0097]In the embodiment, three different air-conditioning operation scenarios are formulated, which are: the temperature is set at 26°C during the working hours (8:00-20:00), and the temperature is set at 26°C during the non-working hours (00:00-7:00, 21:00). 00-23:00) the temperature is set to 28°C; the whole day temperature is set to 26°C; the t...

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Abstract

The invention discloses a day-ahead optimization method for joint scheduling of an air conditioner load and an electric vehicle charging load. The method comprises the following steps: 1) establishing a building total electrical load day-ahead prediction model considering the electric vehicle charging load; 2) performing multi-objective optimization on the building total electrical load day-ahead prediction model in view of two aspects including system operation economy and power grid friendliness; and 3) establishing a comprehensive evaluation calculation method, and determining a comprehensive optimal operation scheme on the Pareto frontier. According to the invention, on the basis of the characteristic that two demand response resources of the electric vehicle charging load and the air conditioning load can both provide flexibility for power grid operation and have complementation in time, a building total electrical load day-ahead prediction model considering the two resources at the same time is established, and a day-ahead optimization method is provided for joint scheduling of an air conditioner load and an electric vehicle charging load.

Description

technical field [0001] The invention relates to the field of building energy conservation, in particular to a method for joint scheduling of air-conditioning loads and electric vehicle charging loads Background technique [0002] Among flexible loads in buildings, air-conditioning loads account for a large proportion and can be adjusted flexibly. Part of the peak load during the day can be transferred through pre-cooling at night, while electric vehicles of a certain scale can schedule charging loads when they are parked at the workplace during the day, and the air-conditioning load Complementary in time, both DR resources provide considerable flexibility in grid operation. [0003] However, at present, the air-conditioning load or electric vehicle load is managed separately, and there are few studies on the joint optimization of the two demand response resources. In the existing joint optimization studies, most either do not consider the thermodynamic process, ignore the t...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06Q10/04G06Q50/06G06F119/08
CPCG06F30/20G06Q10/04G06Q50/06G06F2119/08
Inventor 丁研鄢睿王翘楚
Owner TIANJIN UNIV
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