---
# System prepended metadata

title: 'WP3, D3.1 - 1st Iteration'
tags: [usefleds]

---

# USEFLEDS: WP3, D3.1 - 1st Iteration

**Content:**
* [Partners](#Partners)
    * [FH Bgld](#FH-Burgenland), [4er](#4ward-Energy), [Advoodle](#Advoodle), [Campus02](#Campus02), [EnergySrv](#Energy-Services), [Kelag](#KELAG), [Nexyo](#Nexyo), [Onlim](#Onlim), [Salzburg AG](#Salzburg-AG), [Salburg Netz](#Salzburg-Netz), [Salzburg Research](#Salzburg-Research), [Scheiber](#Scheiber-Solutions), [SDA](#Sustainable-Data-Agency-Alexander-Steger), [TU Wien](#TU-Wien), [OYD](#OwnYourData)
<!--* [Use Case Proposals](#Use-Cases)
    * [Flexible Tarifs](#Flexibe-Tarifs), [Energy Flow Optimization](#Energy-Flow-Optimization), [ESG Reporting](#ESG-Reporting)-->
* [Documents](#Documents)
    * [Data Flow Specification](#D31-Data-Flow-Specification)
    * [Requirements Document](#D32-Requirements-Dokument)

### 1st round of meetings
- [x] FH Burgenland: Dec 19, 2023 10:00
- [x] 4ward Energy: Dec 20, 2023 14:00
- [x] KELAG: Jan 5, 2024 10:00
- [x] Salzburg AG: Jan 8, 2024 13:00
- [x] Campus02: Jan 9, 2024 09:00
- [x] TU Wien: in-person @TUW Jan 11, 2024 9:00
- [x] Nexyo: Jan 12, 2024 10:00
- [x] Salzburg Netz: Jan 15, 2024 10:00
- [x] Energy Services: Jan 15, 2024 14:00
- [x] Salzburg Research: Jan 19, 2024 10:00
- [x] Advoodle: Jan 22, 2024 14:00
- [x] Alexander Steger, Jan 22, 2024 15:30
- [x] Onlim: Jan 26, 2024 10:00

### Follow-up meetings
- [x] Data Intermediary: Jan 23, 2024 15:30
- [x] Scheiber Solutions: Jan 24, 2024 14:00
- [x] KELAG: Jan 24, 2024 15:30
- [x] TU Wien: Jan 25, 2024 9:00
- [x] Campus02: Jan 29, 2024 11:30

-> Summary available here: https://hackmd.io/dtJS4G0cSC6clQdwR7lCWA?view
-> User Stories here: https://hackmd.io/n_uO5dZqSP-U1pE556Zs9Q

## Partners

### FH Burgenland
Contact: christoph.klikovits@forschung-burgenland.at
(organisation: silke.palkovits-rauter@fh-burgenland.at)
Role: consortium lead, WP1 lead, WP7 lead, WP8 lead
Type: domain & technical partner
<!--
Use Cases:
* primary: Flexible Tarifs
* Energy Transition (Markus P. & Christian P.)
* Sustainable Innovation & Digitalisierung (Christoph K.)
* Building Technology (optional)
-->
Data for Energy Transition (create opportunities):
* Have
* Need
    * network utilization from grid providers
* Process
* Interprete

Stakeholder:
* institutions/organisations (e.g., FH)
* private person
* agriculture
* industry
* energy provider
* grid provider

Data Space Tools
* [Dataspace Management Vision Demonstrator](https://www.figma.com/proto/hVkvoEmzIqo33JE9KEpk4G/Dataspaces?page-id=15%3A167&node-id=15-6403&viewport=3072%2C438%2C0.16&scaling=min-zoom&starting-point-node-id=15%3A6403&show-proto-sidebar=1)
    * [Github Link](https://github.com/eclipse-edc/MinimumViableDataspace/blob/main/Vision%20Demonstrator/Vision%20Demonstrator%20Introduction.md) 

Dataflow:
* extisting
    * not yet
* future
    * planned energy monitoring for Landesholding Burgenland
    * local communities (Gemeinden): Netzauslastung --> Netzausbau
        * PV farms, wind,... decentralised infrastructure of grid
        * plan for network expansion
    * mobility: students traveling to university
        * try in FH (Fachhochschule) & FB (Forschung Burgenland daughter FH)

![image](https://hackmd.io/_uploads/HJQrrrKd6.png)
![image](https://hackmd.io/_uploads/Sy1UHBYda.png)


Meetings:
* 11.Nov23: SSI, partner structure, data spaces
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 19.Dez23: collect DataFlow inputs
* 8.Jan24: Data Intermediaries
* 23.Jan24: Data Intermediaries II

### 4ward Energy
Contact: johanna.ganglbauer@4wardenergy.at
(organisation: 4er@forschung-burgenland.at)
Role: WP4 lead
* E-Werk Franz - https://www.ewg.at/ (energy provider + distribution system operator (DSO) in Graz <- collaborate with Energy Services on Use Case
* Energy Services: smart meter management, billing, trading electricity
Type: research partner
<!--primary Use Case: ??? (Salzburg: collaborate on use case development) -->
Data: first 2 iterations for scoping and last 2 iterations focused on selected use cases (more practical)

* Have
    * to be provided through Energy Services, might be through E-Werk Franz
    * already collected data from previous research projects
* Need
    * smartMeter Data - from customers (yearly -> 15min resolution)
        * data only available on the next day
        * expected problems: internet connections to private customers
    * weather data: historic, now, forecasts (global irradiation -> PV), temperature, wind speed, precipitation
    * per consumer / better: per device: current consumption / current generation <- should be real time data (15min is too coarse grained)
        * including forecasts
        * load profile generator: https://www.loadprofilegenerator.de/
    * energy tarifs: economic aspects, device data (type, specs)
    * current time resolution is not enough right now (example: only yearly billing)
* Process
    * access data available in Energy Data Space
* Interprete
    * focus is on initial selection of use cases

Stakeholders:
* EDA GmbH
* Energy Services
* providers and users of 
  * storage (battery)
  * power inverter
  * photovoltaics
* energy management system (HW+SW -> Loxone: https://www.loxone.com/)
* E-charging stations
* heat pumps
* distribution grid operators (200+ in Austria)
* customers / private households <- are they data provider or do they only consent to providing data?
* GeoSphere Austria / "Energy & Meteo" for MET data

Data Flows:
* existing
    * EDA -> check processes: https://www.eda.at/
      experts: Energy Services
    * GeoSphere Austria: MET
    * maybe: Energy & Meteo - https://www.energymeteo.com/
    * read device data using MQTT, OPC-UA, REST APIs
* future
    * live data metering (electricity, gas, heat)

Meetings:
* 7.Dez23: Salzburg Kick-off (talk after world café)
* 20.Dez23: WP3-WP4 Coordination

### Advoodle
Contact: andreas.boecskoer@advoodle.com
(organisation: advoodle@forschung-burgenland.at)
Type: domain partner + technical parts (Blockchain, AI)
Role: Legal / Governance Support ("translator" between technology & law incl. visualisations)
primary Use Case: ESG Reporting

**Data**
* European supply chains
* CSRD - [Corporate Sustainability Reporting Directive](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32022L2464)
  * includes documentation of strategies/outlook for the future; financial & non-financial impact of individual measures
  * double materiality check ("Materialitätsprüfung") with regard to data exchange in the energy industry
  * ESRS - European Sustainability Reporting Standards ([overview: figure 3](https://kpmg.com/at/de/home/insights/2022/11/acnews/einigung-zur-csrd.html))
* Reporting: ESEF (European Single Electronic Format) standard for financial reporting (could be extended to non-financial reporting / CSRD reporting)
* general Data Governance
  * data ownership
  * data protection
  * liability
  * regulatory governance

**Stakeholder**
* consortium is already well positioned in the area of data
* individual connectors might be necessary

**Data flows**
* link energy data with carbon emissions (more generally: GHG - Green House Gases)
* standardisation of data exchange

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 22.Jan24: 14:00 WP3 first call

### Campus02
Contact: stefanie.hatzl@campus02.at
(organisation: campus02@forschung-burgenland.at)
Role: WP2 lead
Type: domain partner
Meetings:
* 7.Dez23: Salzburg Kick-off (co-host at table)
* 9.Jan24: Co-creation Workshop Prep
* 29.Jan24: Co-creation Workshop Prep II
* 1-2.Feb24: Co-creation Workshop @ FH Bgld

### Energy Services
Contact: Nicole.Wieser@energy-services.at
(organisation: energyservices@forschung-burgenland.at)
Role: WP7 lead (Aggregation & Evaluation) & collaboration with 4ward Energy
**Type:** domain partner (electricity, covers all market roles: supplier, network operator, system operator, energy service provider - as defined in the law)
* EDM (Energy Data Management) software is made available during the project

**Use Case:** Energy Flow Optimization
* end user with smartMeter / smart Devices
* network operator and energy supplier ([E-Werk Franz](https://www.ewg.at/)) - also feeds in via PV system
* data in EDM (in-house developed and maintained by Energy Services)

**Daten:**
* clear focus on all data managed by [Energiewirtschaftlicher Datenaustausch](https://www.eda.at/?lang=en) EDA.at 
* weather data from MetGIS (established contact with Energy Services)

**Stakeholder:**
* be aware that many organisations / company wear multiple hats (example: private company E-Werk Franz)

**Dataflows / Prozesse** - defined through the following establied services:
* data hub: https://www.eda.at/
* interfaces: https://www.ponton.de/eda-how-does-it-work
* data models: https://www.ebutilities.at/schemas/

new releases twice a year as defined on https://www.ebutilities.at

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 15.Jan24: first WP3 Call

### KELAG
Contact: hannes.guetler@kelag.at
* Weisskircher Florian (Vertrieb)
* Zwatz Florian (Handel)

(organisation: kelag@forschung-burgenland.at)
Role: data provider
Type: domain partner
Use Case: Flexible Tarifs
* Requirements for energy communities (with regard to energy transition)
* Example Obertauern (80% hotels)
* Data sharing

**Data** for Energy Transition (leverage opportunities):
* L-Band Satelliten: verfügbare Schnee/Wassermenge (ENEO)
  * check: https://www.enveo.at/
  * for predictive maintenance
* problem with consumer data from smartMeter (resolution: 15min interval)
  reliability: if data is missing, how are replacement values generated?
    essential driver for day-to-day business is having all data available: relevant for every tariff that is to be billed using current SmartMeter values (especially on Austrian scale)
    (if a single value is missing in an energy community - then the whole system stops)
* electricity generation (including heat & gas) - theoretically available in real time
  * Abrechnungsperiode ist 15min
  * Gas: Speicherstände
* KELAG produces 100% from renewables; and buys 100% green electricity (i.e. electricity with certificates for green electricity)
  * disclaimer: only the sum of supply and the sum of consumers matches - but physically electricity may still be delivered from a caloric power plant

**Stakeholders within KELAG:** Trade, Sales, Production

**Dataflows**
* existing
  * there is no existing data exchange through data spaces in KELAG yet (only data exchange with Open Data)
* future
  * energy requirements (electricity, gas, heat) can be well estimated per year; not so easy are estimations on a more fine grained level
    * relevant to know is the form of heating: for a full service it would be interesting to know e.g. gas consumption
    * the more information about the customer is available (age, income situation, single/family, which heating system, e-mobility) the better customers can be serviced, the better tailored products can be developed
    * flexibility & storage: if the customer has an electric car to store electricity -> the customer has the opportunity to behave in a "system-serving" way (electricity provider manages car battery)
      * the desire is to start a campaign that only targets those with these capabilities addresses
      * data to generate personas / develop customer segments precisely
    * Weather data: forecasts for smaller regions (relevant for heating in winter, generating PV electricity); if I know how heating is done / what heating requirements are / the situation of the building, it has a specific profile that can be taken into account: link from existing weather data to sales profiles
      * with an available weatherforecast the power consumption of a heat pump can be better modeled
  * Data exchange for trade department
    *  Copernicus / ESA data for risk analysis (100-year probabilities for extreme events)
    * Intraday trading is part of daily business
    * real smartMeter data would enable better planning for day-to-day business -> possible future scenario (better forecasts, less uncertainty)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 5.Jan24: first WP3 Call
* 24.Jan24: 2nd WP3 Call

### Nexyo
Contact: anna.cossa@nexyo.io (CC: andreas.krimbacher@nexyo.io)
(organisation: nexyo@forschung-burgenland.at)
Role: data spaces, policies, governance, enable data sharing, hosting of a Data Space (check out: [Building Data Spaces in 4 Steps](https://drive.google.com/file/d/1YbYkcrPeJwd-pFEpa9SEviIvRPzQb_G7/view?usp=drive_link))
Type: technology partner
Use Case: ESG Reporting and support other use cases with data sharing through technology support and consulting (recommend: C4 modelling - https://c4model.com/)

Input for State-of-the-art:
- DTS Endreport (https://project-dts.eu/)
- Champions (https://www.champi40ns.eu/en/)

**Data**
* power consumtion (in various granularities)
* carbon footprint (in regard to ESG Reporting)
* climate & weather
* raw materials: calorific value, impact on (carbon) footprint
* population data (Statistik Austria)
* tourims: occupancy of hotels / overnight stays
* power consumption of industry
* transport routes
* economic data (clusters for ESG reporting - SMEs not affected by ESG); also: forecasts for economic development

**Stakeholders:** (beyond consortium that could be relevant)
* GeoSphere (provider of climate and weather data)
* ASFINAG: traffic information
* mobile operator (proxy for energy consumption)
* international multipliers -> how to bring the results to the European level

**Data Flows**
* existing: 
  * Standardization of power consumption data
  * E-Control: a vailability of e-charging stations (https://www.ladestellen.at/#/electric)
* future:
  * Consumption data for ESG reporting (Scope 1&2 data)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 12.Jan24: collect DataFlow inputs

### Onlim
Contact: ioan.toma@onlim.com
(organisation: onlim@forschung-burgenland.at)
Role: Conversational AI, Knowledge Graphs
Type: technology partner (spin-off University of Innsbruck)
Use Case: ESG Reporting <- focus

Data: Onlim is data processor but not a data provider
* open questions how to access relevant data
* focus on real data, for testing & benchmarking also synthetic data could be possible

Stakeholder:
* LLM: use Azure instance from OpenAI -> with the goal to host it locally

Data Flows (available tool: https://app.onlim.com/, commercial product)
* modelling & describing data, mapping data from multiple data sources
* data enrichment and interlinking
* integrate with other data (apps & actions) to build data flows / data pipelines
  * flow editor to visually connect components
* LLM for data extraction and extending knowledge graphs
* enventually making the data accessible in conversational AI

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 26.Jan24: WP3 Dataflows

### Salzburg AG
Contact: stefanie.kritzer@salzburg-ag.at
(organisation: SalzburgAG@forschung-burgenland.at)
Role: data provider, evaluate use case & selection of services (to be developed during project)
Type: domain partner (market participant in energy market)
Use Case:
* economic considerations: parallel existence of Salzburg AG & Salzburg Netz
* linking energy provider and networks
* predictive maintenance

**Data:**
* external data to enrich own data
* energy & heat production -> general and per plant and per hour incl. sensor data
* market prices (note: sales department of Salzburg AG is not part of the project but enough know-how available through Stefanie Kritzer)
* network load / grid voltage
  * aggregated data for each tarif group -> to answer the question "at what point do I need how much electricity?"
  * consumption profile data from industry customers
  * synthetic data from small consumers might be outdated
  * changes because auf PV systems
  * e-mobility
* more / better weather data allow for better prediction on consumption
* labeling of electricity
  * Salzburg produces about 50% -> green electricity
  * and buyes the rest -> grey electricity
  * the resulting trade with carbon certificates is static / defined legal situation
* gas is still very much relevant for heat production

**Stakeholder:**
* energy providers
  * sales
* sales
* distribution system operators (grid providers)
  * major network operator in Austria: APG (Austria Power Grid)
* small / medium / big consumer
  * synthetic profiles
  * ski areas - check [end report from CleanEnergy4Tourism](https://drive.google.com/file/d/1ijWEcn2vFHOBlflzId9Ha57P9n1YqkmL/view?usp=drive_link)
* cell phone data (A1, ...)
* electricity sales data
* energy storage technology

**Existing Dataflows:**
* E-Control
* Electricity Market
  * EEX (European Energy Exchange): for long-term trades
  * EPEX (European Power Exchange): spot markets (focused on day-ahead and intrday trade)  
  * https://www.eex-transparency.com/de/power/at/produktion/verfuegbarkeit
  * energy provider need to report availability of power plants and levels of water storage power plants (also to avoid insider trade)
    * report of all commercial transactions
    * timetables for power plants
* weather forecasts

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 8.Jan24: WP3 Dataflows

### Salzburg Netz
Contact: dorina.vogel@salzburgnetz.at
(organisation: SalzburgNetz@forschung-burgenland.at)
Role: data provider, evaluate use case
Type: domain partner
primary Use Case: Energy Flow Optimization (example: Gasteiner Tal - Anger-Tal Umspannwerk)
- [ ] Dorina: end report from recent research project

**Data**
Comment: Salzburg Netz reserved some budget to buy external data (to show added value from linking external data and have creative/new ideas on using data in new ways)
* Cellular data for better planning/predictions
* Network load planning (short-term and long-term)
  depends on a fine-granular level on use of e-mobility, heat pumps, photovoltaic, etc.
* Types/divisions in Salzburg Netz
  * electricity
  * gas
  * district heating
* power consumption per consumer is regulated
  * single-family home restricted to 4kW
    necessary to increase for photovoltaic installation
  * mountain railways / ski lifts: much higher and they pay peak values instead of average consumption
  * smartMeter data not yet integrated in Salzburg Netz
    roll-out at about 80% now
  * load profile counters in use for companies
* Salzburg Netz Subsidiaries that might provide other relevant data
  * Salzburg Verkehr (buses)
  * Schafsbergbahn
  * Wolfgangssee-Schifffahrt
* data exchange between network provider and energy produces might be problematic since this is sensitive data
  example: energy provider has 400 customers but network provider has information about 700 endpoints
  Salzburg Netz is subject to strict monitoring, but has no competitors; nevertheless, Salzburg AG & Kelag are not allowed to benefit from the Salzburg Netz data! -> one possible solution is to make data public / available to everyone


Relevant / possible stakeholder beyond consortium:
* Asfinag, A1
* Google, Booking.com, Social Media (FB, X, Instagram)
* weather data (also search queries from tourists might be relevant)
* Public transport company (ÖBB); Ski train in Gastein

Dataflows
* electricity grid: network maintenance at different levels - plans for first 5s, 20s and 2minutes
* E-cars as electricity storage
  * [ ] Dorina: reference to latest standard
* better predictions through tourism data: ski tickets sales, publlic transport utilization, booking situation at hotels, traffic jams (Asfinag)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 15.Jan24: WP3 Dataflows

### Salzburg Research
**Contact:** peter.dorfinger@salzburgresearch.at
(organisation: srfg@forschung-burgenland.at)
**Role:** WP6 lead (AI Integration) - use case implementation / development of AI algorithms for use cases
**Type:** research partner (incl. developing prototypes)
focus on Salzbuzrg AG & Salzburg Netz (Salzburg cluster)
**Data:**
* processing, interpretation; demonstration of possibilities with AI
* improve forecasts for power grid, e.g., Gasteinertal/Angertal
  * measures in critical siutation
  * evaluate if and how much improvement is possible
* planned data processing from Salzburg AG, Salzburg Netz, and beyond
  * time series data from electricity consumption
  * historical power plant schedules
  * weather, tourism, mobile carriers
  * demand forecast based on consumption data (snow cannon) for edge cases; identify pivot elements based an availability and price of data
  * economic consideration of the whole energy system (previously only economic consideration of the individual stakeholders)

**Stakeholder:**
* energy providers (including private feeders, small power plants, local energy communities)
* grid operators
* large consumers (mountain railways, tourism companies)
* weather data providers, mobile operators
* mobility service providers: ÖBB, shuttle buses, taxis

**Dataflows:**
* existing:
  * EDA
* future:
  * new forms of data exchange are necessary for our project -> establish of cross-organizational data sharing (sharing public data alone does not forn a data space)
  * enabling data exchange beyond established trust boundaries (through incentives, new legal frameworks)

**Meetings:**
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 19.Jan24: 10 Uhr (Peter, Nina)

### Scheiber Solutions
contact: [lucas.scheiber@scheiber.solutions](mailto:lucas.scheiber@scheiber.solutions)
(organisation: scheibersol@forschung-burgenland.at)
Role: Umsetzung von Use Cases mit Lösungen von Scheiber Solutions (KI Prognose für die nächsten 7 Tage)
Type: technology partner
Use Cases:
* primary: Energy Flow Optimization (load management in power grids)
* decentral and flexible tarifs
* privacy & GDPR

Data:
* EDA data pool for everyone with smartMeter
* data disaggregation for H0 (consumption profile for households; E0 is profile from PV production) -> Link to Salzburg AG
* already use data models from FIWARE and SmartCity research projects

Stakeholder:
* decentralization / energy communities: focus on regional context & effects on higher levels

Data flows:
* local energy consumption as provided by smartMeters (averages out at a higher level)
  * but: in a decentralized market, energy is consumed locally, which is then suddenly no longer available at a higher level
* awareness for producers about how electricity consumption is developing
* automation for operating intelligent charging stations


Meetings:
* 24.Nov23: available products & goals
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 24.Jan24: WP3 Data Flows

### Sustainable Development Agency (Alexander Steger)
Contact: [alex@sda.tirol](mailto:alex@sda.tirol)
(organisation: sda@forschung-burgenland.at)
Role: introduces ESG Reporting use case to consortium
Type: domain partner
Use Case: ESG Reporting (automated data exchange)
  * as introduced by European Green Deal
  * reduce effort to aggregate data which is relevant for ESG Reports
  * re-use data for similar activities (join Klimabündnis, request credit/ÖKB)

**Data** (in regard to ESG Reporting use case)
* currently heterogeneous input data (PDF, Excel, images)
* standardised formats for energy and water consumption, ground sealing
* necessary data depends heavily on customer
  * focus on simple scenarios to begin with
  * develop personas
* existing ESG Hub from ÖKB

**Stakeholder**
* Tourism
* ÖKB - Österreichische Kontrollbank, https://www.oekb.at/ (ESG Data Hub)
* Consultants
* WKO, DIO - for authentication
* Akaryon - ESG Cockpit

**Dataflows**
* harmonizing input and results to avoid discrepancies (example: high variety in carbon emissions reports)
* retrieve data along suplly chain (highly specified data, like country of origin, packaging, transport of goods)
* expected steps
  1. data collection
  2. data processing and development of a strategy
  3. reporting and certificates
  4. implementation and improvements
* overall goal: end-to-end solution of an automated consolidation and distribution tool

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 22.Jan24: WP3 Data Flows

### TU Wien
Contact: thomas.preindl@tuwien.ac.at
(organisation: tuwien@forschung-burgenland.at)
Role: WP5 lead
- ASG working group
  - Working on modeling and system architecture
- TU Vienna
  - Possibly stakeholders
  - Buys electricity on the stock exchange
  - obtains heat from Vienna Energy
  - has many customers internally that need to be coordinated

Type: technology partner
Stakeholder:
- ASG
  - Anyone who has anything to do with the energy grid
- TU Vienna
  - Central shopping
  - Faculties, institutes and working groups
  - Network provider
  - Optimization service providers
  - Data aggregators
  - Data collection service providers

WP3 Collaboration:
* State-of-the-art
* Ontologoy Visualization: https://github.com/VisualDataWeb/WebVOWL


**Data**
* on flexible tariffs: basic power (e.g. 3kW) is guaranteed, more needs to be paid extra
* increased decentralization can lead to 2 developments
  * grid operator collects data and controls consumers
  * so called "aggregators" collect data (example: neoom.com, efriends.at)
    * requires more data
    * interesting question how to switch between aggregators
  * relevant data: e-car, PV, battery, heat pump, ... on different levels (have/not have -> capacity -> profile & capabilities -> live data)

**Dataflows**
* Data Space sense-making: [Data Space Business Alliance - Technical Convergence](https://drive.google.com/file/d/1y9LPiA-Rfw7IACe5ogNpLs3zCalvP7Vf/view?usp=drive_link)
* resilient architecture for decentralized planning of the schedules of small feeders -> establish energy community in Burgenland:
  * protocol: ModBus (https://en.wikipedia.org/wiki/Modbus) and data models from Sunspec (https://sunspec.org/)
  * collects data and stores in FIWARE
  * investigate social compatibility
  * types of energy communities: 
    * local (level 6 - grid behind trafostation)
    * regional (level 5 - grid behind substation "Umspannwerk")
      -> focus on economic cooperation and saving network costs
  * example: Neoom (https://neoom.com/) with accesses to inverters & storage to make intra-day trades

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 11.Jan24 9:00 @TU Wien
* 25.Jan24 9:00 @TU Wien

### OwnYourData
Contact: christoph.fabianek@gmail.com
(organisation: ownyourdata@forschung-burgenland.at)
Role: WP3 lead
Type: technology partner

<!--
## Use Cases

### Flexibe Tarifs

### Energy Flow Optimization

### ESG Reporting
-->
## Documents

### D3.1 Data Flow Specification
1. Introduction
2. Stakeholder
3. User Stories
4. Data Sources
5. Functional Components
6. Data Flows
7. Conclusions

### D3.2 Requirements Dokument
1. Introduction 
2. Motivation and Planned Functionalities
3. Requirements
    * Non-functional Requirements
    * Functional Requirements 
4. Business Aspects and Governance
5. Use Case Analysis
6. Conclusions