Case Study on EV Charging Control | Impact of EV Charging

Introduction

Jemena Networks, a Melbourne based distribution utility, and four other
Australian distributors embarked on a government funded trial project to
understand the technical, social, and network impacts of dynamic electric
vehicle (EV) charging in 2020. Dynamic Ratings partnered with the trial to
provide engineering support and monitoring equipment to help realize the
project goals.

EV Charged Cars driving on freeway

The Challenge

EV charging is an evolving industry that is already having a significant impact on the power grid. In recent years the cost of EVs has started to decrease, the number of vehicles has increased and government incentives have been introduced all over the world to support carbon reduction goals.

The population of EVs has begun to dramatically increase which drives the need for charging infrastructure. Distribution utilities are looking forward to options for managing the steady electrification of the transport sector (and beyond). Level 2 domestic chargers are inexpensive (and in some cases offered free with the vehicle) and offer between 7.7kW (single-phase) and 22kW (three-phase): large loads to be all connected to the same local street transformer (In Australia, a single (larger) 3-phase pole-top transformer supplies low voltage power to a whole street).

Energy networks are designed to protect against overloading: if there is too much load on a given low voltage (LV) street circuit, the network protects itself from damage – in this case by blowing a fuse at the nearby distribution  substation (DSS) transformer. Unfortunately, this protection mode impacts more than the electricity users contributing to the problem; everybody connected to the transformer is impacted by an outage, waiting for the maintenance crews to attend the site. Furthermore, other impacts such a voltage drop along an LV feeder may not receive the same visibility due to lack of monitoring, yet obviously have negative impacts on the users at the ends of a circuit where the voltage may be being pulled lower than regulatory limits.

Dynamic Ratings ConnectGrid TTM mounted on an electrical pole

The Solution

Obvious network solutions such as transformer upgrades are not off the table, however the cost and breadth of the problem makes them untenable except in specific areas of the network. The Australian Renewable Energy Agency (ARENA) funded a project with a group of distribution network operators (DNOs) and industry partners to trial real-time EV charger control utilizing operating envelopes
determined by network constraints. Dynamic Ratings worked with Jemena Electricity Networks (the DNO for Melbourne, Victoria) to supply LV monitoring devices and the calculation platform that calculated the operating envelopes and sent them to the EV charger service provider.

Jemena developed an operating envelope (OE) algorithm that calculates available network capacity for EV chargers. When network capacity becomes constrained, a reduced operating envelope is sent to the EV chargers to reduce their charge rate and ease the impact on the network. The system determined network capacity based on three major constraints: distribution substation capacity, individual LV circuit capacity, and end of circuit voltage.

Distribution Substation Capacity

DSS or transformer capacity is determined based on transformer loading compared to nameplate capacity. LV monitors were supplied by Dynamic Ratings and installed
at the DSS on the LV side of the transformer. The monitors supplied near-real-time data to a software platform, including load currents, voltages and power quality
information.

LV Circuit Capacity

LV circuit capacity was based on known circuit/load splits, the transformer loading and the known circuit/conductor rating.

End of Circuit Voltage

End of LV circuit voltage constraints were determined from either measured smart meter (AMI) voltage data or calculated from circuit voltage drop. The measured voltages were extracted from the Jemena metering system and inserted into the Dynamic Ratings platform in nearreal-time using a secure API connection. The goal of end of circuit voltage capacity aimed to prevent the voltage from going below regulatory limits under high loading and used a calculation to determine the margin of voltage available (from current voltage to the low voltage setpoint). This was used to calculate the extra allowable load on the circuit.

System Architecture

Jemena chose the Dynamic Ratings ConnectGrid™ software platform to implement and host the operating envelope algorithm. The system provides data collection and device management services for the connected LV monitors installed at the DSS sites and provides API endpoints for secure injection of AMI data from smart meters. The system also communicates with the EV charger service provider via an API interface based on IEEE2030.5 to retrieve charger status and measurement data, send operating envelopes and pull meteorological data to use for historical load current lookups.

The Result

The LV monitors were installed quickly, safely and successfully using tools that were familiar with the overhead line workers. Data API integration between the secure AMI metering data environment and the EV charger service provider was completed and tested to ensure data flows were adequate to meet the system demands. The OE was implemented on the ConnectGrid™ automation platform and run in test mode for a period of time to ensure the system performed as expected for certain test cases. With the system up and running, Jemena has undertaken trial usage of the system to test various scenarios. This has proven that the technical capability of the overall OE system (including all data sources and interconnections) is working effectively. In a relatively short time, new monitoring equipment was installed in the network, data connectivity was built between multiple organisations and a complex algorithm was implemented to operate reliably and effectively paving the path for real-time control of the low voltage network, intelligent demand response and management of distributed energy resources.

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