Electric power consumer data analyzing method

• US 20030120370A1
• Filed: 05/20/2002
• Published: 06/26/2003
• Est. Priority Date: 12/12/2001
• Status: Abandoned Application

• Current Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Inventors: Matsubara, Ryunosuke, Kitayama, Masashi, Izui, Yoshio
• Application Number:
  US10/150,076
• Publication Number:
  US 20030120370A1
• Time in Patent Office: Days
• US Class Current: 700/100
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

Data on electric energy consumption of respective electric power consumers are collected in a predetermined period. Total electric energy consumption by the electric power consumers are classified into m levels. Degree of load contribution of the electric power consumers in consideration of at least load factors of the load factors which are ratios of average values of the consumed electric energy of the electric power consumers to the maximum values of the consumed electric energy and uniformity coefficient which are ratios of sum totals of the maximum values of the consumed electric energy of the electric power consumers belonging to the same level of consumed electric energy in the period are classified into n levels, the respective electric power consumers are divided into m×n number of classes and the result is displayed or stored.

Claims

1. An electric power consumer data analyzing method realized in the electric power market in which a plurality of electric power consumers purchase electric power from an electric power supplier, the method comprising:

an electric power consumer data collection step of collecting data on electric energy consumption by the respective electric power consumer in a predetermined period;

a consumed electric energy classification step of classifying total electric energy consumption by the electric power consumers in said period into m levels;

a degree-of-load-contribution classification step of classifying degree of load contribution of the electric power consumers in consideration of at least load factors of the load factors which are ratios of average values of the consumed electric energy of the electric power consumers in said period to the maximum values of the consumed electric energy and uniformity coefficient which are ratios of sum totals of the maximum values of the consumed electric energy of the electric power consumers who belong to the same level of the consumed electric energy in said period into n levels;

an electric power consumer classification step of dividing the respective electric power consumers into m×

n number of classes based on the classification steps; and

an outputting step of outputting a result obtained in the electric power consumer classification step to a display unit for displaying or a storage unit for storing the results.

2. The electric power consumer data analysis method according to claim 1, wherein the degree of load contribution is calculated using

degree of load contribution=α

×

(load factor)+(1−

α

)×

(uniformity coefficient)

where α

is a coefficient which expresses a predetermined weight and 0<

α

≦

1.

3. The electric power consumer data analysis method according to claim 1 further comprising expressing data of the electric power consumers who correspond to the m×

n classes in a form of a map.

4. The electric power consumer data analysis method according to claim 1! wherein

in the electric power consumer data collection step, the data on electric energy consumption by the respective electric power consumer are separately collected in at least in two periods of a first period and a second period;

in the consumed electric energy classification step and the degree-of-load-contribution classification step, the total electric energy consumption is classified into m levels and the degree of load contribution is classified into n levels in the first and second periods; and

in the electric power consumer classification step, the respective electric power consumers are classified into m×

n number of classes in the first and second periods.

5. The electric power consumer data analysis method according to claim 1 further comprising a data mining process step of acquiring information related to the electric power consumers and analyzing a relationships between the classes and the information on the basis of the information.

6. The electric power consumer data analysis method according to claim 5, wherein the data mining process step includes a decision tree analysis process step of calculating the relationships between the classes and data contents of the information in a form of a tree.

7. The electric power consumer data analyzing method according to claim 5, wherein the data mining process step includes

a neural network process step which has data contents of the information of the electric power consumers who belong to the classes as an input layer, the classes to which the electric power consumers belong as an output layer, and an intermediate layer between the input layer and the output layer;

and

a network leaning process step of inputting the data contents of the information into the input layer and calculating a weight coefficient of the intermediate layer on the basis of the classes which are output from the output layer and to which the electric power consumers belong.

8. The electric power consumer data analysis method according to claim 5, wherein

in the electric power consumer data collection step, the data on electric energy consumption by the respective electric power consumer are separately collected in at least in two periods of a first period and a second period;

in the consumed electric energy classification step and the degree-of-load-contribution classification step, the total electric energy consumption is classified into m levels and the degree of load contribution is classified into n levels in the first and second periods;

in the electric power consumer classification step, the respective electric power consumers are classified into m×

n number of classes in the first and second periods and the electric power consumers are subdivided into smaller classes according to the classes to which the electric power consumers belong in the first period; and

the second period and the respective relationships between the subdivided respective classes and the respective information are analyzed in the data mining process step.

9. The electric power consumer data analysis method according to claim 1, wherein in the electric power consumer data collection step, the data on electric energy consumption by the respective electric power consumer in the daytime or the nighttime are collected in a predetermined period.