PPC and Protergia are marketing dynamic electricity products for residential customers in Greece where retail prices change with wholesale market prices rather than staying fixed for a full month or contract period. The offers are positioned as a shift in how ordinary consumers experience hourly wholesale-market economics. The products are designed to align household and small-business consumption timing with market price movements.
Dynamic tariff structures and customer requirements
PPC’s myHome Dynamic prices electricity using a formula of 1.19 times the hourly market clearing price plus €0.044/kWh, alongside a fixed charge of €9/month. The supplier publishes the next day’s 24 hourly prices so customers can schedule consumption around lower-cost periods. Participation requires an installed smart meter and validated metering data from distribution operator HEDNO.
PPC also states that customers interested in joining a dynamic contract can request smart meter installation rather than waiting for HEDNO’s normal national replacement programme. Smart meters have traditionally been used to support billing efficiency, remote readings and network modernisation. In this context, dynamic tariffs provide an immediate commercial reason for customers to request the meters.
The smart meter functions as the gateway to a different retail proposition under which customers can be exposed to hourly price signals. Protergia is competing with its Dynamic One Home product for residential low-voltage customers with smart meters. That offer includes a fixed charge of €9.90/month and hourly pricing linked to the wholesale market.
Wholesale reference pricing and the role of HEnEx
HEnEx, the Greek market operator, provides the reference architecture behind the dynamic products. For each delivery day, it publishes the day-ahead clearing price for individual market time units and an hourly reference price for dynamic electricity contracts. Because Greece’s day-ahead market clears in 15-minute time units, the hourly dynamic reference is calculated as the average of four quarter-hour prices within each hour.
This mechanism transmits wholesale volatility into retail bills through the published reference price. It also creates variability for consumers depending on when they consume electricity relative to hourly price levels. A customer able to shift demand into lower-price midday periods may reduce costs, while consumption concentrated in higher-priced evening hours may increase them.
Flexible loads enabled by dynamic pricing
The commercial value of dynamic tariffs is described as depending less on annual electricity consumption and more on load flexibility. The source examples include electric vehicles consuming 3 MWh/year, where most charging can be moved several hours without affecting consumer outcomes. Heat pumps combined with thermal inertia or hot-water storage are also cited as use cases where timing can be adjusted.
Air conditioning is another highlighted load category because summer power demand can be influenced by cooling needs. Automated temperature management can move part of consumption between intervals without switching cooling off entirely. This setup is described as creating conditions for automation tied to the electricity contract rather than relying only on manual behaviour changes.
At present, customers are mainly shown tomorrow’s prices and encouraged to change behaviour manually based on that information. The next step described is software that can download the next day’s hourly price curve automatically and decide when to charge an EV, operate a water heater, or pre-cool a building. In that scenario, the customer is not actively trading electricity because an algorithm performs decisions on their behalf.
Supplier economics, aggregation overlap, and product competition
The shift toward automated control overlaps retail supply with aggregation functions. A supplier controlling thousands of such devices is described as having a dispatchable demand portfolio rather than only passive customer exposure. The company could optimise that portfolio against wholesale procurement while balancing exposure and participation in flexibility markets.
The structure also changes supplier economics by altering how much hourly price risk is borne by different parties. A traditional retailer carries much of the price risk by buying at variable wholesale prices and selling under a retail structure that may smooth those movements. Under a dynamic contract, more of the hourly exposure is transferred to the customer, reducing procurement risk but requiring support for managing that exposure.
This creates competitive pressure around software capabilities rather than only headline €/kWh pricing. Examples of product approaches mentioned include wholesale pass-through, bundling an electricity contract with automated EV charging, combining a dynamic tariff with a heat pump, home battery or smart thermostat, and offering guaranteed savings in return for limited control over selected appliances. The margin is described as increasingly coming from optimisation across these elements.
Metering and data-flow constraints in Greece
Dynamic pricing depends on suitable metering infrastructure and efficient interval data flows between HEDNO and suppliers using validated metering data. The source states that Greece has moved beyond conceptual discussion because products are commercially available and competing for customers. It frames Greece as an SEE test of whether consumers respond to wholesale prices and whether suppliers can convert that response into scalable flexibility operations.
The relevant metric is presented as not only how many households sign dynamic contracts but how many megawatts of household load become controllable once they do .
