SmarThor Towards Energy as a Service. Wim Cardinaels

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3 SmarThor Towards Energy as a Service Wim Cardinaels

4 SmarThor Towards Energy-as-a-Service Business as Usual Communication Tourism Retail Mobility

5 SmarThor Towards Energy-as-a-Service Energy

6 II000III00II0IIIII0III00II000III0IIIII000IIIIIIIIIII000I0I0I000III00II000III0IIIII000IIIIIIIIIII000II000 III00II0IIIII0III00II000III0IIIII000IIIIIIIIIII000I0I0I000III00II000III0IIIII000IIIIIIIIIII SmarThor services EVCaaS (Electric Vehicle Charging) LaaS (light) WaaS (Washing) CaaS (Cooling) HaaS (Heating) HWaaS (Hot Water) ICT grids DC AC HCG gas inverter wind pv batteries CHP battery charger HP boiler Multi-energy optimisation ORC geothermal storage PCM

7 SmarThor Preparing a Living Lab 4G district heating & cooling grids, storage, Monitoring & Controls Regulation Electric Mobility as a Service vean MoThor MoThor MoThor EAN P4 EAN EAN EAN Central T2 IncubaT EAN sub metering EAN markets EV2 EV1 EAN Aggregator C4 TSO DSO SmarThor balance PV monitoring IoT services Meteo forecast lab server meteo station RTDS Building Mgt Syst

8 SmarThor Agenda Envisioning the Future Pieter Valkering & Erik Laes Multi-carrier Energy Markets Kris Kessels SmarThor Data Platform Klaas Thoelen

9 Envisioning Opportunities and barriers for multi-energy services in the future Flemish energy landscape Pieter Valkering Erik Laes

10 SmarThor Objective Explore the role of multi-energy services in the future energy system, given various uncertain developments Identify main opportunities and barriers Facilitate dialogue and open innovation

11 SmarThor Methodology Horizon scanning factors influencing the evolution of the Flemish energy system towards 2030 major uncertainties concerning these factors Development of four future visions on the Flemish energy system scenario-axis technique Interviews with key players in the innovation system barriers and opportunities for multi-energy innovation Innovation potential for the Thor site and beyond

12 SmarThor Energy Visions Trends & uncertainties: Energy policy Energy demand side Energy supply System integration Energy users

13 SmarThor Multi-energy services: Today Feed-in PV electricity Local use of waste heat Selling kwhrs Regional wind cooperatives

14 SmarThor Multi-energy services: Tomorrow Feed-in PV electricity Trading individual flexibility Self-sufficiency Local use of waste heat Local multi-energy communities Selling kwhrs Heating as a service Regional wind cooperatives Community Virtual Power Plants Geothermal heat

15 Interviews Helicopter viewers

16 SmarThor Opportunities and barriers Opportunities: Individual technologies largely developed challenge is integration Positive attitudes among policy and users Regulatory environment adapts (e.g. heat networks) In some case, viable business cases exist (e.g. agregation residential flex) Barriers: Perception and awareness among residential / industrial users Difficult business case (e.g. low gas price) Regulatory barriers (e.g. obligatory individual connection points, direct DC lines) Financing, uncertainties in technology and policy

17 Where are we heading? Example of Smart Energy Districts Advocates: Locally optimal solutions Lower connection capacity to the distribution grid Especially under high electrification Attractive for the socially engaged Development potential in new district development Sceptics: Slow decision-making in a community context Privileged households profit most ( Mattheus effect ) Distributed flexibility services and P2P trading more efficient? Difficult to reconcile with free choice of energy provider.

18 SmarThor Conclusions: What is needed? Enabling: Removal of regulatory barriers, alternative pricing schemes, Benefit from upscaling effects Innovation: Exploring business cases for smart energy district solutions Exploring what motivates people/businesses to engage Developing standardized planning tools, control algorithms, and platforms Dialogue: Explore and quantify potential for multi-energy solutions in Flanders

19 SmarThor Agenda Envisioning the Future Pieter Valkering & Erik Laes Multi-carrier Energy Markets Kris Kessels SmarThor Data Platform Klaas Thoelen

20 Multi-Carrier Energy Markets A Multi-Energy System Calls for Multi-Energy Market Models Kris Kessels

21 Multi-Carrier Energy Markets Context Drivers multi-carrier energy systems Climate goals: low-carbon supply Increased need for flexibility (Local) energy independence Technological developments Move toward energy services Objective Develop a multi-energy market platform so that the interaction between the energy carriers on a given level (building, industrial site, district, city, region, country, ) is optimal in terms of a certain objective.

22 Multi-Carrier Energy Markets Design challenges Physical Market Regulation Coupling of carriers (conversion technologies) Different scales (local vs. global) Different networks (network constraints!) Different trading times / practices (coupling!) Compatibility with fut. > DA > ID > RT Energy as a service Different regulations for different carriers Access to markets Free trade within MES Smart metering, settlement, (flexible) tariffs, etc. Compatible with (expected evolutions of) regulation Focus on coupling of carriers and day-ahead market

23 Multi-Carrier Energy Markets Conversion technologies and storage

24 Multi-Carrier Energy Markets Multi-carrier order types Single-carrier (i.e. existing order types) Block orders (consecutive time steps) Linked block orders, exclusive block orders, flexible hourly orders Multi- carrier (i.e. new order types) Linked multi-carrier orders Exclusive multi-carrier orders Dependent multi-carrier orders Conversion multi-carrier orders Storage orders GAS P demand 1 Q time carrier (P,Q) ELECTRICITY P supply A Q e.g. gas turbine

25 Multi-Carrier Energy Markets Implementation of multi-carrier energy market Two designs Two-step approach: a local electricity-gas-heat market before a national electricity and gas market Integrated approach: a single national electricity-gas-heat market Case study Belgian national gas and electricity markets, and a single heat market of the size of the Thor campus Reference scenario: sequential day-ahead market clearing (heat > electricity > gas)

26 Multi-Carrier Energy Markets Case study: two-step vs. integrated Option 2 chosen

27 Multi-Carrier Energy Markets Results A simultaneous day-ahead multi-carrier market is able to increase the social welfare compared to a series of sequential day-ahead markets as: It eliminates the need for price forecasting, and therefore also the associated errors that occur in sequential markets It is able to use the flexibility in one energy carrier to clear another one through multi-carrier technologies It allows for a type of order acceptance configurations that cannot be realized in a sequential market set-up

28 SmarThor Agenda Envisioning the Future Pieter Valkering & Erik Laes Multi-carrier Energy Markets Kris Kessels SmarThor Data Platform Klaas Thoelen

29 ICT: Platform, Forecasting, Smart Charging SmarThor Data Platform Klaas Thoelen

30 SmarThor Data Platform A Central One-stop Shop for Energy Data A single Web interface for often used data at EnergyVille External data Energy Markets Power Generation Forecast Weather Forecasts & Observations Internal data Building Management Systems Local Energy Production & Consumption EV Charging Stations PV Production Forecast

31 SmarThor Data Platform Goals Accelerate data-driven algorithmic research at EnergyVille Facilitate access to data, increase TRL of research deliverables Repository for multi-year, multi-feature data sets Gain insight into the energetic operation of the EnergyVille 1 building and other buildings at Thor Park, e.g.: Integrate with Building Management Systems Monitor renewable energy production Reusable ICT infrastructure for (future) research and cooperation with project partners

32 SmarThor Data Platform Control Thor Park Web Other Captor 1 Captor 2 Captor 3 Captor 4 Real-time Relational DB Table Storage D a t a A P I Application Environment Project X Project Z.1 Project Y Project Z.2 P r o j e c t A P I Project DB Monitoring & Data Viewers Operations & Billing

33 SmarThor Data Platform Use-case: Smart EnergyVille SmarThor project: from 7 to 25 charging points EV charging capacity > 500kW > capacity of electrical panel of the parking > half of the grid connection capacity of the building Thus: need for smart charging to reduce peak grid consumption Main objective for optimization: increase self-consumption of PV production

34 Hours in a day Hours in a day SmarThor Data Platform EnergyVille 1: Building Consumption vs. PV Production PV Production kW PV installation at EnergyVille 1 Total production in 2017: 228MWh Days in 2017 Grid Injection 2017 Total grid injection in 2017: 63MWh Days in 2017

35 hor PV Forecaster SmarThor Data Platform V Forecasting, PV Production Based Forecaster on Historical/Weather Precisely predict the PV production at EnergyVille 1 Next day, hourly resolution Optimize charging of electrical vehicles and heating at EnergyVille 1 eric PV Forecasting module, based on black- box machine learning approach. llation or configuration required. Only requirement: access to historical and/or weather data. (This is SmarThor data platform.) n, that is not tailored to specific hardware. o account impact of specific local circumstances (shadow, azimuth, gradient) and panel-specific properties inverter output, ) homes and/or larger installations. Test-Case EnergyVille: PV power predictions for a 24-hour window, Data-driven expert system: 1. Historical PV production data 2. Irradiance predictions for nearby sites 3. Numerical weather predictions

36 SmarThor Data Platform Posters & Demos

37 Questions? Introduction Envisioning the Future Multi-carrier Energy Markets Welcome to our poster sessions in the labs! Take your belongings with you We do not come back to Thor Central SmarThor Data Platform

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39 Eager to find out more? The scientific publications developed during the project can be found using the QR-code on the posters