US 12,224,586 B2
Adaptive persistence forecasting for control of distributed energy resources
Hossein Ghassempour Aghamolki, Edina, MN (US); Arun Sukumaran Nair, Denver, CO (US); Abhinandan Tripathi, Kannauj (IN); and David Wu Ganger, Lakewood, CO (US)
Assigned to EATON INTELLIGENT POWER LIMITED, Dublin (IE)
Filed by Eaton Intelligent Power Limited, Dublin (IE)
Filed on Apr. 25, 2022, as Appl. No. 17/728,177.
Prior Publication US 2023/0344225 A1, Oct. 26, 2023
Int. Cl. H02J 3/00 (2006.01); G05B 13/04 (2006.01)
CPC H02J 3/003 (2020.01) [G05B 13/048 (2013.01); H02J 2203/20 (2020.01)] 18 Claims
OG exemplary drawing
 
1. A method of adaptive persistence forecasting for load control comprising:
receiving historical load values for a site comprising at least one component that consumes energy;
receiving historical temperature values corresponding to dates of the historical load values;
evaluating the historical load values and the historical temperature values to determine a correlation coefficient;
determining that there exists at least a threshold correlation between a load activity and temperature for the historical load values and the historical temperature values based on the correlation coefficient;
in response to determining that there exists at least the threshold correlation, normalizing the historical load values based on a set temperature;
applying an adaptive seasonal persistence model to the normalized historical load values to output a forecast;
receiving a temperature prediction;
generating a correction term using the temperature prediction and a correlation relationship between the historical load values and the historical temperature values identified when evaluating the historical load values and the historical temperature values;
applying the correction term to the forecast;
rescaling the forecast; and
controlling energy resources at the site using the rescaled forecast.