The market of energy services for the residential sector in Europe is very limited at present. Various reasons can be argued such as the high transaction costs in a highly fragmented market and the low energy consumption per dwelling. The rather long payback time for investments render Energy Services Companies’ (ESCOs) services financially unattractive for many ESCOs and building residents, thus hindering a large potential of energy savings in a sector that is responsible of almost half of Europe’s energy consumption. If the ambitious 2030 and 2050’s decarbonisation targets are to be met, the EU’s residential sector must be part of the solution. This paper offers insights about novel ESCO business models based on intensive data-driven Artificial Intelligence algorithms and analytics that enable the deployment of smart energy services in the domestic sector under a Pay-for-Performance (P4P) approach. The combination of different sources of energy efficiency services and the optimal participation of domestic consumers in aggregated demand response (DR) schemes open the door to new revenue streams for energy service providers and building residents and reduce the hitherto long payback periods of ESCOs services in the sector. Innovative business models for ESCOs and demand flexibility Aggregators are thoroughly described. Especially customised Performance Measurement and Verification protocols enable fair and transparent P4P ESCO contracts. The new human-centric energy and non-energy services increase the energy consumption awareness of building users and deploy behavioural and automated responses to both environmental and market signals to maximise the economic benefit for both energy service providers and consumers, always respecting data protection rules and the consumers’ comfort preferences. The new hybrid business models of P4P energy services make traditional EPC more attractive to energy service providers, with low cost data collection and treatment systems to bring payback periods below 10 years in the residential building sector.

This study addresses an identified literature gap regarding indoor environmental quality in residential buildings, where the primary focus has traditionally been on energy performance rather than comfort optimization. Leveraging the low-cost and easy-to-implement LoRaWAN protocol, this research collects and analyses real-time data on comfort parameters, including temperature, CO₂ levels, humidity, lighting, atmospheric pressure, and total volatile organic compounds (TVOC) across various buildings within the INCUBE EU project. The results highlight the dynamic nature of the parameters and emphasize the importance of continuous monitoring to enhance comfort and energy efficiency in smart residential buildings. The findings advocate for integrating technologies like LoRaWAN to optimize indoor environmental quality, ultimately improving residential comfort and occupant well-being.

The residential building sector is critical to the success of Europe’s 2030 and 2050 decarbonization targets. To achieve that success, this paper demonstrates how advanced Pay-for-Performance (P4P) energy services for energy service companies (ESCOs) can address challenges by leveraging low-cost data collection systems in buildings to offer a combination of revenues stemming from informed decision-making, energy management optimization, and active participation in demand response schemes. Our methodology includes (i) preliminary assessments to identify each building’s occupancy patterns, equipment, and smart readiness, (ii) the installation of sensors and data gateways, (iii) the deployment of data-driven energy efficiency and demand response measures, and (iv) the evaluation of non-energy services such as comfort and air quality monitoring. We conducted empirical tests in three distinct building typologies: a multi-apartment residential building in Spain, detached dwellings in Croatia, and a hotel bungalow in Greece, to measure self-consumption savings, occupant-driven energy use behaviour changes, and the potential for explicit demand response. The results indicate overall payback periods of less than 10 years, although effectiveness varies depending on occupant engagement, building suitability, and the local energy market context. These findings reinforce the technical and economic feasibility of enhanced ESCO smart services and provide practical insights for scaling up data-driven solutions to advance Europe’s energy and climate objectives.