Household flexibility is emerging as a central element of the energy transition as power systems move away from centralized, one-way operation toward decentralized, multi-directional, data-driven and dynamic models, said Kiss Péter, Residential Flex Europe business development lead at Kraken Tech, at the Portfolio AI in Energy 2026 conference. The shift poses operational challenges for network operators and suppliers while opening new commercial opportunities.
Electrification and the proliferation of home devices
Electrification is a major driver: the growing presence of high-power devices in homes—electric vehicles, heat pumps, inverters, PV systems and batteries—could total some 200 million new distributed devices globally by 2030, according to a BNEF estimate cited by Kiss. These devices raise not only technical capacity issues but also service-design questions: energy companies must profile customers, design appropriate offerings and retain clients over time.
Aggregation and digital twins to manage scale
Kiss said the objective is to ensure that tens or hundreds of thousands of household devices do not stress the grid as separate loads but are aggregated into virtual power plants that support system balance. Technical connectivity alone is not sufficient: residential consumption depends on many individual factors—when a user wants to charge, thermostat setpoints, the devices present in a home, or shading of solar panels—that must be understood and forecast.
Kraken addresses this with machine learning: the platform connects to household devices, collects historical and near-real-time data, and builds digital twins. From these data it generates cohorts and customer segments that form the basis for portfolio-level forecasts and trading strategies. Those digital models help trading desks and portfolio managers monetize the aggregated virtual plant on different energy markets.
Network forecasting and dynamic signals
Network-side forecasting uses household data together with grid information—transformer station telemetry, topology and capacity—to predict where capacity constraints may arise in coming hours. That enables dynamic price signals or optimization signals: if presented as a network-use charge, such a signal creates an economic incentive for consumers or automated systems to shift high-power device use away from congested periods.
Kraken’s approach can be more direct: a dynamic signal or network optimization instruction fed into the aggregator engine can actively control devices, so that, for example, EV charging in a constrained area is curtailed or rescheduled. This is the operational essence of residential flexibility: devices operate in line with household needs, market prices and network limits rather than randomly.
Three business value channels
Kiss identified three main commercial value streams:
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Customer lifetime value: residential flexibility programs serve as customer retention tools. Kraken reports a 95 percent retention rate in its supported residential flexibility programs, which Kiss called a competitive advantage.
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Spot market optimization: by shifting the portfolio’s energy needs, suppliers can procure electricity in cheaper periods. Kiss estimated wholesale procurement savings of roughly 100–150 euros per EV per year across Europe, achieved primarily via day-ahead and intraday optimization.
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DSO and system services: integrating residential portfolios into network and system-level flexibility markets can create new revenue streams, though many European markets remain at pilot or early stages. As an example, the UK saw some 340 million euros of network investment savings associated with flexibility in 2024.
Kraken’s footprint and ambitions
Kiss described Kraken not only as a residential-flexibility technology provider but as a global software firm supporting utilities across customer management, billing, distribution and field operations, with utility-grade AI embedded across those offerings. The company currently supports about 70 million customer accounts worldwide. While Hungary has not been a core target market to date, Kraken aims to explore partnerships and expand locally, with an ambition to impact more than one billion people by the end of the decade through cheaper, cleaner energy and improved utility services.
Conclusion
For Kiss Péter, residential flexibility is no longer purely a technical topic: it represents a network risk and simultaneously an opportunity for customer retention, trading optimization and new revenues for energy suppliers. Aggregation and AI are central to turning dispersed household devices into system-level flexibility resources.
