Data-driven Residential Energy Carrier-agnostic Demand Response Tools and Multi-value Services

Projektinformationen

DEDALUS

ID Finanzhilfevereinbarung: 101103998

DOI

10.3030/101103998

Projekt abgeschlossen

EK-Unterschriftsdatum 26 April 2023

Startdatum 1 Mai 2023

Enddatum 30 April 2026

Finanziert unter

• Climate, Energy and Mobility

Gesamtkosten

€ 7 359 075,00

EU-Beitrag

€ 5 999 801,25

Koordiniert durch

ENGINEERING - INGEGNERIA INFORMATICA SPA
Italy

Periodic Reporting for period 1 - DEDALUS (Data-driven Residential Energy Carrier-agnostic Demand Response Tools and Multi-value Services)

Berichtszeitraum: 2023-05-01 bis 2024-10-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Historically, matching electricity supply and demand was relatively straightforward, with large and controllable power plants on the one hand and relatively easy to predict demand on the other. But in recent years, matching electricity supply and demand at all times is becoming more challenging and the electricity system needs more flexibility. A flexible consumption can play an important role in the residential sector. Residential Demand Response (DR) can reduce the need for fossil fuel power plants and help integrate renewable energy onto the electric grid by providing increased stability and management.
The residential sector in Europe offers huge energy demand flexibility, mainly due to the huge thermal energy storage and power management capabilities of the buildings. Moreover, innovative data-driven ICT technologies and IoT-oriented smart appliance are available at decreasing costs.

However, many socio-economic and technological challenges must be considered:
● Socio-economic challenges
○ Insufficient awareness of the value of individual energy consumers flexibility
○ Business models immaturity preventing DR value sharing and propagation along energy and buildings value chains
○ Lack of appropriate yet attracting beyond-financial incentives and compensation stimulating residential consumers engagement
○ lack of a multi-value multi-commodity perspective for residential DR
● Technological challenges
○ Huge protocols fragmentation and heterogeneity and insufficient technical interoperability
○ Smart appliances are smart enough BUT are not DR-ready
○ Lack of dynamic and closer to real-time coordination to really support smart grids applications
○ Lack of trusted and sovereignty-preserving DR data sharing environment (aka DataSpace)

To overcome these challlenges, the project must achieve the following objectives:
1. Using SSH for a better engagement of energy consumers in the residential DR
2. Extension of ENERSHARE Energy Data Space Interoperability and Trust layer
3. Combination of eDREAM, BRIGHT, MATRYCS and DigiBUILD building-level data-driven models, algorithms and flexible assets DTs with end-users’ consumption and beyond consumption profiling models
4. To deliver data-driven, value stacking cross-stakeholder/cross-commodity/cross-value chain DR algorithms, models, and ICT-based services, for DR in energy-efficient residential buildings
5. To demonstrate, validate and replicate DEDALUS solutions through a number of different pilots
6. new business models from sharing economy, multi-carrier system-level perspective and with social innovation and non-financial benefits capture for DR
7. To allow effective consumer participation in DR and further market opportunities by providing input to regulatory bodies to stabilise and harmonise the regulatory framework for residential DR, ensuring an efficient communication and dissemination, as well as alignment and synchronisation with European relevant initiatives and projects.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

In order to use SSH for a better engagement of energy consumers in the residential DR, seven co-creation workshops were organized, questionnaires were created, tailored for each pilot, including questions about the socio-economic, gender, sociocultural and socio-political factors.
To extend ENERSHARE Energy Data Space Interoperability and Trust layer, MQTT was integrated (efficient data exchange) as well as the FIWARE context broker and NGSI agent. The DEDALUS ontology was defined and integrates elements of other (even standard) ontologies. Smart Data Models have been adopted, implementation of ERC721, adoption of OAuth2 and OpenID Connect.
To combine eDREAM, BRIGHT, MATRYCS and DigiBUILD building-level data-driven models, algorithms and flexible assets DTs with end-users’ consumption and beyond consumption profiling models, the 1st technology development cycle was completed, consisting in two Technology Enablers, TE-8 - Digital Twins for consumer-aware optimal flexibility planning and TE-5 blockchain and smart contracts integrated DT.
In delivering data-driven, value stacking cross-stakeholder/cross-commodity/cross-value chain DR algorithms, models, and ICT-based services, for DR in energy-efficient residential buildings, the 1st technology release includes TE-10: Nudging Apps for near real-time closed-loop residential consumers activation and multivector DR, TE-11 Multi-value DR service, TE-12: P2P digital platform for trading pre-aggregated building flexibility, TE-13: District-level DR for self-consumption and cost optimization, TE-14: Aggregation of flexible energy resources for district heating management.
To demonstrate, validate and replicate DEDALUS solutions through a number of different pilots, several initiatives were taken aimed at fostering awareness and participation, such as questionnaires collected insights into energy consumption habits of residential consumers and their willingness to participate in DR programs, co-creation workshops were conducted at each pilot site, 13 different actor types identified, TRL6 reached by the flexibility modelling tool (TE-4), the universal secure gateway (TE-6), mechanisms for secure and privacy-preserving data transactions (TE-7), and the district-level DR for self-consumption and cost optimization (TE-13).

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The advancement beyond the state of the art can be summarized as follows:
• Multi-vector DR for explicit and implicit flexibility management: developing electrical flexibility management tools for building-level energy communities, energy districts and virtual cluster of buildings, based on pre-aggregation and shared DR assets
• SSH-based tools and methodologies for facilitating energy consumers participation in residential DR: providing a Social Science Framework, innovative multi-dimensional incentives and nudging interventions (KER1) for energy consumers’ activation and participation in residential DR
• AI-based models for buildings clustering considering consumers socio-behavioural features: developing ML-based clustering models that are innovatively considering behavioural and social-related features on top-of energy-related ones
• Extended interoperability, data models and flexibility modelling towards DR aggregation for residential buildings: proposing adaptable and modular interoperability tools and methodologies based on standardized architectural concepts, protocols and data models, following the Bridge reference documentation, to integrate smart devices and enable DR services
• Blockchain-based privacy-preserving electrical and thermal DR: providing blockchain-based tools for the decentralisation of energy or heat DR programs management, while assuring the privacy of sensitive data
• Digital Twins for consumer-aware flexibility planning: (i) effective clustering algorithms of residential user loads, supported by social-science driven insights, (ii) thermal models based on advanced neural networks, leveraging real-world assets as monitored in DEDALUS, and enabled by BEMS, (iii) aggregated models for HITL (‘Human-In-The-Loop’) flexibility assessment and modelling of communities (as opposed to individual residential units/devices).
• Comfort-based flexibility for DR and aggregators: providing a platform for flexibility (for DR applications) with comfort-based actions to enable a dynamic reshaping of buildings energy demand