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  • Writer's pictureBram van der Wal

How AI creates high value EV services on top of Smart Meter Data

Nowadays with the use of advanced AI algorithms, utilities are able to integrate the Electric Vehicle (EV) charging consumption component as part of their energy insight services and adding this on to the integral home energy bill as a separate item. Using these EV charging load curves, on top of smart meter data analytics, utilities are able to detect when the EV charging started, stopped, for how long it ran and how much energy was consumed charging an EV. This data disaggregation works without a direct interface connection to the charger or any user input making this a universal EV charging insights service. Just smart meter data alone will do it.

A truly enjoyable experience for your customers using just smart meter data

Processing 15 minute AMI meter reads already gives a good idea of the energy used for car charges. However the use of real time smart meter data offers extra features and benefits to the customer. These benefits include not having to worry about overloading your residential electrical system when charging, using solar energy for car charging as much as possible, enjoy special EV electricity tariffs (when charging at specific times or with an EV tariff bundle) and expensing the electricity cost for car charges, because it is separated on the bill. Next to these benefits a user can be notified by their utility app once the charging has finished without the need for an EV charging specific app.

To detect EV charging in real-time, only a small inexpensive SmartBridge is needed. It can be self-installed by the customer on their own smart meter and via a mobile app the user can get the EV charging insights. See the live demo in below video where the appliance recognition runs in hardware on the SmartBridge using 1-10 second HAN data.

New EV services and business models to stand out in the market

Not only customers benefit, real-time detection of EV charging opens up an array of new service and business models for utilities and EV charging solution providers.

1. Identify customer homes and regional / local hotspots when charging EVs

Using electrical consumption data disaggregation, utilities are able to identify customers having already an EV charger and electric car at home. This would allow them to target specifically those EV drivers with a personalised offer for e.g. a specific Time-of-Use tariff, a personal EV charging tariff or even the lease of an electric vehicle.

Next to this utilities could approach these customers to participate in a behavioural or automated demand response program when applying a smart charging feature using real-time smart meter data insights. This way the increasing EV charging loads on the local grid network can be better balanced and expensive grid infrastructure investments can be postponed or avoided.

Electric Charging Demand Location Model (Source: MDPI - 2019)

2. Integrate EV charging costs into a unified energy insight experience and on one energy bill

Because the EV charge loads can be detected from smart meter data you can have them made visible as an integral part of the energy bill break down.

For end customers this will give transparency when and how much energy the EV charging really takes from their annual energy costs and enables EV charging solution providers to offer an integrated home energy consumption overview as add-on service.

3. Enable Smart Charging at home avoiding overloads of the residential electrical installation

With the use of a low cost real-time SmartBridge you are able to tell the current energy load at home level and see how much energy bandwidth is still available inside the home while charging an EV, also when using solar panels. This real-time energy insight data can be used by energy suppliers or charge pole operators to start, stop, shift, throttle up or down the EV charging loads based on merely real-time smart meter data.

Residential EV smart charging loads explained on the right side of the picture (Source: García-Villalobos et al., 2014)

4. Performance monitoring of EV charging sessions enabling preventive maintenance services

With the EV charging activity being detected using granular smart meter data you can also tell the customer, for each charging session, if the car was fully charged up to 100% (notice the sliding - throttling down charge load between 80% to 100% battery capacity, for battery longevity purposes, in the first picture), or to the default 80% battery capacity (second picture) as e.g. Tesla advises on their models.

Monitoring the charging sessions you can detect trends over time that might indicate decreased battery capacity or other influencing factors that could give you an upfront notification to check the charging process and its components.

5. Flexible tariffs for EV charging utility customers

When using a flexible tariff for Time of Use or as part of a Charging-as-a-Service offer you can apply specific EV charging tariffs, while maintaining another electricity tariff for the rest of the energy consumption in home. By doing this you offer customers a unique proposition to charge their car at home against reduced prices or at specific ToU moments. The great thing is that all items can be placed on one electricity bill, even with a special tariff.

6. Automated reimbursement for company car charging sessions at home

As we previously explained the EV charging loads are automatically detected analysing smart meter data and can be linked to a certain cost unit. This would enable the EV charging bill component to be automatically integrated with a company EV lease contract. This means your customer can charge at home against the tariff of their business energy contract or a utility EV lease contract.

7. Charge the car with your own generated solar power

Using smart meter data to detect the actual amount of solar energy self-production at home (and obviously net metering as well), and detecting when the EV charging took place, you can tell within the integrated energy insights overview how much solar energy from your own roof was used to charge the EV. For customers this gives them the opportunity to charge their EV with as much solar power from self-generated electricity as long as the car is plugged in at home while the sun produces the charging loads.

NET2GRID Ynni white label energy insight app showing one morning charge session while solar generation takes place, and another evening charge session without solar energy being produced

8. Automated Demand Response using the EV as outlet for peak shaving

ADR controlled services can use the residential real-time smart meter data in order to identify which residential customers have free capacity available and could steer signals to the EV charging process as an outlet for off-loading electricity peaks.

By the use of real-time insights utilities can generate up to 3 hour-ahead load forecasting models on what specific houses have as predicted free capacity available and enough bandwidth, so utilities are clear to send a charge signal to the EV charger when extra energy off-loading is required.

NET2GRID 3h ahead energy consumption forecast service as used for intra-day energy trade

Via these flexibility residential energy pools utilities are able to offer grid flexibility services to DSOs and TSOs, participate in intra-day energy trading, and reimburse end customers for the use of their residential flexible energy capacity.

These use cases are all powered by NET2GRID’s PaaS offering

NET2GRID uses AI-driven smart meter data analytics and energy insight platform services via open APIs, which can be integrated with utility platforms, EV charger operators and charge pole manufacturer solutions.

If you are interested in knowing more about our Platform-as-a-Service on the above mentioned use-cases or their respective business models please contact us at


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