Distributed asset optimization (DAO) system and method
First Claim
1. A method of determining an energy load on a power distribution component, the method comprising:
- collecting meter data for a group of meters, wherein some of the meter data is in an hourly format and some of the meter data is in a monthly format;
collecting weather data;
correlating the meter data with the weather data to generate tuning equations, wherein each of the tuning equations is associated with at least one of the meters and indicates a weather sensitivity of the associated meter;
normalizing the meter data in the hourly format to generate normalized hourly loadshapes that are independent of weather conditions and weekly variations;
combining the tuning equations and the normalized hourly loadshapes to generate a set of model coefficients for each of the meters, wherein the set of model coefficients reflects weather conditions and weekly variations for one of the meters.
8 Assignments
0 Petitions
Accused Products
Abstract
A method of determining an energy load on a power distribution component, and a system for storing such method are presented. The method entails collecting meter data (in various formats) and weather data. The meter data and the weather data are correlated to generate tuning equations, each of which is associated with at least one of the meters and indicates a weather sensitivity of that meter. Any meter data that is in the hourly or daily format are normalized to generate normalized hourly loadshapes that are independent of weather conditions and weekly variations. These normalized hourly loadshapes are combined with the tuning equations to generate a set of model coefficients for each of the meters. The set of model coefficients reflects weather conditions and weekly variations for one of the meters, and is useful for determining an energy load on the power distribution component.
63 Citations
51 Claims
-
1. A method of determining an energy load on a power distribution component, the method comprising:
-
collecting meter data for a group of meters, wherein some of the meter data is in an hourly format and some of the meter data is in a monthly format;
collecting weather data;
correlating the meter data with the weather data to generate tuning equations, wherein each of the tuning equations is associated with at least one of the meters and indicates a weather sensitivity of the associated meter;
normalizing the meter data in the hourly format to generate normalized hourly loadshapes that are independent of weather conditions and weekly variations;
combining the tuning equations and the normalized hourly loadshapes to generate a set of model coefficients for each of the meters, wherein the set of model coefficients reflects weather conditions and weekly variations for one of the meters. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
-
-
26. A computer-readable memory system to instruct a computer to function in a specified manner, the memory comprising:
-
instructions to collect meter data and weather data for a group of meters;
instructions to correlate the meter data with the weather data to generate tuning equations, wherein each of the tuning equations is associated with at least one meter and indicates a weather sensitivity of the meter;
instructions to normalize the meter data to generate normalized hourly loadshapes that are independent of weather conditions and weekly variations; and
instructions to combine the tuning equations and the normalized hourly loadshapes to generate a set of model coefficients for the meter, wherein the set of model coefficients reflects weather conditions and weekly variations for the meter; and
instructions to store the model coefficients so that the model coefficients are retrievable to determine the power load on a power distribution component. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50)
-
-
51. A system for determining energy usage load, the system comprising:
a memory system that has;
a first module for collecting meter data and weather data about a plurality of meters, wherein the meter data includes daily deviation information;
a second module for using the meter data and the weather data to generate a tuning equation specific to a meter;
a third module for developing normalized hourly loadshapes for meters from which hourly energy usage data are collected; and
a fourth module for generating model coefficients based on the daily deviation information, the tuning equation, and the normalized hourly loadshapes, wherein the model coefficients reflect weather sensitivity, revenue class, rate class, and loadfactor for each of the meters.
Specification