N-2NSPI (NSEB) RIR 1 to 15 - Redacted
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17 (b) The project will evaluate the extent to which DI Apps can improve operations and customer 18 service by enhancing visibility into distribution system conditions and providing actionable 19 insights. Specifically, the project will ev...
AI summary The project aims to evaluate the capabilities of DI Apps in improving outage management, identifying revenue loss from energy theft, and automating processes for asset and safety-related issues, with the goal of enhancing operational efficiency and customer experience.
Advanced Temperature Monitoring Uses high-resolution temperature readings and peer-to-peer communication to detect meter socket problems before they create a safety hazard or interrupt service
AI summary Advanced Temperature Monitoring uses high-resolution temperature readings and peer-to-peer communication to detect meter socket problems before they create a safety hazard or interrupt service.
High Impedance Detection Detects and locates poor electrical connections in low voltage secondaries before they create a safety hazard or interrupt service
AI summary This section discusses the High Impedance Detection system, which identifies and locates poor electrical connections in low voltage secondaries to prevent safety hazards and service interruptions.
Challenges - May not have the field resources to proactively address issues (process is currently customer initiated) - Low excitement from business stakeholders Future State: DI data autonomously identifies poor electrical connections and...
AI summary The current process for addressing electrical connection issues is customer-initiated, leading to challenges such as lack of field resources and low stakeholder engagement. The future state envisions using DI data to autonomously identify and dispatch resources for poor electrical connections.
Location Awareness Distributed Intelligence Effectively using your smart meters to support monitoring and control of your secondary distribution requires knowing exactly where they are in your distribution network. One of the greatest chal...
AI summary Location Awareness is a new capability in Itron's distributed intelligence platforms that allows smart meters to continuously know their electrical connectivity in the distribution grid, improving grid operations and enabling new smart grid applications without relying on GIS or communication network topology.
Grid Edge Intelligence Base Requirements A Grid Edge platform should provide: Every meter is a grid condition-sensing waveform analyzer Distributed intelligence extends the value of every meter High resolution processing locally pushed to...
AI summary The document outlines the base requirements for a Grid Edge Intelligence platform, emphasizing the need for every meter to function as a grid condition-sensing waveform analyzer, distributed intelligence, high-resolution local processing, peer-to-peer communications, and support for multiple communication networks.
Monitoring and Managing the Low Voltage Grid DI Integration with Grid Management CI C0068719 NSEB IR-2 Attachment 3 Page 6 of 42
AI summary This document discusses the integration of Demand Intelligence (DI) with grid management in the context of monitoring and managing the low voltage grid.
High Impedance Detection – Field Examples ©2024 ITRON CONFIDENTIAL PROPRIETARY HOME CI C0068719 NSEB IR-2 Attachment 3 Page 11 of 42
AI summary The document discusses field examples related to high impedance detection, with a focus on technologies and systems used in the energy sector. It includes references to advanced monitoring systems and is associated with Nova Scotia Power Inc. and the Nova Scotia Energy Board.
Distribution Operations - Trouble Dept, Risk & Reliability Managers Unpredictable and unplanned outages cause too much spending crew overtime, and it's difficult to plan effectively. Customer satisfaction is impacted. CI C0068719 NSEB IR-2...
AI summary Unpredictable and unplanned outages lead to increased overtime costs and difficulties in planning, negatively affecting customer satisfaction.
Location Awareness Production - » Function: Determines connectivity of meter to transformers, phases, and feeders utilizing PLC and RF peer-to-peer - » Benefits: Maintain up-to-date grid topology awareness for DI and back-office utility sy...
AI summary Location Awareness functionality determines the connectivity of meters to transformers, phases, and feeders using PLC and RF peer-to-peer communication. Benefits include maintaining grid topology awareness, advanced transformer management, storm simulation, DER analytics, and accurate asset loading and planning.
Distribution Operations You want to prevent transformer overloading – especially transformer failure or fuse operation (e.g., 200% overload). However, you can't take real-time actions without knowing the real-time loading. CI C0068719 NSEB...
AI summary The text discusses the importance of preventing transformer overloading and failure by having real-time data on transformer loading, as real-time actions are necessary to address issues like 200% overload.
» Benefits: - Preserve transformer lifetime - Reduce unplanned outages - Reduced network traffic through use of spokesmeters - More effective programs (e.g. VVO/CVR) or better resolution control (e.g. load flow)
AI summary The benefits outlined include preserving transformer lifetime, reducing unplanned outages, decreasing network traffic with spokesmeters, and enabling more effective programs like VVO/CVR and better resolution control such as load flow.
» Benefits: - EV models for 'offline' applications such as in utility planning and EV program customer engagements - Inputs for real-time controls (e.g. DERMS, ADMS) for applications such as distribution transformer protection and Volt/Var...
AI summary The text outlines benefits of EV models for offline utility planning and customer engagement, as well as their use in real-time controls for distribution transformer protection and Volt/Var Optimization.
Distribution System Operations Due to resource constraints (e.g., loss of unit, extreme weather), you want to avoid automatic load shedding or worse. You need to prepare to shed load to save portions of the system, but need a fast, reliabl...
AI summary The document discusses the need for a fast, reliable, and flexible method to shed load during system emergencies due to resource constraints such as loss of units or extreme weather, ensuring secure system operations.
» Benefits: - Detect wide variety of anomalies using highfidelity waveform data from a greater density of meters across the grid - Example grid anomalies include vegetation contacts, wildfires, protection device failures, grid equipment is...
AI summary The benefits section highlights the ability to detect various grid anomalies using high-fidelity waveform data from a greater density of meters. Examples include vegetation contacts, wildfires, protection device failures, grid equipment issues, and power quality issues.
Example 1: Hurricane Ian Voltage Anomaly Event Detecting grid events using high-fidelity data CI C0068719 NSEB IR-2 Attachment 3 Page 33 of 42
AI summary This section discusses the detection of grid events using high-fidelity data, specifically referencing an example involving Hurricane Ian and a voltage anomaly event.
Example 2: Capacitor Bank Switching Triggered Harmonics Detecting grid events and equipment health using high-fidelity data CI C0068719 NSEB IR-2 Attachment 3 Page 34 of 42
AI summary This example discusses the detection of grid events and equipment health using high-fidelity data, specifically focusing on capacitor bank switching triggered harmonics.
» Benefits: - Input to solar generation models for more accurate planning studies - Protection of distribution transformers in conjunction with real-time control systems
AI summary The benefits discussed include improved accuracy in solar generation planning studies and protection of distribution transformers through real-time control systems.
Distribution Operations Your group receives several complaints a month where you have to roll a truck to install a power quality meter, hoping to catch the power quality issues that they were complaining about. You wish you didn't have to...
AI summary The group receives monthly complaints requiring truck rolls to install power quality meters to address customer-reported issues, expressing a desire to reduce the frequency of such field visits.
HW4.1+ mixed w/ HW4.0 HW4.1+ HW4.1+ GenX HW4.2+ Existing Apps 2025 2026+ Deployed in-field (scaled or pilot) Under Development / Committed Strategic Initiatives / Directional • Advanced Temperature Monitoring • High Impedance Detection • M...
AI summary The document outlines existing and planned advanced applications for grid management, including technologies like Advanced Temperature Monitoring, Voltage Bellwether, and EV Awareness, with deployment timelines extending into 2026 and beyond. It highlights initiatives such as Solar Awareness, Virtual RTU, and Advanced Outage Awareness as part of strategic directions for future implementation.
Description - » LUMA Energy operates Puerto Rico's transmission & distribution system (since 2021) within an inherited grid marked by aging equipment, vegetation risks, storm exposure and funding constraints. - » Instead of waiting for the...
AI summary LUMA Energy is managing Puerto Rico's transmission and distribution system, facing challenges from aging infrastructure and environmental risks. They have begun deploying the High Impedance Detection (HID) DI App in San Juan, identifying issues such as high impedance levels on a transformer.
CI C0068719 - IT - Distributed Intelligence Apps (NSEB M13014) NSPI Responses to NSEB Information Requests 1 Request IR-13: Advanced Transformer Load & Voltage Monitoring Distribution Grid Situational Awareness Provides near-real time moni...
AI summary The document discusses the limitations of existing monitoring equipment in providing near-real-time visibility into transformer loading and voltage conditions. It highlights the need for improved grid-edge visibility to support operational decision-making and future ADMS capabilities, but notes that current AMI data is insufficient for this purpose.