Renewable Energy System Location Identification via Data Triangulation

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Solution Overview

Problem

Current monitoring solutions for distributed renewable energy projects face challenges in accurately locating renewable energy systems and environmental sensors due to human error in geospatial data inputs, which hinders efficient monitoring and analysis.

Innovation Solution

A computer processor-based method that correlates energy production and environmental sensor data with known locations to triangulate the latitude and longitude of unknown systems and sensors, using geospatial interpolation and solar noon calculations to correct location errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If geospatial analytics are used for monitoring renewable energy systems, then monitoring effectiveness is improved, but location accuracy deteriorates due to human error in user inputs

Engineering Contradiction:

Improvemonitoring effectivenessVSAvoidlocation accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system automatically determines geospatial coordinates by analyzing energy production data and environmental sensor readings without requiring manual user input. The renewable energy system itself provides the data needed to locate itself, eliminating human error in coordinate entry while maintaining monitoring effectiveness

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses feedback loops where energy production data and sensor readings are continuously analyzed to refine and verify location accuracy. By comparing actual production data with expected production at different locations, the system iteratively improves location precision while maintaining effective monitoring

Inventive Principle:

Principle #23Feedback

2Ease of operation

If manual user input is used for geospatial data, then system deployment is simplified, but location accuracy deteriorates due to human error

Engineering Contradiction:

Improvesystem deployment simplicityVSAvoidlocation accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical data entry with an automated computational system that derives location from energy production and sensor data. This substitution eliminates human error while maintaining ease of deployment through automated processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If incorrectly located systems are monitored using geospatial algorithms, then fleet monitoring is enabled, but analytical accuracy deteriorates due to errors in incorrectly located regions

Engineering Contradiction:

Improvefleet monitoring capabilityVSAvoidanalytical accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

Each system automatically determines its own accurate location through analysis of its energy production data and sensor readings, ensuring that analytical algorithms receive accurate geospatial information while maintaining fleet-wide monitoring capabilities

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary location verification by analyzing energy production patterns and sensor data before applying analytical algorithms. This preliminary action ensures location accuracy is established upfront, preventing propagation of errors through subsequent analytical processing

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10564315B2Methods for location identification of renewable energy systems

Publication Date: 2020.02.18 LOCUS ENERGY

AI summary

A computer processor implemented method of identifying the location of a renewable energy system; providing a set of renewable energy systems having at least two location-known renewable energy systems each having a longitude and latitude pair and production data; providing at least one location-unknown renewable energy system in a computer processor; correlating by a computer processor each location-unknown renewable energy system to at least one location-known renewable energy system according to location-known renewable energy systems longitude and latitude pair and production data; providing a best-fit location for each location-unknown renewable energy system by triangulating the location-unknown renewable energy system to provide a triangulated latitude and longitude; setting the triangulated latitude and longitude for the location-unknown renewable energy system to become a location-known renewable energy system that is part of the set of renewable energy systems.