Patents by Inventor Kevin F. Forbes

Kevin F. Forbes has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210320495
    Abstract: Systems and methods for improving load energy forecasting in the presence of distributed energy resources in which a revised load forecast is calculated based on forecasted meteorological conditions data, forecasted wind and solar energy, forecasted load data, time data and time-series variables determined based on an analysis of the historical data. In exemplary embodiments, the revised load forecast is provided to energy management computer systems to enable appropriate levels of generation of conventional and renewable energy generation within the electric power grid.
    Type: Application
    Filed: April 14, 2021
    Publication date: October 14, 2021
    Inventor: Kevin F. Forbes
  • Patent number: 10656306
    Abstract: A computer system and method for improving the accuracy of predictions of the amount of renewable energy, such as solar energy and wind energy, available to an electric utility, and/or refine such predictions, by providing improved integration of meteorological forecasts. Coefficient values are calculated for a renewable energy generation model by performing a regression analysis with the forecasted level of renewable energy posted by the utility, forecasted weather conditions and measures of seasonality as explanatory variables. Accuracy is further enhanced through the inclusion of a large number of time series variables that reflect the systematic nature of the energy/weather system. The model also uses the original forecast posted by the system operator as well as variables to control for season.
    Type: Grant
    Filed: May 19, 2017
    Date of Patent: May 19, 2020
    Assignee: The Catholic University of America
    Inventors: Kevin F. Forbes, Ernest M. Zampelli
  • Patent number: 10127568
    Abstract: Systems and methods improve the forecast of electricity consumption, and/or refining such predictions. Predictions may be refined by accounting for factors such as preliminary predictions, pricing and cost information associated with future supply of energy, the extent of anticipated changes in the predictions, the time of day and/or anticipated daylight for the period of time. Coefficient values are calculated for a forecast error model that takes into account factors related to electricity consumption using existing historical electrical grid data. Using the calculated values, the forecast error model may be applied to current electricity demand forecasts.
    Type: Grant
    Filed: April 4, 2012
    Date of Patent: November 13, 2018
    Assignee: THE CATHOLIC UNIVERSITY OF AMERICA
    Inventors: Kevin F. Forbes, Ernest M. Zampelli, O. Chris S. St. Cyr
  • Publication number: 20170336534
    Abstract: A computer system and method for improving the accuracy of predictions of the amount of renewable energy, such as solar energy and wind energy, available to an electric utility, and/or refine such predictions, by providing improved integration of meteorological forecasts. Coefficient values are calculated for a renewable energy generation model by performing a regression analysis with the forecasted level of renewable energy posted by the utility, forecasted weather conditions and measures of seasonality as explanatory variables. Accuracy is further enhanced through the inclusion of a large number of time series variables that reflect the systematic nature of the energy/weather system. The model also uses the original forecast posted by the system operator as well as variables to control for season.
    Type: Application
    Filed: May 19, 2017
    Publication date: November 23, 2017
    Inventors: Kevin F. Forbes, Ernest M. Zampelli
  • Publication number: 20130096983
    Abstract: Systems and methods improve the forecast of electricity consumption, and/or refining such predictions. Predictions may be refined by accounting for factors such as preliminary predictions, pricing and cost information associated with future supply of energy, the extent of anticipated changes in the predictions, the time of day and/or anticipated daylight for the period of time. Coefficient values are calculated for a forecast error model that takes into account factors related to electricity consumption using existing historical electrical grid data. Using the calculated values, the forecast error model may be applied to current electricity demand forecasts.
    Type: Application
    Filed: April 4, 2012
    Publication date: April 18, 2013
    Applicant: THE CATHOLIC UNIVERSITY OF AMERICA
    Inventors: Kevin F. Forbes, Ernest M. Zampelli, O. Chris S. St. Cyr