International Business Machines Corporation

Universiti Brunei Darussalam

James Peter Cipriani

Anthony Paul Praino

Lloyd Alan Treinish

Younghun Kim

Ildar Khabibrakhmanov

Yogish Sabharwal

Vaibhav Saxena

Thomas George

Saiful A Husain

Rashmi Mittal

A set of characteristics of a period is extracted from a forecast that is applicable to the period and a geographical area. From a repository, a set of historical data is selected corresponding to a historical period, the set of historical data including a historical forecast related to the geographical area, and an actual measurement of wind at a location in the geographical area, the set of historical data having a subset of the set of characteristics. From the set of historical data, a function is computed to represent a discrepancy between the historical forecast and the actual measurement over the historical period. A bias value is computed from the function. By applying the bias to a value in the forecast, an adjusted forecast is produced of winds at a wind turbine located at a location in the geographical area.

Temporal bias correction in wind forecasting

Methods and arrangements for automating weather model configurations. Characteristics of a target geographical area are received, as are a plurality of existing weather model configurations which are implemented for undertaking weather modeling in other geographical areas. A subset of the existing weather model configurations is selected, the subset comprising configurations corresponding to geographical areas having characteristics similar to the characteristics of the target area. A weather model is run with respect to each configuration in the subset of existing weather model configurations. Based on the running of a weather model with respect to each configuration, an output set of weather model configurations is selected for undertaking weather modeling in the target area.

Automating weather model configurations

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Danbury, CT, United States of America

James Peter Cipriani