Background

In order to improve the resiliency of the electric grid and support increasing demand for distributed photovoltaics (PV), utilities are seeking to establish greater real‑time situational awareness of distribution circuits. On circuits with high penetration of PV, power backfeeds from residential customers to the grid during the daytime. This can introduce issues such as overvoltage, violations of thermal limits on the electrical lines, and at a system level, the need to provide adequate operational reserves to protect against transient cloud coverage. Utilities wish to control PV and other distributed energy resources (DERs) such as electric vehicles and smart appliances to mitigate the natural variability of PV, effectively rerouting power and shifting energy to avoid expensive upgrades to wires and transformers.

Existing commercial solutions provide centralized, aggregated control of PV and DERs that is not well‑suited to address localized conditions at the distribution level. Data acquisition solutions such as smart meters provide local information but are expensive to deploy widely. Also, due to communication limitations, data is reported too slowly to address transient conditions. To reduce cost and increase coverage, utilities are looking at distribution service transformers as a key location for data acquisition that is near the edge of the grid but serves several customers at once. The annual market for distribution transformer power monitors (DTMs) in the US is estimated at $755 million in the near termⁱ. Yet the features of existing DTMs are limited to basic electrical measurements reported every few minutes. True power quality meters are much more expensive and still require communications equipment with a commercial data plan, a power supply, and a weather‑resistant enclosure.

To prepare for the oncoming DER revolution, utilities need a platform that merges distributed measurement, real‑time analytics, and controls. Such a platform could vastly improve situational awareness; address PV and load variability at a local level while also providing system‑level ancillary services such as operating reserves; provide no‑wires alternatives; improve resiliency, power quality, and the efficacy of conservation voltage reduction (CVR); and serve as a gateway for reliable communications with DERs. Our technology provides the foundation for such a platform.

Technology Overview

Researchers at the University of Hawaii’s Hawaii Natural Energy Institute (HNEI) have developed ARGEMS: Advanced Real‑time Grid Energy Monitor System. The system includes an advanced DTM that provides power quality measurements and can also serve as a communications gateway and a controller for PV and other DERs ‑ all at a price point that competes with traditional DTMs. The device is extremely flexible, with powerful computational resources to enable real‑time analytics including harmonic identification. The hardware is now well‑refined, and HNEI is partnering with other organizations to further develop advanced functions and services in software.

Benefits

Higher penetration of renewable energy

Tighter analysis of hosting capacity (planning)
Reduced PV and load uncertainty for tighter reserves (operations)
Fast, localized sources of ancillary services (operations)

Greater grid resiliency

DER control to assist black start
Build out secure, resilient, and utility-owned comms network

Lower cost of service

Deferred grid investment (non-wires alternatives)
Detection of non-technical losses
Greater potential for conservation voltage reduction (CVR)
Data and tools to optimize battery energy storage systems (BESS)

Higher quality of service

Earlier, more precise outage reports
Detection of voltage flicker and harmonic distortion
Coordinated voltage control via DER inverters

Features

High Performance:

Uses the latest smart meter, GPS, communications, and computing technology
Numerous metrics including voltage and current (total and fundamental), total harmonic distortion, power (total and fundamental—real and reactive components), and frequency
Powerful hybrid computing platform for real-time signal processing and high-level analytics: field programmable gate array (FPGA) with one or more 160 MHz 32-bit soft-core processors (configurable) and a 1.5 GHz 64-bit quad core CPU
Website with device status, interactive plotting/visualization, and application program interfaces
Reporting of root-mean-square (RMS) measurements as fast as 1⁄60 s or single cycle
Hardware ready for waveform capture (32 kHz internal sampling, up to 150 Mbps upload)**
Low latency (<250 ms typical, including communication to server)
Accurate GPS time reference (±20 ns), ready for phase measurement unit (PMU) functions*

Flexible:

Split single-phase or three-phase voltage and current measurement up to 277 V line to neutral, with optional neutral current measurement
Supports Rogowski and traditional current transducers (CTs)
Multiple communication options: LTE wireless, WiFi, Gigabit Ethernet, and XBee mesh
Modular hardware design with expansion slot for custom interfaces
Utilizes pub/sub messaging (AMQP and MQTT) and modular software framework to enable low-latency, real-time functions such as DER controls
Over-the-air configuration and programming*
Electrically isolated for lab use

Robust:

Fully weatherized with IP67-rated enclosure and connectors
Back-up power supply to record grid blackout events
Data retention and timestamping at multiple levels (device, gateway, and server) to mitigate intermittent communications; automatic upload when communications are restored
Capability for Transport Layer Security (TLS) and AES encryption*

Low cost:

Wireless mesh networking to allow 10–20 devices per commercial wireless data line
Communications and power supplies included
Expected to achieve a retail prices less than $800 per unit (CTs included) and less than $10/mo/unit operational cost

Easy to install:

Compact enclosure (6” ⨉ 5” ⨉ 4”) with magnet or screw mounts
Removable connectors for each phase / transformer lug
Internal antennas

*Coming soon (currently in software development)

** Future software development

[i] Greentech Media Research, “Transformer Monitoring Markets, 2013-2020: Technologies, Forecasts and Leading Vendors,” Last modified February, 2013. https://www.greentechmedia.com/research/report/transformer-monitoring-markets-2013-2020

Distribution Grid Power Monitor

IP Status

Seeking