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New energy storage system scheduling optimization method considering demand response resources

A technology of demand response and energy storage system, applied in the field of power system to achieve the effect of reducing impact

Pending Publication Date: 2020-03-24
青海格尔木鲁能新能源有限公司 +4
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are certain problems in the current consumption of new energy
In 2018, the annual curtailment of wind power was 27.7 billion kWh, with a wind curtailment rate of 7%, and the curtailment of photovoltaic power was 5.49 billion kWh, with a curtailment rate of 3%. Although compared with 2017, the curtailment of wind and solar It has been alleviated, but the problem of new energy power consumption still needs to be solved

Method used

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  • New energy storage system scheduling optimization method considering demand response resources
  • New energy storage system scheduling optimization method considering demand response resources
  • New energy storage system scheduling optimization method considering demand response resources

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Embodiment Construction

[0025] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0026] figure 1 A schematic diagram of a computing device 100 according to one embodiment of the invention is shown. Such as figure 1 As shown, in a basic configuration 107 , computing device 100 typically includes system memory 106 and one or more processors 104 . A memory bus 108 may be used for communication between the processor 104 and the system memory 106 .

[0027] Depending on the desired configuration, processor 104 ma...

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Abstract

The embodiment of the invention discloses a new energy storage system scheduling optimization method considering demand response resources, and the method comprises the steps: training an intelligentload neural network model, so as to obtain a function of controllable active power of a residence with respect to a demand response control signal; based on the function of the controllable active power, optimizing by utilizing a new energy storage scheduling optimization model to obtain a demand response control signal; calculating controllable active power by utilizing a function of the controllable active power at least based on the demand response control signal; and obtaining a scheduling strategy of the new energy storage system by utilizing the new energy storage scheduling optimizationmodel at least based on the controllable active power.

Description

technical field [0001] The invention relates to the field of electric power systems, in particular to a scheduling optimization method for a new energy storage system that takes demand response resources into consideration. Background technique [0002] my country has abundant new energy resources, among which, the wind energy reserve that can be developed and utilized is 1 billion kilowatts, and the total solar energy received each year is 3.3×103-8.4×103 MJ per square meter. However, there are certain problems in the current consumption of new energy. In 2018, the annual curtailment of wind power was 27.7 billion kWh, with a wind curtailment rate of 7%, and the curtailment of photovoltaic power was 5.49 billion kWh, with a curtailment rate of 3%. Although compared with 2017, the curtailment of wind and solar It has been alleviated, but the problem of new energy power consumption still needs to be solved. The development of distributed new power sources is one of the impo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06N3/04G06N3/08
CPCG06Q10/06315G06Q50/06G06N3/084G06N3/045
Inventor 祁万年李静立刘英新宋锐
Owner 青海格尔木鲁能新能源有限公司
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