See how we stand out from traditional SCADA/EMS systems and Asset Management systems.
The Intelligence Layer for Modern Utility Management
YDURA™® — Empowering Utilities with Intelligence. Sustainable, Efficient, and Future-Ready.
It is the first framework in the region to explicitly link "Resilience" (N-1 security) with "Sustainability" (Carbon-aware dispatching) within a single functional layer.
The framework is built on a microservices architecture, allowing utilities to deploy specific modules (e.g., the Digital Logbook or the Unit Commitment engine) independently and scale as their digital maturity grows.
The YDURA™® is founded on several core principles that guide its design, implementation, and operational effectiveness:
The system's architecture is designed for seamless integration with emerging technologies and regulatory requirements. This flexibility allows utilities to adapt quickly to market changes.
By addressing both real-time control and back-office functions, EVLDI™ fosters a more holistic approach to utility management, enhancing overall performance and resilience.
The implementation of the YDURA™® system is expected to yield substantial benefits and returns across multiple dimensions:
YDURA™® holds significant importance in addressing the myriad challenges that utilities face today:
YDURA™ leverages advanced machine learning to predict, optimize, and learn.
Core Engine
Utilizing machine learning algorithms, the system analyzes historical and real-time data to identify patterns and predict equipment failures before they occur.
This proactive approach allows utilities to schedule maintenance activities efficiently, minimizing unplanned outages and optimizing resource use.
Optimization
AI-driven optimization algorithms evaluate multiple variables to recommend the best operational strategies.
These can include optimal resource allocation, scheduling, and load management, thereby improving overall operational efficiency.
Machine learning models analyze vast datasets, including weather patterns and historical consumption trends, to generate highly accurate demand forecasts.
AI technologies identify and flag unusual patterns in operational data, enabling quicker responses to potential issues and enhancing safety.
The system continuously learns from new data, refining its algorithms to improve accuracy and effectiveness over time.