Renewable Energy Maintenance Planning Using Weather-Linked Predictive Insights

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Solution Overview

Problem

Existing renewable energy systems face inefficiencies due to manual data collection and interpretation, lack of real-time environmental data integration, and inadequate predictive maintenance, leading to suboptimal energy generation and increased maintenance costs.

Innovation Solution

The technology leverages multiple data sources to generate insights for optimizing renewable energy systems through data fusion and insight generation algorithms, integrating historical and real-time operational and environmental data to inform predictive maintenance and planning activities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual data collection and interpretation methods are used, then operational simplicity is maintained, but energy generation efficiency and maintenance optimization are compromised

Engineering Contradiction:

Improveenergy generation efficiencyVSAvoiddata collection and interpretation complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces manual data collection and interpretation (mechanical human operations) with an automated computer-based system that collects, processes, and analyzes operational and environmental data. This substitution enables efficient energy generation optimization without the limitations of manual methods, directly resolving the contradiction between productivity improvement and operational simplicity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables renewable energy systems to self-monitor and self-optimize by automatically collecting operational data, integrating environmental data, and generating maintenance predictions without external manual intervention. This self-service capability improves energy generation efficiency while maintaining operational simplicity through automation.

Inventive Principle:

Principle #25Self-service

2Reliability

If real-time environmental data integration is implemented, then predictive maintenance accuracy is improved, but data processing complexity increases

Engineering Contradiction:

Improvepredictive maintenance accuracyVSAvoiddata processing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent creates a multi-functional computer-based system that simultaneously performs data collection, environmental data integration, predictive analysis, and maintenance planning. This universal system handles multiple functions within a single integrated platform, improving predictive maintenance accuracy through real-time environmental data while managing data processing complexity through unified architecture.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces an intermediary computer-based processing layer that bridges operational data and environmental data, transforming raw data into actionable predictive maintenance insights. This intermediary layer simplifies the complexity of integrating multiple data sources by providing a standardized processing interface that enhances predictive accuracy without proportionally increasing operational complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Duration of action of stationary object

If comprehensive maintenance planning is implemented, then system operational lifespan is extended, but maintenance management complexity increases

Engineering Contradiction:

Improveoperational lifespanVSAvoidmaintenance management complexity

Core Design Contradiction:

Duration of action of stationary objectVSDevice complexity

Solution Approach 1:

The patent implements preliminary action by using predictive analytics to identify potential maintenance needs before they manifest as actual problems. The system analyzes operational and environmental data to forecast when maintenance will be required, allowing planners to schedule maintenance activities in advance. This approach extends operational lifespan by preventing failures while simplifying maintenance management through proactive rather than reactive planning.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system establishes a feedback loop where maintenance outcomes are continuously monitored and fed back into the predictive model. This feedback mechanism refines the accuracy of maintenance predictions over time, extending operational lifespan through increasingly accurate predictions while reducing maintenance management complexity by learning from past performance data and optimizing future maintenance schedules.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250044761A1Method for predicting and planning renewable energy maintenance and sustainment activities

Publication Date: 2025.02.06 60 HERTZ INC

AI summary

The technology leverages data sources into an insight generation system to generate a recommendation for a renewable energy asset. The technology combines historical operational data and real-time operational data associated with the renewable energy assets and incorporates historical environmental data and real-time environmental data to include forecasts of weather activity. An insight generation engine ingests the combined and incorporated data to generate an insight that enables data-driven decisions related to operation and sustainment of a resource associated with the renewable energy asset. The insight is associated with optimization, emplacement, or substantiality of the resource.