Locus Energy, Inc.

Charles McBrearty

Michael Herzig

Shawn Kerrigan

The present invention provides methods and systems to estimate energy losses due to partial equipment failure in photovoltaic (PV) systems based on measured power and energy data, weather data, PV system configuration information, and modeled power and energy generation data.

Estimation of energy losses due to partial equipment failure for photovoltaic systems from measured and modeled inputs

The present invention provides methods and systems to estimate energy losses due to shading in PV systems from data including the measured energy and power produced over the lifetime of the system, the system size and configuration data, the weather conditions (including irradiance, ambient & panel temperature, and wind conditions) over the lifetime of the system, and derived meteorological condition information (e.g., decomposed irradiance values at any time).

Estimation of shading losses for photovoltaic systems from measured and modeled inputs

The present invention provides methods and systems to estimate energy losses due to soiling in photovoltaic (PV) systems from data including the measured energy and power produced over the lifetime of the system, the system size and configuration data, the weather conditions (including irradiance, precipitation, ambient and panel temperature, and wind conditions) over the lifetime of the system, and derived meteorological condition information (e.g., the history of clear-sky conditions at the location of the site).

Estimation of soiling losses for photovoltaic systems from measured and modeled inputs

A computer implemented method of estimating solar irradiance, the method comprising: constructing a reference irradiance set of tuples; constructing a reference predictor set of tuples, merging the reference irradiance set of tuples and the reference predictor set of tuples by matching numerical identifiers for a location for which a global horizontal irradiance exists in the reference irradiance set of tuples and the timestamp with the numerical identifier for a particular location in the reference predictor set of tuples and the timestamp to provide a reference data set of tuples; and estimating the global horizontal irradiance for a specific location and a timestamp by minimizing the least squares error between the reference predictor set of tuples and the reference irradiance set of tuples to provide a set of estimated global horizontal irradiance values for a specific location and timestamp.

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San Francisco, CA, United States of America

Charles McBrearty