A solar radiation heat sensor device includes: a black plate having a black surface; a silver plate having a silvery-white surface; a casing that supports the black plate and the silver plate in such a manner as to be exposed to an outside with the black surface and the silvery-white surface facing the same direction; a thermistor which is accommodated in the casing and is configured to measure temperatures of each of the black plate and the silver plate; and a processor configured to calculate a solar radiation heat amount based on a difference between the temperature of the black plate and the temperature of the silver plate, the temperatures being measured by the thermistor.

A solar radiation heat sensor device includes: a black plate having a black surface; a silver plate having a silvery-white surface; a casing that supports the black plate and the silver plate in such a manner as to be exposed to an outside with the black surface and the silvery-white surface facing the same direction; a thermistor which is accommodated in the casing and is configured to measure temperatures of each of the black plate and the silver plate; and a processor configured to calculate a solar radiation heat amount based on a difference between the temperature of the black plate and the temperature of the silver plate, the temperatures being measured by the thermistor.

A forecast engine is configured to analyze aerial and/or satellite images depicting a geographic area to identify the existence of solar panels within the geographic area at different times. Based on the installation time of each solar panel, the forecast engine estimates the solar power generation capacity of the solar panel. The forecast engine also analyzes meteorological data, including weather forecasts, to estimate a level of insolation at each solar panel within the geographic area across a range of times. The forecast engine can then determine the total amount of solar power generation within the given geographic area at a particular time using the solar power generation capacity of each solar panel and the level of insolation at each solar panel at the particular time.

A forecast engine is configured to analyze aerial and/or satellite images depicting a geographic area to identify the existence of solar panels within the geographic area at different times. Based on the installation time of each solar panel, the forecast engine estimates the solar power generation capacity of the solar panel. The forecast engine also analyzes meteorological data, including weather forecasts, to estimate a level of insolation at each solar panel within the geographic area across a range of times. The forecast engine can then determine the total amount of solar power generation within the given geographic area at a particular time using the solar power generation capacity of each solar panel and the level of insolation at each solar panel at the particular time.

Techniques for forecasting solar power generation include a computing device determining a clear-sky solar power generation level for a photovoltaic installation; receiving, from a first measurement device, measurement data indicating an amount of cloud cover at a first location of the first measurement device, wherein the first measurement device and the photovoltaic installation are located in a same geographical area; and generating a solar power generation forecast for the photovoltaic installation based on the clear-sky solar power generation level and the measurement data.

Techniques for forecasting solar power generation include a computing device determining a clear-sky solar power generation level for a photovoltaic installation; receiving, from a first measurement device, measurement data indicating an amount of cloud cover at a first location of the first measurement device, wherein the first measurement device and the photovoltaic installation are located in a same geographical area; and generating a solar power generation forecast for the photovoltaic installation based on the clear-sky solar power generation level and the measurement data.

Techniques for predicting solar power generation include a node measuring, using one or more sensors, a first time series of voltage readings for a first power line located at a first location, wherein a portion of power on the first power line is generated from solar irradiance on one or more first solar panels located at the first location; generating a first cross-correlation between the first time series of voltage readings and a second time series of voltage readings for a second power line located at a second location, wherein a portion of power on the second power line is generated from solar irradiance on one or more second solar panels located at the second location; and computing a wind vector based on the first location, the second location, and the first cross-correlation, wherein the wind vector is usable to forecast solar power generation at one or more other locations.

Certain aspects pertain to a cloud detector comprising a first detector module directed to a first region of the sky and a second detector module directed to a second region of the sky. Each detector module has a tube enclosing one or more sensing elements. The one or more sensing elements of the first detector module are configured to take weather condition readings from the first region of the sky. The one or more sensing elements of the second detector module are configured to take weather condition readings from the second region of the sky. In one aspect, the cloud detector is configured to detect cloud cover based on these weather condition readings. In some cases, the one or more sensing elements comprise an infrared radiation detector (e.g., thermopile) for measuring infrared radiation intensity and a photosensor element for measuring sunlight intensity.

Certain aspects pertain to a cloud detector comprising a first detector module directed to a first region of the sky and a second detector module directed to a second region of the sky. Each detector module has a tube enclosing one or more sensing elements. The one or more sensing elements of the first detector module are configured to take weather condition readings from the first region of the sky. The one or more sensing elements of the second detector module are configured to take weather condition readings from the second region of the sky. In one aspect, the cloud detector is configured to detect cloud cover based on these weather condition readings. In some cases, the one or more sensing elements comprise an infrared radiation detector (e.g., thermopile) for measuring infrared radiation intensity and a photosensor element for measuring sunlight intensity.

A rotating shadowband for shading a pyranometer includes a cylindrical ring and a semicircular shadowband held within the cylindrical ring, a motor configured for rotating the shadowband, at least one solar panel, a rechargeable battery, and a controller having circuitry configured to power the first motor to rotate the semicircular shadowband. The semicircular shadowband may include a window opening, wherein the window opening substantially extends from a center of the band to a first end. The controller rotates the shadowband 0 to 360 degrees about the central axis of the cylindrical ring to alternately shade the pyranometer for making diffuse radiation measurements and expose the pyranometer to direct solar radiation for making global radiation measurements. Alternatively, the shadowband may be solid and rotate pivotally 0 to 180 degrees or 0 to 360 degrees within the cylindrical ring to alternately shade and expose a pyranometer head to and from direct sunlight respectively.