3.2.3 Monitoring technologies

3.2.3 Monitoring technologies

Smart meters

Smart meters are one of the monitoring technologies with the most immediate potential for improvements to network visibility bringing benefits to both customers and network operators. They can facilitate increased flexibility of tariff options by allowing implementation of cost-reflective pricing that better reflects the value of electricity supplied, when it is supplied, and reward consumers for changing their consumption. Smart meters provide customers with:

• More granular information and price signals to enable them to actively manage their energy profile. • Different tariff structures which provide the opportunity to implement more cost reflective pricing. • Access to new products and services e.g., live data monitoring, and load management. • Better services from retailers and network providers.

At the same time, network operators can use data from smart meters to improve visibility of their networks. Without smart meter data, network providers today rely on manually obtained data to plan the network, which leads to inefficient outcomes and ultimately higher costs to customers. Indeed, limited access to real-time data obliges network providers to take more conservative approaches, which in turn, reduces the hosting capacity of the network, and consequently customers likely experience significantly more solar constraints than necessary.

A review conducted by Australian Energy Market Commission (AEMC) in December 2020 concluded that the penetration of smart meters has increased in the past 2 years, reaching 1.04 million (17.4% penetration) in all states excluding Victoria. The total number of smart meters installed in each state is illustrated in figure 1. NSW has highest number of smart meters installed; on the other hand, Tasmania has the highest penetration reaching 20%.

Figure 3-1 - Smart meter penetration in each state [4]

Furthermore, smart meter penetration differs between DNSPs. As shown in figure 2, compared to other DNSPs, Ausgrid and Ergon have the lowest percentage of smart meters in their network. It is essential to understand the drivers for smart meter installation. According to AER, between 2019-2020 it was found that there are four reasons for installing smart meters. Customer requests is the key driver followed by new connection, with new meter deployment (retailer-led) being the least category.

Figure 3-2- Percentage of smart meter penetration in each DNSP [4]

Apart from Australia, smart meters are being deployed worldwide including in the United Kingdom, European Union (EU), New Zealand, Canada, China, and parts of America. The current state of the market for smart meters is reported in [4] as follows:

• United Kingdom: one of the key drivers for smart meter roll out is providing flexibility for ways gas and electricity customers can participate in the market.

• European Union (EU): finds in necessary to deploy smart meters to support their smart gid development. It has high penetration percentage of 99 and 98% in Italy and Finland, respectively. • New Zealand: roll out depends on customer benefits, primarily increased accuracy in billing and forecasting. As of 30 September 2020, 89% of residential connections have been installed with smart meters.

• Canada: smart meters are viewed as primary components in renewable investment, increase in decentralised renewable energy and smart grid technologies deployment.

With 82% of the electricity meters being smart meters.

Phasor Measurement Units (PMUs)

Phasor Measurement Units (PMUs) are a promising metering technology for power networks. In simple words, a PMU is a measurement device, capable of measuring the synchronised voltage and current phasors in power systems. A distinct peculiarity of PMUs over other metering devices used in power networks is that the measurements are timestamped and synchronised to the coordinated universal time reference. Having a common time-reference allows PMUs to define “phasors” and compare them in different locations in a power grid, because the instantaneous phase of a given stationary sinusoidal signal cannot be defined unless it is referenced to a common value. Therefore, “synchrophasors”, which are phasors calculated at different locations all using a common time reference, can be obtained from PMUs. Availability of the synchrophasors in power networks can provide frequent and accurate snapshots of the status of the electrical grid, enabling development of advanced processes such as state estimation, which is crucial for network operation.

Traditionally, state estimation has been performed by the supervisory control and data acquisition (SCADA) system with a refresh rate in the range of few tens of seconds (or even minutes). Having high refresh rate synchrophasors can significantly improve classical state estimation processes, enabling the implementation of novel real-time management, control, and protection functionalities leading to optimal, affordable and efficient operation of the electrical grid, enhancement of the security of supply, and prevention of blackouts.

PMUs were originally studied and deployed in large transmission networks, and one of their primary applications have been in the context of Wide Area Measurement System (WAMS). In this context, PMUs have various applications such as power swing detection, stability enhancement, real-time congestion management, disturbance management, and adaptive protection.

The use of PMUs and WAMS in distribution networks is becoming an emerging research topic. Compared to transmission networks, the phase angle displacements between grid nodes in distribution systems are extremely small. As a consequence, PMUs dedicated to distribution networks require higher measurement accuracy. In addition, measurements in distribution networks are more contaminated with measurement noise, harmonics, and non-predictable dynamics due to the presence of DERs and power electronic converters. This measurement noise makes it challenging to provide high accuracy synchrophasor

estimation in the presence of interfering signals. A further challenge is related to the cost of PMUs, which can limit wide roll out of these advanced monitoring devices.

Having said that, compared to legacy technologies that are designed to monitor specific grid conditions and limited applications or uses, PMUs collect a wide set of grid condition data from many locations, which can be used for a broader and evolving set of use cases and applications. This enables development of advanced applications including [5]:

• State or condition monitoring of the distribution system. • Monitoring and analysis of customer-owned, behind-the-meter distributed generation and energy storage devices, enabling better forecasting and integration of those devices.

• Measurement and verification of customers’ energy efficiency, demand response and load management activities (subject to appropriate privacy protections). • Monitoring and analysis of significant end-user loads (for example, clusters of electric vehicle chargers). • Identification of asset and equipment problems, including detection and advance warning of equipment operational issues and failures. • Fault detection (including high-impedance faults), location and event forensics. • Anomaly detection, including potential cyber-intrusions. • Detection of previously unknown dynamic events (for example, control instabilities or oscillations) that are not recognizable with traditional monitoring.

A summary of PMU data applications and the data requirement is presented in Tables 3-1 and 3-2 [6]

Table 3-1- Applications using synchrophasors and the data requirement.

Application

Voltage profile and variability

Awareness of real-time loads

Measurement Quantities

Voltage magnitudes critical, voltage phase angle useful for tap change detection

Current magnitudes very useful, voltage phase angle can be proxy for current if network impedances are

Time Resolution Accuracy Latency & Continuity

1 sec or better resolution is useful, synchronisation between & among measurement locations essential 1 cycle or better resolution reveals transient behaviours, full time domain characterisation to 30kHz sampling of Absolute accuracy of 0.5% is adequate Retain complete history

Absolute 0.5% error likely adequate Operationally relevant latency on the order of 1 sec

Outage management

System frequency & oscillation detection known, current phase angle useful for P,Q decomposition & reverse power flow Voltage and current magnitudes Voltage phase angle essential

Island detection; microgrid islanding & resynchronisatio n Distribution state estimation and topology detection

Topology detection based on source impedance Voltage phase angle essential

Voltage phasors, sensitive to placement and number of sensors, network model and load data important Voltage and current phasors

Phase identification Voltage phase angles essential

Model validation for line segment impedances Voltage & current phasors

DER characterisation, transformer, generator and load models Voltage and current phasors interest to reveal harmonics

1 sec likely adequate 1% error likely adequate 1 sec latency likely adequate

1 cycle or better & synchronisation essential

Change in time, not absolutely accuracy of interest, 1% error adequate of stable 1 cycle or better Insensitive to magnitude error, phase angle error stable to 0.01 Retain complete history, latency requirement may vary, sub-second critical information protection

Continuous monitoring, sub-second latency critical if informing protection

Synchronisation critical

1 Cycle or better & synchronisation critical

1 sec or better for time series approach, synchronisation critical synchronisation critical

1 cycle or better reveals dynamic behaviours: synchronisation between primary & secondary side Absolute accuracy on the order of 0.0001 pu, requires correction for transducer errors Operationally relevant latency on the order of 1sec

Changes in time, not absolute accuracy of interest, 0.5% error adequate if stable Absolute accuracy of phase angle on the order of 1 likely adequate Absolute accuracy of all phasors is limiting factor, as good as 0.0001 pu for shorter segments Change in time, not absolute accuracy of interest, 0.5% error adequate if stable Operationally relevant latency on the order of 1 sec

No particular need for latency or continuity

No particular need for latency or continuity

No particular need for latency or continuity

Event detection and classification Voltage and current magnitudes adequate for most events, phase angles useful of transformer critical 1 cycle or better, synchronisation critical Changes in time, not absolute accuracy of interest, 0.5% error adequate if stable

Fault location Voltage & current phasors 1 cycle or better, synchronisation critical Absolute accuracy of all phasors is limiting factor

Phasor-based control Voltage phasors 1 cycle or better Absolute accuracy critical for steady-state optimisation, but stable errors acceptable for disturbance rejection Continuous monitoring, operationally relevant latency on the order of 1 sec

Continuous monitoring, operationally relevant latency on the order of 1 sec Continuous monitoring, latency critical

Table 3-2- advantages of using high-resolution voltage angle measurements compared to conventional techniques [7]

Application Competing conventional methods Likely advantage of voltage angles Likely technical challenges

Unintentional island detection Automatic Transfer Switch

Oscillation detection

Reverse power flow detection Line sensors, directional relays

Fault location various

Highimpedance fault detection

Topology detection various, difficult

direct SCADA on switches

State estimation computation based on V mag measurements faster, greater sensitivity and selectivity

Unique and crucial

may extrapolate to locations not directly monitored

better accuracy using voltage phasor values

better sensitivity and selectivity using voltage phasor values

fewer measurement points, higher accuracy using timeseries phasor data linear state estimation, higher accuracy communication latency

Potential Transformer and Current Transformer errors

PMU placement

Communication latency

Communication latency

PMU placement

PMU placement

Load and DG characterizati on limited observation with PQ instruments uniquely capture dynamic behaviours data mining, proximity to subject

Other DER and LV Network Visibility Technologies

In light of recent technological advances, several products have been developed for customer and behind-the-meter assets energy monitoring and management. These technological advances including smart inverters, home automation technologies, and integrated energy management components can be utilised at the customer premises or at different locations of the network. They can enhance the network visibility, while enabling customers to manage their electricity consumption and match it with their electricity generation and storage preferences. Increase in deployment of these smart devices enhances grid stability and reliability by enabling real-time action of smart customers in response to grid operator requests (e.g., through demand response). Indeed, these technologies provide information about customer load and DER data, which in turn improves network visibility. In Table 3-3, a list of different technologies that can be used to improve DER and network visibility is provided, in which for each product the main features are highlighted:

Table 3-3- Products that can be utilised for DER and LV network visibility

Product Company Features

The Solar Smart Monitor

Solar analytics Solar Analytics communicates with all inverters through Solar Smart Monitor. Features include 5 Second Live data, 3G/4G multi band communications, measures up to six sub-circuits and provides Class 1 equivalent accuracy. It also collects data from the inverter and inverter consumption meter. Auditor 6M Wattwatchers Provides real-time energy monitor leveraging cellular communications. Up to 6 channels of measurement. Revenue-grade (Class 1 accuracy). Suitable for single, two and three phase applications. Edge’s eSensor EDGE ELECTRONS Edge’s eSensor is an intelligent and compact power quality monitor, which uses software-driven technology for network control.

Droplet switchDin Droplets are generalised distributed energy resource (DER) controllers, which can be used as energy management systems for homes & businesses, battery energy storage system controllers, microgrid controllers, managed DER controllers, AS4755 DRED controllers and DER system aggregators. Each Droplet-equipped site or device can operate autonomously or in coordination with other Droplets via Stormcloud, our cloud-based management platform. HomeKit GOODWE GoodWe HomeKit is a solution designed to monitor load energy consumption in real time, 24 hours a day. It

consists of a smart meter and a Wi-Fi / LAN communication module. It can be applied to gridconnected systems with inverters of any brand or even systems without PV and it is a key component in keeping load consumption records. With 60-second update frequency, data is transmitted by Wi-Fi / LAN and stored on the cloud.

blue’Log XSeries meteocontrol The blue’Log X-Series records all relevant system data, provides various interfaces and functionality for power plant control and thus enables grid-compliant feed-in for PV systems.

Envoy ENPHASE

The Envoy delivers performance data from microinverters to the Web and carries system updates from the Web to microinverters. It provides the real-time, module-level performance data to monitor the system or fleet from any web-connected device. GridEyE DepSys A platform combining hardware and software components to produce and leverage real-time data. GridEye helps to operate, monitor, analyse, automate and optimise any power distribution grid. GridGem ArgandSolutions An integrated control and monitoring solution to solve the problems faced within the renewables, energy storage and / or buildings markets. GridGEM’s core competence is constraints management and real-time monitoring.

Ubi™ Energy Management Platform mondo

It provides near real-time energy monitoring, single or aggregated multi-site data, downloadable historic data to see trends, financial and sustainability reporting, optimises solar and batteries. dex GreenSync Provides Visibility of DER, including standing data (nameplate) and near real-time telemetry. Mapping DER to the network model, providing critical insights into DER behaviour and their impact on the grid, leading to increased network reliability, improved compliance and better network planning decisions. The kWatch® Flow Power The kWatch® Intelligent Controller has the ability for near-real time information collection from meters and delivery (via portal and app) to enable participants to make educated decisions about energy usage. Real-time and near real-time visibility of customer loads in response to DR activations and market signals. Ability to measure and observe individual asset behaviour within the customer site.

Node 1 Indra Indra’s node#1 (domo and industrial) based on the Intel® IoT Gateway design acts as the datalogger for every data sent from/to the devices, with the ability to speak the main protocols out there.