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Method for identifying urban power grid feeder load based on artificial neural network

An artificial neural network and urban power grid technology, applied in the field of load composition identification of urban power grid feeders

Inactive Publication Date: 2017-04-26
CHINA ELECTRIC POWER RES INST +3
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Problems solved by technology

[0004] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides an identification method for feeder load composition of urban power grid based on artificial neural network. The present invention can effectively identify different building load composition of large-scale feeder nodes, which is helpful for predicting the dynamic characteristics of feeder node loads, evaluating Demand response potential, laying the groundwork for sound demand response policies and mechanisms

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  • Method for identifying urban power grid feeder load based on artificial neural network
  • Method for identifying urban power grid feeder load based on artificial neural network
  • Method for identifying urban power grid feeder load based on artificial neural network

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Embodiment Construction

[0042] The present invention will be further described in detail below in conjunction with the drawings.

[0043] This method collects the composition of typical urban building loads and the characteristics of daily power consumption, and builds different types of typical building load models based on EnergyPlus software. On this basis, a method is proposed to separate the urban grid feeder load into different types of typical building loads. method. The key is: 1) The typical load model library should be able to contain the main load types in the area where the feeder is to be separated; 2) The typical load model can effectively reflect the influence of seasons, dates and external environmental factors on the power consumption curve. Such as figure 1 As shown, the specific steps include:

[0044] Step 1. Collect the typical building load type (set as m type), historical electricity consumption information and corresponding weather information in the building climate zone corres...

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Abstract

The invention provides a method for identifying urban power grid feeder load based on an artificial neural network. The method comprises the following steps: (1) searching equipment composition, historical power consumption information and meteorological information of typical construction load of a corresponding climatic region; (2) establishing power consumption load models of all kinds of typical constructions; (3) generating load curves of corresponding time periods of all kinds of typical construction loads based on date and meteorological information of a to-be-identified feeder load curve; and (4) identifying the load composition of the to-be-identified feeder load curve by using a BP artificial neural network algorithm. According to the method provided by the invention, different construction load composition of large feeder nodes is effectively identified, which is conducive to predicting the dynamic load properties of the feeder nodes and evaluating the demand response potentials, and foundation is laid for regulating a reasonable demand response policy and mechanism.

Description

Technical field [0001] The invention relates to a method for identifying the load composition of a power grid feeder, in particular to a method for identifying the load composition of an urban power grid feeder based on an artificial neural network. Background technique [0002] The composition of the large-scale feeder node load in the power system is related to the characteristics, cycles and habits of end users' power consumption. It always changes continuously with the season, date and external environment, which affects the dynamic power consumption characteristics of the entire system load and creates disturbances to the grid. Shifting the peak load to the trough period through demand-side management will be beneficial to the balance of power generation and consumption, but the planning and formulation of management policies such as the design of dynamic electricity price mechanism need to be clear about the composition of the load of different power supply nodes, so as to e...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06Q50/06
CPCG06Q50/06G06F30/20
Inventor 王珂韩冰姚建国赵家庆杨胜春田江冯树海吕洋李亚平徐秀之刘建涛赵慧
Owner CHINA ELECTRIC POWER RES INST
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