The Distribution Grid, a volatile, dynamic and expansive network of interconnected assets spanning between substations and endpoint meters, is plagued with Energy Loss and Inefficiencies. GRID20/20's OptaNODE™ intra-grid sensors help to remedy this costly reality.
Distribution Grid Realities Limited Visibility
Utilities are blind to intra-grid conditions between substations and endpoint meters. Reacting to asset failures and customer complaints versus proactively managing the intra-grid has been the industry’s approach heretofore. Even with substantial AMI/AMR deployment, over 199.1 Billion kWh of Loss, representing over $20.7 Billion, was unnecessarily subsidized by US rate payers in 2014, and continues annually. All distribution grids in the world share this similar, energy inefficiency condition.
Limited visibility into the Distribution Grid is the root cause for many problematic conditions, and results in reactionary and costly grid management, negatively impacting rates and customers.
Illegal pre-meter taps
Wrong multiplier settings
Reverse energy flows
Accelerated Loss of Life
‘Hard to read’ meters
GIS Mapping Errors
GRID20/20's OptaNODE™ Distribution Transformer Monitor devices address the utility’s needs with rich functionality, accurate measurement, rapid deployment and ubiquitous communications capability.
The OptaNODE™ solution delivers 20/20 vision into the Distribution Grid
One Solution Multiple Value Propositions
Cost-Effective OptaNODE™ intra-grid sensors provide a vast array of grid management improvements for global utility providers – simultaneously shrinking OpEx, improving CapEX ROI, increasing metered revenues, reducing GHG, embracing DER/DG/EV/CVR, and lowering rate payer costs.
There is no algorithm substitute for the accurate, timely, and unique data provided by intra-grid sensors. GRID20/20 provides a vast, growing list of applications for utilities.
✓ Intra-Grid Loss
Technical Loss due to improper Transformer Sizing, Incorrect Tap settings, Voltage Imbalance, etc.., and Non-Technical Loss due to Power Theft, Incorrect Multipliers, and Excessive Energy delivery cause power rates to unnecessarily increase. OptaNODE™ sensors reveal costly Intra-grid Loss.
✓ DER/DG Integration
DER/DG can create grid de-stabilization, and safety concerns. By monitoring Voltage Fluctuations & Reverse Power Flows, utilities can safely manage their grid and effectively select distributed storage locations. OptaNODE™ sensors enhance DER/DG Integration.
✓ Voltage Optimization
Timely, accurate intra-grid Voltage Readings enhance CVR to reduce peak demand costs, and improve proper energy delivery levels to cut power costs. Our collaboration with Dominion Voltage, Inc. (DVI) helps utilities to apply CVR. OptaNODE™ sensors enhance Voltage Optimization. Learn more »
✓ Theft Detection
Power Thieves have learned that stealing power in front of the meter is undetectable by utilities, allowing thieves to steal over $6 Billion from US grids in 2014. Power Theft has INCREASED since AMI/AMR deployment. OptaNODE™ sensors reveal costly Power Theft.
✓ Metered Revenues
US loss exceeded $20.7 Billion in 2014. It is estimated that over 50% of loss can be identified and remediated. Taking a proactive stance to loss will help rate payers and utilities simultaneously. OptaNODE™ sensors yield Increased Metered Revenues.
✓ Outage Detection
OptaNODE™ DTM devices can notify operators of power interruptions, enabling faster location of outages, and accelerated restoration. Faster Restoration improves SAIDI ratings, and resumes metered revenues more quickly.
✓ Asset Management
Failing or improperly sized Transformers lead to Power Outages, and Decreased Revenue. By revealing stressed assets, Preventive Maintenance is enabled. This maximizes CapEx, Reduces Trouble Calls and improves SAIFI ratings. OptaNODE™ sensors enable proactive Asset Management.
✓ Automated Alerts
Using technology to monitor the grid is efficient, and lowers Operating Costs. Programmable Alarms permit utilities to select key intra-grid Tolerances, then be notified when undesirable conditions occur. This enables “Hands-Free” grid management capabilities. OptaNODE™ sensors provide Automated Alerts.
✓ Meter Inaccuracies
GIS Mapping Errors, Pre-Meter Taps, and Incorrect Multipliers are identified by reconciling Transformer data with downstream Meters. AMI, AMR, and mechanical meters are subject to these Revenue-Reducing impacts. OptaNODE™ sensors reveal costly Meter Inaccuracies.
✓ Greenhouse Gas Reduction
Over 199.1 Billion kWh ‘leaked’ from the US grid in 2014. This loss represented over 106.5 Million Metric Tons of CO2 Emissions. By locating Loss locations inside the grid, up to 50+ Million Metric Tons of CO2 emissions can be eliminated annually. OptaNODE™ sensors enable GHG Reduction.
✓ Electric Vehicles
To reduce CO2 emissions and dependency upon petroleum, global penetration of EVs increases annually. Each EV requires a charging station which demands significant electricity. This unplanned demand can seriously overburden transformers. OptaNODE™ sensors monitor EV impacts on the grid.
✓ Smart Grid Realization
Official Loss data proves that AMI/AMR alone cannot create a smart grid. The intra-grid represents the most volatile, vulnerable and dynamic segment. Utilities are blind to today’s intra-grid conditions. Cost-effective intra-grid sensors remedy the ‘missing link’. OptaNODE™ Sensors enable Smart Grid Realization.
AMI & AMR Synergies
Meter data is subject to substantial inaccuracies due to decalibration, improper GIS asset mapping, and pre-meter theft taps. Creating necessary reconciliation points via OptaNODE™ DTM intra-grid sensors remedies this problem.
Utilities with deployed AMI are now discovering that power theft is increasing, and AMI cannot effectively report intra-grid data. AMI based Analytics lack the necessary accuracy and timely information required by utilities and deliver inaccurate predictions based on:
Assumptions & Estimations
Incomplete & Antiquated Information
The OptaNODE™ Solution is required to enhance AMI data, and achieve a genuine, comprehensive Smart Grid.
GIS Mapping and Meter-to-Transformer Association Errors Identified