Abstract: A system and method is disclosed for calculating potential power generation for a wind farm, the wind farm including a plurality of wind turbines. The system and method include measuring the power generated by the wind farm; acquiring turbine data from at least a subset of the plurality of wind turbines, the wind turbine data including local wind speed and power generated at the local wind speed; acquiring wind resource data for the wind farm, the wind resource data including wind speed; generating a power curve from the turbine data and the wind resource data, the power curve plotting the relationship between wind speed and power generated; calculating power lost due to availability, subcurve, and curtailment, the power loss calculated for at least said subset of turbines; and aggregating the power lost in order to determine an aggregate power loss for the wind farm.

Abstract: A voltage pattern analysis system and method may automate aspects of the process of mapping or assigning utility meters to a specific transformer or other distribution node by identifying misassociated meters and correcting a system-wide transformer assignment or distribution node assignment. When a meter's voltage signal does not correlate well with other meters' voltage signals on the same transformer, the meter is likely misassociated to that transformer. A pairwise voltage signal correlation may be computed for all meters assigned to a transformer and a voltage signal correlation for every transformer in the system, or a subset thereof, may be imputed. Individual meter correlations may then be compared with the transformer correlation. For meters identified as misassociation candidates, transformers or other distribution nodes within a specified radius may be considered for reassignment of the meter.

Abstract: A system and method is disclosed for calculating potential power generation for a wind farm, the wind farm including a plurality of wind turbines. The system and method include measuring the power generated by the wind farm; acquiring turbine data from at least a subset of the plurality of wind turbines, the wind turbine data including local wind speed and power generated at the local wind speed; acquiring wind resource data for the wind farm, the wind resource data including wind speed; generating a power curve from the turbine data and the wind resource data, the power curve plotting the relationship between wind speed and power generated; calculating power lost due to availability, subcurve, and curtailment, the power loss calculated for at least said subset of turbines; and aggregating the power lost in order to determine an aggregate power loss for the wind farm.

Abstract: Enhanced meteorological measure-correlate-predict systems and methods. The systems and methods preferably consider publicly available, long-term data sets at each of a plurality of locations nearby a potential wind farm location. A test tower is preferably located at the potential location to collect a shorter-term data set, which, in combination with the long-term data set, is used to correlate and train embodiments of the systems and methods of the present invention using computational learning systems. Longer-term data can then be predicted for the potential wind farm location based on the correlation.