Slovenia is developing a flexibility-market test bed using smart meters, dynamic network tariffs and automated electric-vehicle charging. Recent Slovenian pilots indicate that EV charging can be shifted to cheaper periods without disrupting fleet operations. The country’s regulator has also identified a second issue: if thousands of customers react to the same price signal at the same time, flexibility can create a new electricity-demand peak.
The regulator’s findings are pushing the market beyond conventional time-of-use tariffs. Consumption is increasingly expected to respond simultaneously to electricity prices, network conditions and operational requirements. The commercial opportunity described for this shift involves selling optimisation rather than electricity alone.
Optimisation services using smart-meter data
Suppliers, aggregators and energy-management companies can sell optimisation decisions on when vehicles charge, buildings consume electricity or industrial equipment operates. Slovenia’s infrastructure for this model is supported by widespread smart-meter deployment. The granular consumption information can be used to establish customer baselines, forecast flexible demand and verify whether an agreed reduction or shift in electricity consumption occurred.
The meter is described as more than billing equipment. It becomes part of the infrastructure required to run a flexibility market. In this setup, the value comes from the ability to translate consumption patterns into inputs for flexibility verification.
EV fleet pilots with Avantcar and Kolektor sETup
Electric vehicles are presented as an early test case for the approach. Results from Slovenian pilots involving Avantcar and Kolektor sETup show that fleet charging can be optimised against electricity-market conditions while maintaining vehicle availability.
The operational principle described is based on connection time versus required readiness. A vehicle connected to a charger for eight hours may only need two or three hours of actual charging. The gap between connection and departure provides an aggregator with a window to move electricity demand.
Across hundreds or thousands of vehicles, those windows are described as forming a significant flexible electricity portfolio. For fleet operators, the immediate benefit cited is lower energy procurement costs. For aggregators, the same flexibility could be offered into balancing or local distribution-network markets where regulations permit.
Limits of price-only shifting and dynamic network signals
Slovenia’s national flexibility assessment highlights limitations of simple price optimisation. If electricity or network tariffs become cheaper after a certain hour, automated chargers may all react simultaneously. Rather than reducing system pressure, thousands of vehicles could start charging together and create a new night-time peak.
The assessment also notes similar risks for heat pumps, electric boilers and other automated loads. It describes a change in programme design from moving consumption away from peak hours to preventing too many flexible devices from shifting in the same direction at the same time. That requires more granular signals than earlier demand-side programmes.
Dynamic network pricing is described as one possible solution. Traditional tariffs primarily indicate when electricity is expensive, while a more sophisticated network tariff can also signal when particular parts of the grid are constrained. As distributed solar, EVs, heat pumps and other flexible assets connect across distribution networks, location becomes part of optimisation decisions.
The source describes how one megawatt of additional consumption may be beneficial where local solar output is high and network capacity exists, while the same megawatt could worsen congestion elsewhere. It says optimisation therefore cannot rely only on when electricity is cheapest. The focus shifts toward when and where the power system has capacity for additional consumption.
Software layers combining wholesale prices and grid constraints
Slovenia’s advanced metering infrastructure provides energy-service providers with consumption data needed to address capacity constraints. Detailed meter data can show when customers consume electricity, how predictable that consumption is and how much could potentially be moved. For industrial users this may involve identifying flexible pumps, compressors, cooling systems or production processes.
For commercial buildings it can involve heating, cooling or ventilation. For EV fleets it involves determining how long vehicles remain connected and how much energy each requires before departure. Software can then combine hundreds of individual profiles into a portfolio large enough to participate in electricity markets.
This creates an additional commercial layer around meter-data analytics, automated demand response, consumption forecasting and flexibility verification. The infrastructure described as enabling dispatch is not only the meter but also software that converts meter readings into an asset the power system can use .
Automated flexibility services and roles for aggregators
A longer-term model is described as more sophisticated than tariff response alone. A fleet-management platform could examine wholesale electricity prices, network tariffs, local grid conditions, balancing-market revenues and each vehicle’s charging requirement simultaneously . An industrial energy-management system could perform similar calculations for production equipment.
The customer sets operational boundaries while software decides when electricity should be consumed within those limits. This approach is described as turning electricity flexibility into an automated service rather than requiring behavioural response to cheaper night-time tariffs.
The role of aggregators is also described as important between consumers and the power system. Aggregators can combine thousands of small assets, forecast their availability and sell resulting flexibility to parties that need it. Buyers could include suppliers, transmission operators and distribution companies where applicable .
Regional implications for Southeast Europe’s power markets
The model described is said to have implications beyond Slovenia. Southeast European countries are investing heavily in smart-meter infrastructure while EV charging, electric heating and distributed generation increase flexible electricity demand connected to distribution networks.
The source says many investments are still discussed in terms of equipment deployment rather than market design once equipment exists. It states that the next stage will centre on interaction between smart-meter data, dynamic tariffs and automated consumption . EVs are identified as an early use case alongside coordination of commercial buildings, industrial processes, heat pumps, electric boilers and other controllable loads.
The business model described relies on existing assets with limited new generation capacity requirements because the asset already exists . What is described as missing is a digital layer capable of determining when controllable assets should consume electricity and turning that resulting flexibility into revenue.
