Resources
Toward a human-centric demand response framework: Optimizing energy efficiency and comfort for aging people in the built environment (pre-print version)
This paper shows how a human-centric demand response framework can improve both energy efficiency and the comfort of older adults in residential buildings. Developed within the DEDALUS project, the framework combines IoT technologies, Artificial Intelligence and personalised comfort models to optimise demand response strategies while addressing the specific needs of elderly occupants. The approach is demonstrated through the DEDALUS Italian pilot in Treviso, showcasing its potential to support more inclusive, user-centred and sustainable building energy management.
DEDALUS Innovation Handbook
The DEDALUS Innovation Handbook brings together the project’s main pilot experiences and lessons learned on residential demand response.
Drawing on seven real-life pilots across Europe, it shows how interoperable, human-centred and data-driven solutions can support residential flexibility while addressing key challenges related to user engagement, comfort, data readiness and replication.
DEDALUS Policy Brief for System Operators
This policy brief presents the key operational lessons from the DEDALUS project on enabling residential demand response (DR) in Europe. Drawing on evidence from five pilot sites, it outlines the practical steps that transmission and distribution system operators can take to move residential flexibility from pilot validation to real system integration. Cost Minimization in Energy Communities With Multi-Agent Deep Reinforcement Learning and Linear Programming
This paper presents MODREC, a decentralised Community Energy Management System combining multi-agent deep reinforcement learning and linear programming to optimise energy use in residential energy communities. By coordinating PV systems and battery storage under dynamic pricing, the approach enables intelligent load shifting, reduces costs by up to 30%, and supports the use of residential flexibility as a system-level resource. Policy Recommendations for Residential Demand Response
These policy recommendations present the DEDALUS priorities for scaling up residential demand response across Europe. Based on pilot experience and expert policy dialogues, they outline six priority actions to address regulatory, technical and social barriers, supporting the effective implementation of the upcoming Network Code on Demand Response
Improving energy autonomy of positive energy districts using multi-agent deep reinforcement learning
This paper presents CoMAD V2G, a multi-agent deep reinforcement learning solution to improve energy autonomy in Positive Energy Districts with shared energy storage and V2G-enabled electric vehicles. By optimising EV charging and discharging while preserving user comfort, the approach reduces grid dependency, lowers household electricity costs by up to 25%, and supports more sustainable community-level energy management. Expert Roundtable on Residential Demand Response Policy
This report provides the key insights from the second DEDALUS policy roundtable on residential Demand Response, in which a select group of energy policy experts from EU governance, industry and academia discussed which new EU-level policies can have the most meaningful impact right now — particularly in light of the forthcoming Network Code on Demand Response. Incentive Design Toolkit | Behavioural Strategies for Residential Demand Response
This factsheet presents the DEDALUS incentive design toolkit, providing practical guidance to support user participation in residential demand response programmes. Drawing on behavioural insights and pilot experience, the toolkit highlights the complementary role of financial and non-financial incentives, as well as the importance of user segmentation, timing and socio-cultural alignment in enabling sustained engagement SSH Framework | End-user Engagement Strategy for Residential Demand Response
This factsheet presents the DEDALUS SSH framework, a structured end-user engagement strategy designed to support participation in residential demand response. Combining user segmentation, co-creation, behavioural insights and digital engagement tools, the framework highlights the role of trust, inclusivity and continuous feedback in enabling socially accepted and replicable demand response solutions across diverse residential contexts. Spanish Pilot | District-level Energy Optimisation for Local Energy Communities
The Spanish pilot shows how district-level energy optimisation can support local energy management in a residential energy community. Implemented in La Seu d’Urgell, the pilot combines household-level flexibility, shared battery storage and cloud-based optimisation tools, highlighting the role of integrated system design, user recruitment and accessible communication in enabling demand response at community scale. Romanian Pilot | Data-driven Residential Flexibility for Student Housing
The Romanian pilot shows how data-driven residential flexibility can be implemented in a student housing environment. Combining structured data modelling, digital twin services and a blockchain-enabled flexibility market, the pilot highlights the role of interoperable data systems and user familiarisation in enabling advanced demand response services in complex residential contexts. Italian Pilot | Comfort-aware Energy Management for Elderly Residents
The Italian DEDALUS pilot shows how residential demand response can be implemented in a senior cohousing environment through comfort-aware energy management. By integrating monitoring systems, a digital twin and an AI-driven flexibility model, the pilot highlights the importance of accessible design and mediated engagement in ensuring usability and acceptance among elderly residents.
Irish Pilot | Heat Pump Optimisation for Residential Flexibility
The Irish pilot shows how API-based heat pump optimisation can support residential demand response by aligning operation with electricity prices, PV availability and grid carbon intensity. Combining residential connectivity with controlled validation, the pilot highlights the role of data availability, system interoperability and reliable infrastructure in enabling heat pumps to act as flexible assets in residential energy systems. Greek Pilot | Multi-vector Demand Response for Residential Flexibility
The Greek pilot shows how multi-vector demand response can optimise both electricity and heating flexibility in residential environments. Deployed across multiple cities, the pilot combines smart heating control, appliance-level monitoring, digital twins and user-facing nudging applications, highlighting the role of forecasting and continuous user interaction in sustaining participation and balancing grid efficiency with occupant comfort. Danish Pilot | Digital Comfort and Flexibility Services for Social Housing
The Danish pilot shows how digital tools can support district heating optimisation and indoor climate management in social housing. Implemented across two residential blocks in Herning, the pilot highlights the importance of predictive heating control, tenant-facing services and accessible in-person onboarding to enable demand response in highly diverse residential settings. Austrian Pilot | Interoperable Digital Platforms for Residential Energy Communities
The Austrian pilot shows how interoperable digital platforms can support residential energy communities in a multi-unit building complex in Wiener Neustadt. By combining peer-to-peer energy trading, local optimisation and user-facing services, the pilot highlights the role of interoperability, user onboarding and integrated system design in enabling active participation in demand response.
Integration of Cloud Computing and Real Time Simulation Systems for Validating Energy Management Solutions
This paper presents a Cloud-in-the-Loop architecture to validate cloud-based energy management solutions before real-world deployment. Using real-time simulation and hardware-in-the-loop tools, the approach supports the optimisation of storage use in distributed residential energy systems. Data-driven techniques to improve the reliability of low voltage electricity networks through dynamical evaluation of non-technical losses
This paper presents a data-driven methodology to improve the reliability of low-voltage electricity networks. By detecting and assessing the origin of non-technical losses and grid anomalies, the approach supports smarter and more efficient management of increasingly distributed and variable energy systems. Optimizing Electricity Sharing from Generation and Storage Within District-Based Renewable Energy Communities
This paper presents a linear programming-based methodology to optimise energy distribution within renewable energy communities. Validated in a real pilot with 12 dwellings, a shared PV plant and a centralised storage system, the approach improves fairness and efficiency in local energy allocation. DEDALUS Toolkit for incentive scheme design
This DEDALUS toolkit shows how to design effective incentives for residential Demand Response, combining financial and non-financial measures tailored to different user profiles. Its core message is that incentives work only when they are people-centred, clear, fair, and aligned with real behaviours and needs. First Policy Roundtable on Demand Response and Its Deployment
This report summarises the key insights from the first DEDALUS policy roundtable on demand response deployment in Europe. It highlights the main regulatory, technical and social barriers that still need to be addressed to support wider uptake. D7.2: DEDALUS Communication Kit
This deliverable presents the main communication tools developed for DEDALUS, including the website, printed materials, video and social media channels. It outlines their design, implementation and monitoring, highlighting their role in informing stakeholders, supporting engagement and broadening the project’s outreach. D5.2 – DEDALUS Pilots’ execution documentation and consumers’ engagement pre-pilot phase
This initial report summarises progress in DEDALUS pre-pilot demonstration activities across the pilot sites, including KPI results, service deployment and next steps. It also assesses the real-world impact of the deployed technologies to support further refinement and optimisation. D4.1: ‘First wave’ of DEDALUS digital twins and data-driven services for residential DR
This deliverable presents the first wave of DEDALUS Digital Twins and data-driven services for residential demand response. It describes their functional and technical specifications, including architecture and algorithms, as a basis for further development and pilot deployment. D.3.1: DEDALUS technological enablers for multi-value and energy carrieragnostic residential DR (1st technology release)
This deliverable summarises first-year project activities and their contribution to the DEDALUS value-added services. It also outlines progress and next steps across the main technological building blocks, including architecture, interoperability, ontology, flexibility estimation, blockchain, privacy, and security.. IISA 2024 | Methodology for assuring interoperability in demand-response services (pre-print version)
This paper presents a methodology to ensure interoperability in demand response services, enabling seamless data exchange across building systems, devices and applications. It proposes an interoperable architecture based on a shared data model, extending existing ontologies to better represent buildings, users and performance indicators within the DEDALUS framework. DEDALUS Educational Kit
The educational kit introduces residential energy flexibility, demand-response strategies, and user-centred energy management. Aimed at students, researchers, and professionals, it explains the project’s core services—FLEXiT, the Comfort Flexibility Service, and the District-Level Energy Management System—using practical examples from selected DEDALUS pilots.
Key takeaways from the workshop “Human-in-the-loop digitalisation for Europe’s energy transition”
Held during Sustainable Places 2025, this workshop examined how to turn “human-in-the-loop” from rhetoric into concrete participatory methods and people-centred digital solutions. Organised by ICONS under the Smart Energy Cluster, it brought together four EU-funded projects: DEDALUS, CRETE VALLEY, EnerTEF and ENPOWER. Optimal Photovoltaic Energy Allocation in Residential Renewable Energy Communities
The paper explores improved energy-sharing mechanisms within Renewable Energy Communities. Using enhanced linear programming methods validated with real data from a Spanish DSO, it shows how renewable energy allocation can be optimised to reduce surplus generation and increase user benefits across different REC sizes.
Social -Sciences- and- Humanities-Based Profiling of Energy Consumers Towards Increasing Demand Response Engagement
This paper examines the effectiveness of demand response programmes in different European residential contexts by analysing households’ willingness to take part in energy management strategies. Based on questionnaire data from 284 participants in six countries, it identifies different user profiles and their potential for adaptive DR programmes.
Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction
Hybrid transformer model with liquid neural networks and learnable encodings for buildings’ energy forecasting
The paper presents a hybrid Transformer-based model for building energy forecasting that improves accuracy by combining Liquid Neural Networks with learnable encodings. The approach addresses key limitations of existing models, particularly in capturing nonlinear dependencies, weather influences and temporal dynamics in energy consumption patterns.
Social Factors in P2P Energy Trading Using Hedonic Games
This paper shows how energy communities can improve resilience and flexibility through peer-to-peer trading. Using a hedonic game model that factors in social relationships, it optimises prosumer coalitions and increases energy transactions by 5% compared to other methods. Blockchain Solution for Buildings’ Multi-Energy Flexibility Trading Using Multi-Token Standards
This paper shows how buildings can enhance energy system resilience by leveraging their flexibility in multi-carrier energy networks. Using blockchain and ERC-1155 tokens, it enables buildings to trade heat and electricity in community marketplaces, improving interoperability, reducing transactional overhead, and supporting integrated energy grids.
Evolutionary game for incentivizing social cooperation of prosumers in transactive energy communities
The paper explores how evolutionary game theory can foster cooperation among prosumers in transactive energy communities. It presents a blockchain-based local energy market that rewards collaborative behaviour and discourages self-interested actions, supporting peer-to-peer trading and flexibility. Demand response optimization for smart grid integrated buildings: Review of technology enablers landscape and innovation challenges
This paper presents a comprehensive overview and analysis of state-of-the-art technological advancements in building integration within smart grids, with a focus on their role in demand response. It consolidates knowledge from high-quality sources on key research topics, providing researchers, building owners, and energy stakeholders with insights into the latest developments, trends, and best practices in the field.
Methodological approach for optimizing demand response in building energy management through AI-enhanced comfort-based flexibility models (pre-print version)
This paper presents a methodology to optimise Demand Response in building energy management systems through AI-enhanced comfort-based flexibility models. By combining historical and real-time data, it aligns energy use with individual comfort preferences and demonstrates its application across several DEDALUS pilots. A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs
This paper presents a machine learning framework for clustering residential electricity load profiles to support more targeted Demand Response programmes. Using data from thousands of London households and integrating explainable AI, it offers a scalable and transparent approach to consumer segmentation. Review of blockchain tokens creation and valuation
This paper examines the creation and valuation of blockchain tokens, reviewing key standards and the main economic factors affecting their value. Using the PRISMA methodology, it provides an overview of tokenisation applications and related regulatory and valuation challenges. 
