Gridcog for distribution networks

Modelling for distribution network operators and DNSPs

Distribution network operators (DNOs), distribution system operators (DSOs) and distribution network service providers (DNSPs) can use Gridcog to model how customer batteries, EV charging, rooftop solar and flexible loads respond to network tariffs, flexibility services and connection limits. The load shapes it produces can feed power-flow studies and network planning.

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Key points

  • 1,950 tariffs

    The Gridcog Library holds 1,950 tariffs with demand charges from 119 networks in 28 countries; the median works out at about €47k per MW a year for a 1 MW load (April 2026).

  • 67 kW

    In a Gridcog model of a London supermarket, switching its battery and EV fleet to smart control cut maximum demand from almost 400 kW to about 67 kW (August 2025).

  • Almost 50%

    NESO's Future Energy Scenarios 2025 put almost 50% of GB system flexibility in 2050 with residential and commercial consumers.

How is the role of distribution networks changing?

Distribution networks are moving from owning assets that carry energy one way from the transmission system to operating a distributed system.

They now integrate and optimise distribution-level resources: variable renewable generation, distribution-connected storage and flexible loads. New network services, operating capabilities and pricing models can all be tested in Gridcog before they reach customers.

How do distribution networks model the impact of batteries and EV charging?

Trial the tariff virtually.

Gridcog models price-responsive, customer-owned resources such as EVs, batteries, rooftop solar, heat pumps and other flexible loads, and shows how each responds to a new network tariff. The resulting customer load shapes can be inputs to power-flow modelling and downstream network planning.

Control mode matters as much as price. In a model of a small London supermarket by Genna Boyle, Gridcog's CCO and Head of EMEA, the same battery and delivery fleet moved from simple control to co-optimised battery dispatch and smart charging. Maximum demand fell from almost 400 kW to about 67 kW, with most demand shifted overnight.

Genna Boyle, CCO and Head of EMEA at Gridcog

Genna Boyle

CCO and Head of EMEA

Read Genna's analysis of NESO's Future Energy Scenarios 2025

How much do network demand charges vary?

A lot.

Gridcog CEO and Co-Founder Fabian Le Gay Brereton analysed 1,950 tariffs with demand charges in the Gridcog Library, from 119 networks in 28 countries. For a 1 MW load the median was about €47k per MW a year, the 90th percentile about €159k and the highest about €624k.

Across 1,950 tariffs, for a 1 MW load:

About €47kMedian, per MW a year
About €159k90th percentile
About €624kHighest
Ausgrid, Australia

EA305

What makes it complex

Time-of-use demand charge on a 12-month rolling ratchet

Indicative demand cost

About €144k

per MW a year

WEL Networks, New Zealand

655 Large Customers LV

What makes it complex

Seasonal demand charges plus an excess charge above contracted capacity, with power factor treatment

Indicative demand cost

About €378k

per MW a year

E-REDES, Portugal

AT (high voltage)

What makes it complex

Contracted capacity charge, peak-window demand charge and excess demand, on a four-period seasonal time map

Indicative demand cost

About €58k

per MW a year

The tariffs apply to different loads and voltage levels, so they are not directly comparable. What they show is how much structure a model has to handle: time maps, ratchets, contracted capacity, excess-demand penalties and utilisation bands.

Fabian Le Gay Brereton, CEO and Co-Founder of Gridcog

Fabian Le Gay Brereton

CEO and Co-Founder

Read the network demand charges analysis

Can networks test flexibility services and new connection arrangements?

Yes.

Networks are contracting network support through distribution-level flexibility markets, and customers weigh that value against avoided supply costs and wholesale market services. Gridcog models the complete value stack for distributed energy resources and demand flexibility, so a network can see whether its offer is attractive.

Connections are shifting the same way, from static import or export limits to dynamic limits and operating envelopes. Gridcog models how each arrangement changes a customer's supply costs and revenue, which supports new network products and conversations with customers during the connection process.

How do you value community batteries and other network-owned assets?

Count every function.

Neighbourhood or community batteries, stand-alone power systems, microgrids and EV charging serve customers, markets and the network at once. Gridcog gives a complete view of that customer, market and network value to support regulatory engagement, investment decisions and performance reporting.

Community batteriesDemand side response and flexible loadsVirtual power plants

Testing a tariff or flexibility product?

Model your project in Gridcog

Frequently asked questions

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A distribution network operator (DNO) owns and runs the regional network that carries electricity from the transmission system to homes and businesses, such as UK Power Networks in Great Britain. In Australia the equivalent is a distribution network service provider (DNSP), such as Ausgrid. As networks take on active management of local resources, the role is often called a distribution system operator (DSO).

No. Gridcog models how customers and their assets behave: generation, storage, EV charging and flexible loads responding to tariffs, markets and connection limits. The customer load shapes it produces can be inputs to the power-flow tools networks already use for planning.

Yes, in detail. The Gridcog Library includes transmission and distribution tariffs, updated in line with the network operators' own changes. Gridcog handles layered time-of-use maps, demand ratchets, contracted capacity, excess-demand penalties and utilisation bands, and optimises how batteries and flexible loads respond to them.

Yes. Gridcog models existing and planned connections, dynamic connection limits, active network management and dynamic operating envelopes. A Site Import Schedule applies timed or phased import limits, and interval data can represent real-time curtailment, so you can see the effect on each customer's costs and revenue.

Gridcog models the full value stack in one optimisation: avoided supply and network costs, wholesale trading, ancillary services, capacity markets and network flexibility payments. You can see whether a flexibility service adds value on top of the alternatives, or whether a customer would earn more elsewhere.

How customer-owned resources will actually behave. NESO's Future Energy Scenarios 2025 put almost half of GB system flexibility in 2050 with residential and commercial consumers. Modelling those assets under realistic control modes and price signals shows networks how much peak they can expect to move, and at what price.

Request a live demo

See Gridcog on your own project.

Tell us a little about what you're modelling and we'll shape the demo around it. Bring your own price curves and assumptions, or use ours.

The team behind Gridcog

Fabian Le Gay Brereton, Chief Executive Officer and Co-Founder of Gridcog

Fabian Le Gay Brereton

Chief Executive Officer & Co-Founder

Previously co-founded Greensense, acquired by ERM Power (now Shell Energy).

Pete Tickler, Chief Product Officer and Co-Founder of Gridcog

Pete Tickler

Chief Product Officer & Co-Founder

Co-founded Greensense and led digital innovation at ERM Power (now Shell Energy).

Genna Boyle, Chief Commercial Officer and Head of EMEA at Gridcog

Genna Boyle

Chief Commercial Officer & Head of EMEA

More than 10 years in energy strategy, trading and renewables, with senior roles at Battery Optimiser and Limejump.