DERMS

Ingests high-frequency telemetry from thousands of heterogeneous behind-the-meter (BTM) assets. A DERMS normalizes disparate protocols like IEEE 2030.5, OpenADR, and Modbus into a unified data model.

• Polls inverters, batteries, and EV chargers at sub-second intervals
• Maintains a dynamic registry of asset availability and state of charge
• Provides a real-time digital twin of the distributed fleet for operators

Solves complex optimization problems to disaggregate a single grid service request into thousands of individual device setpoints. The engine respects local constraints to prevent asset damage or customer comfort violations.

• Models locational marginal price (LMP) and nodal congestion
• Enforces transformer loading limits and voltage boundaries
• Utilizes mixed-integer linear programming for optimal power flow

Enables a single asset to participate in multiple markets simultaneously by prioritizing revenue streams. A battery can provide frequency regulation while reserving capacity for peak shaving.

• Co-optimizes bids across wholesale energy, ancillary services, and local capacity markets
• Dynamically allocates capacity based on real-time pricing signals
• Maximizes net revenue per asset through stochastic forecasting

Executes autonomous control loops that respond to grid instability in milliseconds without human intervention. This is critical for fast frequency response and synthetic inertia.

• Responds to grid stress signals and under-frequency events autonomously
• Provides volt-VAR optimization by modulating reactive power from smart inverters
• Enables seamless microgrid islanding and black start coordination

Calculates the precise load modification delivered by an aggregated fleet against a statistically rigorous customer baseline load (CBL). This ensures financial settlement integrity.

• Applies interval-meter analytics to quantify actual performance
• Detects non-compliance and asset drift in real-time
• Generates audit-ready reports for settlement engines and market operators

Protects the bidirectional command and control infrastructure from intrusion. A DERMS enforces strict authentication on every connected intelligent electronic device.

• Implements role-based access control and PKI certificate management
• Monitors for SCADA anomaly detection and command injection attempts
• Ensures data integrity across public internet and cellular backhaul links

A cloud-based aggregation of decentralized energy resources—such as batteries, EVs, and controllable loads—coordinated to provide grid services equivalent to a traditional power plant. A DERMS provides the real-time control fabric for a VPP.

• Aggregates hundreds to thousands of individual assets
• Bids capacity into wholesale energy and ancillary service markets
• Relies on DERMS for telemetry, forecasting, and dispatch

A standard communication protocol for smart grid applications, commonly used to manage DERs and enable secure demand response interactions via internet protocols. It defines the application-layer messaging between a utility server and a client device.

• Supports function sets for pricing, metering, and DER control
• Uses RESTful architecture over TCP/IP
• Mandated by California Rule 21 for smart inverter communications

The process of combining numerous small-scale energy assets into a single, controllable virtual resource large enough to participate in wholesale energy markets. A DERMS performs the mathematical optimization to aggregate heterogeneous assets with different ramp rates and availability.

• Handles behind-the-meter (BTM) assets invisible to the operator
• Manages diversity factor to ensure reliable aggregate response
• Enables participation in frequency regulation and spinning reserve markets

An open, standardized communication data model and protocol (IEC 62746-10) used to exchange demand response and price signals between utilities and end-user energy management systems. A DERMS often implements an OpenADR Virtual End Node (VEN) to receive grid signals.

• Supports both price-based and reliability-based events
• Enables standardized communication across vendor platforms
• Provides reporting mechanisms for measurement and verification

A statistical calculation of what a customer's energy consumption would have been in the absence of a demand response event, used to measure performance. The DERMS must calculate CBL with high precision because financial settlement depends on the delta between baseline and actual load.

• Common methods include 10-day averaging and regression models
• Adjusted for weather and day-type variations
• Accuracy directly impacts settlement engine payouts

A building optimized to use smart technologies and distributed energy resources to provide demand flexibility while maintaining occupant comfort and utility. A DERMS treats a GEB as a dispatchable node capable of load shifting and peak shaving.

• Integrates HVAC, lighting, and battery storage controls
• Responds to dynamic pricing signals and grid stress events
• Aligns with Load Flexibility strategies without compromising operations