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Method for Estimating the Operating Regime of a System Based on Its Electrical Consumption Signature

Summary

Profile Type
  • Technology offer
POD Reference
TOES20250318020
Term of Validity
18 March 2025 - 18 March 2026
Company's Country
  • Spain
Type of partnership
  • Commercial agreement with technical assistance
Targeted Countries
  • All countries
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General information

Short Summary
A Spanish research group has developed a novel method for estimating the operating regime of an electrically powered system using its electrical consumption signature. AI models are used to analyse voltage, current, and phase shift data, improving system state identification without relying on power measurements. The technology enables more efficient monitoring and predictive maintenance in industrial and energy management applications. A licensee is sought to develop and market the invention.
Full Description
The identification of operating states in electrically powered systems traditionally relies on power consumption analysis. However, conventional methods, such as Non-Intrusive Load Monitoring (NILM), often face challenges in distinguishing overlapping loads and require extensive labelled datasets. Existing solutions also struggle to provide real-time, high-accuracy state detection in complex industrial environments.
Researchers from two Spanish universities have solved these inconveniences by developing a method for estimating the operating regime of a system based on its electrical consumption signature. Unlike traditional approaches, this method leverages artificial intelligence models that analyse voltage, current, and phase shift data across multiple dimensions. This enables accurate state identification without relying on direct power measurements, leading to enhanced monitoring and predictive maintenance capabilities.
The present invention is applicable in those industries where accurate system state monitoring is crucial, such as manufacturing, energy management, and predictive maintenance. It can be integrated into industrial plants, smart grids, and automated systems to optimize operational efficiency and reduce unexpected downtimes.
The IPR owners would like to reach license agreements with companies operating in such fields, so they can develop applications of the technology.
Advantages and Innovations
• Eliminates the need for direct power measurements, enhancing flexibility and applicability.
• Utilizes artificial intelligence for precise system state identification in real-time.
• Enables predictive maintenance and anomaly detection, reducing operational costs.
• Applicable to various industrial settings, improving equipment efficiency and reliability.
• Offers a scalable solution that can be integrated into existing monitoring infrastructures.
Stage of Development
  • Available for demonstration
Sustainable Development Goals
  • Goal 9: Industry, Innovation and Infrastructure
  • Goal 7: Affordable and Clean Energy
IPR status
  • IPR applied but not yet granted
IPR notes
Spanish Patent applied.

Partner Sought

Expected Role of a Partner
Licensee of the technology to develop and market the invention.
Type and Size of Partner
  • Big company
  • SME <=10
  • SME 11-49
  • SME 50 - 249
Type of partnership
  • Commercial agreement with technical assistance

Dissemination

Technology keywords
  • 01003003 - Artificial Intelligence (AI)
  • 004006001 - Energy management
  • 02003001 - Process automation
  • 09001009 - Sensor Technology related to measurements
  • 01003010 - Databases, Database Management, Data Mining
Market keywords
  • 08002003 - Process control equipment and systems
  • 08002001 - Energy management
  • 09003001 - Engineering services
  • 06006002 - Metering and monitoring
  • 09008001 - Electric companies
Sector Groups Involved
  • Renewable Energy
Targeted countries
  • All countries