Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of predefined features with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Some embodiments may provide viewing, creating, and manipulating of multiple versions of a solar collector layout design for a particular installation worksite. The use of versions may allow analysis of alternative layouts, alternative feature classifications, and cost and performance data corresponding to alternative design choices. Version summary information providing a representative comparison between versions across a number of dimensions may be provided.

In an embodiment, measurements are simulated of direct normal irradiance, diffuse horizontal and global horizontal irradiance from groups of two or more photovoltaic arrays and/or irradiance sensors which are located in close proximity to each other and which have different tilt and azimuth angles. Irradiance measurements derived from solar power system power measurements are combined with measurements made by irradiance sensors to synthesize an image of ground level global horizontal irradiance which can be used to create a vector describing motion of that image of irradiance in an area of interest. A sequence of these irradiance images can be transformed into a time series from which a motion vector can be derived.

A power generation prediction system using a first and second neural networks is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again. The power generation prediction data is a power generation prediction bound having a maximum and minimum power generation prediction values, and thus the power deployment terminal in a power grid can deploy power more precisely.

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre-defined features with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Some embodiments may provide viewing, creating, and manipulating of multiple versions of a solar collector layout design for a particular installation worksite. The use of versions may allow analysis of alternative layouts, alternative feature classifications, and cost and performance data corresponding to alternative design choices. Version summary information providing a representative comparison between versions across a number of dimensions may be provided.

A device comprises a platform constructed and arranged to be mounted to one or more solar array modules and one or more solar irradiance sensors on the platform configured to receive incident solar energy, the one or more solar irradiance sensors oriented on the platform so that the received incident solar energy is comparable to that received by the solar array modules, the one or more solar irradiance sensors providing solar irradiance signals in response to the incident solar energy. A processor is on the platform, the processor configured to receive the solar irradiance signals and, in response, generating a performance reference metric based on the solar irradiance signals, the performance reference metric related to the expected performance of the one or more solar array modules to which the platform is mounted. A transmitter is on the platform, the transmitter configured to periodically transmit the performance reference metric to a receiver.

A device comprises a platform constructed and arranged to be mounted to one or more solar array modules and one or more solar irradiance sensors on the platform configured to receive incident solar energy, the one or more solar irradiance sensors oriented on the platform so that the received incident solar energy is comparable to that received by the solar array modules, the one or more solar irradiance sensors providing solar irradiance signals in response to the incident solar energy. A processor is on the platform, the processor configured to receive the solar irradiance signals and, in response, generating a performance reference metric based on the solar irradiance signals, the performance reference metric related to the expected performance of the one or more solar array modules to which the platform is mounted. A transmitter is on the platform, the transmitter configured to periodically transmit the performance reference metric to a receiver.

An optimization engine determines an optimal configuration for a solar power system projected onto a target surface. The optimization engine identifies an alignment axis that passes through a vertex of a boundary associated with the target surface and then constructs horizontal or vertical spans that represent contiguous areas where solar modules may be placed. The optimization engine populates each span with solar modules and aligns the solar modules within adjacent spans to one another. The optimization engine then generates a performance estimate for a collection of populated spans. By generating different spans with different solar module types and orientations, the optimization engine is configured to identify an optimal solar power system configuration.

A photovoltaic energy system includes a photovoltaic field configured to convert solar energy into electrical energy, one or more solar intensity sensors configured to measure solar intensity and detect a cloud approaching the photovoltaic field, and a controller. The controller receives input from the solar intensity sensors and predicts a change in solar intensity within the photovoltaic field before the change in solar intensity within the photovoltaic field occurs. The controller is configured to preemptively adjust an electric power output of the photovoltaic energy system in response to predicting the change in solar intensity within the photovoltaic field.

A method for controlling the orientation of a single-axis solar tracker orientable about an axis of rotation, including observing the evolution over time of the cloud coverage above the solar tracker; determining the evolution over time of an optimum inclination angle of the solar tracker substantially corresponding to a maximum of solar radiation on the solar tracker, depending on the observed cloud coverage; predicting the future evolution of the cloud coverage based on the observed prior evolution of the cloud coverage; calculating the future evolution of the optimum inclination angle according to the prediction of the future evolution of the cloud coverage; servo-controlling the orientation of the solar tracker according to the prior evolution of the optimum inclination angle and depending on the future evolution of the optimum inclination angle.

A monitoring system that is configured to monitor a property is disclosed. The monitoring system includes a sensor that is configured to generate sensor data that reflects an attribute of the property; a solar panel that is configured to generate and output power; and a monitor control unit. The monitor control unit is configured to: monitor the power outputted by the solar panel; determine that the power outputted by the solar panel has deviated from an expected power range; based on determining that the power outputted by the solar panel has deviated from the expected power range, access the sensor data; based on the power outputted by the solar panel and the sensor data, determine a likely cause of the deviation from the expected power range; and determine an action to perform to remediate the likely cause of the deviation from the expected power range.