Voltage Correlation for Cloud Motion Solar Forecasting
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Solution Overview
Problem
Existing methods for predicting electricity generation from solar panels, such as satellite-based and ground-based nowcasting, are expensive, inaccurate, and have availability issues, complicating the utility provider's ability to accurately predict electricity demand.
Innovation Solution
A wireless mesh network of nodes that measure voltage fluctuations to estimate cloud movements and compute time offsets, allowing for near-term solar forecasting by correlating voltage time series data across multiple locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If satellite-based nowcasting is used to estimate solar irradiance, then broad regional coverage is achieved, but the cost becomes quite expensive and accuracy decreases due to low resolution
Solution Approach 1:
The patent replaces expensive satellite-based nowcasting with a network of low-cost electricity meters that continuously monitor voltage fluctuations. These meters provide frequent, high-resolution measurements at multiple locations without the high launch and maintenance costs of satellites, achieving both broad coverage and high accuracy through distributed sensing.
Solution Approach 2:
The patent substitutes optical/satellite-based measurement systems with electrical measurement systems. By monitoring voltage fluctuations in the power grid caused by cloud-induced changes in solar panel generation, the system achieves accurate solar irradiance estimation through electrical signals rather than optical imaging, providing both high resolution and continuous availability.
2Measurement precision
If ground-based skyward facing cameras are deployed for nowcasting, then high-resolution cloud images are captured, but the cost increases due to costly optics and availability is limited to specific deployment locations
Solution Approach 1:
The patent replaces expensive ground-based camera systems with inexpensive electricity meters that are already deployed across the power grid. These meters provide continuous, high-resolution measurements of solar generation effects without requiring costly optical equipment or specialized deployment locations, making the system both affordable and widely available.
Solution Approach 2:
The patent uses the power grid itself as an intermediary measurement medium. Instead of directly observing clouds with cameras, the system measures the indirect effect of clouds on solar panel generation through voltage fluctuations in the power line, providing accurate solar irradiance estimation without optical equipment.
3Area of stationary object
If satellite-based nowcasting is used, then broad regional coverage is achieved, but periodic unavailability occurs due to orbital trajectories
Solution Approach 1:
The patent replaces periodic satellite passes with continuous monitoring through the power grid infrastructure. Electricity meters operate continuously without interruption, providing uninterrupted measurements of voltage fluctuations that reflect real-time changes in solar irradiance, eliminating the periodic unavailability inherent in orbital-based systems.
Solution Approach 2:
The patent utilizes the existing power grid infrastructure and electricity meters that are already in place for billing purposes. These meters continuously monitor electrical parameters and can detect solar generation effects without requiring separate dedicated measurement equipment or external observation systems, providing reliable continuous data using self-sufficient infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables utility providers to anticipate electricity demand based on real-time weather conditions, improving the efficiency of electricity production and distribution.
Implementation Method 1
a first node in a wireless mesh network measures a first plurality of voltage fluctuations in a first power line to a solar panel at a first location
Implementation Method 2
The node determines the node's geolocation based on a signal strength of the wireless signal received at the node
Implementation Method 3
generating, at the first node, a first cross-correlation between the first voltage time series and a second voltage time series generated by a second node
Data Source
AI summary
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.