User peak shaving potential analysis method based on data mining

An analysis method and data mining technology, applied in the field of electricity market

Active Publication Date: 2020-11-20
NANCHANG UNIV
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

At the same time, when evaluating the peak-shaving potential of residential users, it is faced with the problem of high-quality transmission, storage, processing and calculation of load data of a large number of scattered users

Method used

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  • User peak shaving potential analysis method based on data mining
  • User peak shaving potential analysis method based on data mining
  • User peak shaving potential analysis method based on data mining

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Embodiment 1

[0076] The embodiment of the present invention provides a data mining-based method for analyzing user peak-shaving potential. The overall framework is as follows: figure 1 shown, including the following steps:

[0077] Step 1: Based on the data collected by the smart meter at 96 points per day (that is, 15 minutes 1 data), use the improved K-means algorithm based on particle swarms to accurately classify electricity customers into "9 to 5", "overtime workers" ", "Night Owl" and "Otaku" four categories;

[0078] Step 2: Based on the above data, deeply excavate the characteristics of power consumption such as the matching degree between users and the system peak, power consumption level and house vacancy, and analyze the factors involved in the user's peak shaving potential in multiple dimensions, such as: weather temperature, user's own economic and cultural level , the urban and rural category of the user's location;

[0079] Step 3: Recognize the pattern class label of the ...

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Abstract

The invention discloses a reasonable and effective user peak shaving potential analysis method based on data mining, and the method comprises the steps: firstly enabling power utilization customers tobe precisely classified into D categories through employing a K-means algorithm based on particle swarm improvement based on the power utilization collection data of C points of an intelligent electric meter every day; secondly, deeply mining the power consumption level of the user, the peak matching degree with the system and the power consumption characteristics of the vacancy condition of thehouse based on the data, and performing multi-dimensional analysis on factors related to the peak regulation potential of the user; performing pattern label identification on the user based on a BP neural network; and finally, building a peak shaving potential analysis model of the user by using an improved RBF network based on a genetic algorithm. The peak shaving potential of the user is reasonably analyzed, implementation of the demand response activity is effectively guided, and the effectiveness of the demand response activity is improved.

Description

technical field [0001] The invention relates to the technical field of electric power market, in particular to a data mining-based analysis method for user peak-shaving potential. Background technique [0002] With the continuous development of smart grid technology, demand response (Demand Response, DR) plays an increasingly important role in the economical and stable operation of the grid. Demand response strategies can improve the reliability of power supply in the distribution network. In recent years, the demand for electricity across the country has maintained rapid growth, power shortages have occurred from time to time, and the pressure on power grid operation has continued to increase. Although orderly electricity consumption can guarantee the stability of electricity consumption order at present, it will inevitably have a certain degree of impact on industrial production; if only by means of expanding the installed capacity of generators, it will face greater techn...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06K9/62G06N3/00G06N3/04G06N3/08G06N3/12
CPCG06Q10/06315G06Q10/06393G06Q50/06G06N3/006G06N3/08G06N3/126G06N3/045G06F18/23213Y02D10/00
Inventor 杨胡萍范锦张扬彭鑫黄煌
Owner NANCHANG UNIV
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