EnersynQ is energy systems intelligence for power-constrained growth: analytical methods, models, and case studies examining where large electric demand emerges, which physical asset becomes the first binding constraint, and what technical or operational changes can improve delivery readiness.

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Applied models and methods

EV-fleet transformer model

Evaluates unmanaged charging, thermally managed charging, and storage-backed coordination against transformer loading, hot-spot temperature, and insulation aging.

Power Readiness method

Examines power availability, binding constraints, infrastructure timing, operating flexibility, and delivery risk for concentrated new loads.

Flexible-load coordination

Studies how scheduling, curtailment, and storage can be coordinated against the first binding physical constraint rather than energy price alone.

Michigan and MISO analysis

Regional analysis in development using verified public data on large-load growth, grid constraints, and time-to-power conditions.

Institutional and technical context

FERC large-load proceedings · MISO regional planning · DOE and Lawrence Berkeley National Laboratory load-growth analysis · IEEE transformer-loading standards

Publications and professional service

  • Accepted · NAPS

    Coordinating Electric Vehicle Fleet Charging Against Distribution Transformer Thermal Limits

    A constraint-first study comparing unmanaged charging, thermally managed charging, and storage-backed coordination under identical delivered energy.

  • Peer Reviewer · NAPS

    Reviewed technical-paper submissions for the North American Power Symposium.

  • M.S. thesis

    Smart Grid Technologies for Efficiency Improvement of Integrated Industrial Electric System

    University of New Orleans.