Positive Energy Districts

Making CityProject

Klaus Känsälä, VTT

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• +eDistrict manages its energy consumption and the energy flow

between buildings in the district and the wider energy system

• Healthy lifestyle &attractive place to live

• Positive Energy Districts have an annual positive energy balance

Definition of +eDistrict : boundaries

+eDistrict, SET concept http://smartenergytransition.fi/

Carbon-Free district vision 2050

Solar heat

collectors

Electrical

storage

Wind turbines

District heating network, temperature approx. 65 °C

Industrial heat pump

Old residential buildings with

solar PV, EVs, heat pumps and hot water storage tanks

New residential buildingswith solar PV and EVsOffice buildings,

data centers etc. with solar PV, EVs and heat pumps

Flexible bio-CHP (back-up power)

District cooling network Seasonal heat storage

School building withsolar PV

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Smart CitiesEuropean Cities

43Smart Cities portfolio

5M€

Oulu Lighthouse City

Helsinki Lighthouse City

Tampere Lighthouse CityKerava Follower City

Tampere Nature-Based

solutions Living lab

Smart City Performance

measurement system

Making City

EU 2020 Lighthouse project

22 M€, City of Oulu; City of Gröningen

Oulu: Kaukovainio• 8M€ budget ; 12.12.2018-31.12 2023

• 15000 m2;

• 200 apartments

• Supermarket

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Buildings refurbished using smart energy-efficient systems.

Demonstration of solutions like heat recovery, building energy modelling

and other advanced ICT schemes.

Combined heating and cooling energy systems introduced to reduce and

recycle heat waste

Electric vehicles and charging stations

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Main innovations: Zero Energy Block

Local heat disribution pipeline (T<60C) connecting all buildings

Heat power plant powered by solar energy, harvesting from

district heating pipeline

Local heat storages based on PCM (Phase Change Material)

Efficient use of waste energy

Supermarket used as a storage and supply for energy

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8Local District heating network T +35 / +65 °C

Old residential buildings/retrofitted with solar PV, EVs, heat pumps and hot water storage tanks

New Sivakka residential buildings with solar PV andEVs

Commercial Building

Arina with solar PV and heat recovery

District cooling network

School building with Solar

Panels

+eDistrict, best practices: Oulu case

Energy storage, ground well + heat pump

PCM tank

PCM tank

High efficiency - heat pump 250 kW nominal output

Heat recovery from City District Heating return pipe

New YIT residentialbuildings with PCMtank and EVs

+eDistrict, best practices: Oulu case

Heat distribution between the

buildings on site (Local LT Pipeline)

Solar thermal plant (270 kW

nominal output) with very low carbon

footprint

High efficiency - Heat pump

systems with CO2

Retrofitting of old building. Low

temperature distribution

Decentralized PV system

Energy storages (wells, PCM tanks)

Heat recovery from buildings and

from regional heating pipeline

Definition of +eDistrict: boundaries

10

energy use for space

heating, space

cooling, domestic hot

water, ventilation,

built-in lighting and

other technical

building systemsEnergy use of home appliances may or may not be included, countries can decide

Picture: Kurnitski J (ed) (2013) REHVA nZEB technical definition and system boundaries for nearly zero energy buildings, 2013 revision for uniformed national implementation of EPBD recast prepared in cooperation with European Standardization Organization CEN. REHVA Report No. 4, 2013. www.rehva.eu

Data collection & management

Based on open source code

platforms and DB solutions

Supports Python, AI and

machine learning tools

Provides non Vendor lock

approach to all system

components

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MySQL /MariaDB

Node.js

Nginx

HeidiSQL R-Studio

SQL

CSV

HTML

QueriesMQTT / REST API for read/write operations

Server environment

Staticfiles

-Reverse proxy-Web server

Visualisation web pages

Data storage

Off-line analytics

External import /Export tools

Web server for datamanipulation and SQL queries

Objectives: project evaluation

Robust monitoring and evaluation protocols for projectactions and interventions

Validation of PED through measurement of the performance of actions

Evaluation of the impact at 1. project level 2.city level Based on « CityKEYS » and « SCIS » -> KPI Selection -> Data Collection procedures

All performance data (i.e. KPIs) will be incorporated into SCIS database

• Strong cooperation with the lighthouse cities• https://www.smartcities-infosystem.eu/

Project level KPIs:Building and energy cluster

Reduction in annual final energy consumption

Renewable energy production

Annual CO2 emission reduction

Peak load reduction

Calculation methodology of the technical KPIsmust be checked. The basic equations mayhave to be modified depending on the case.

Project level KPIs:ICT cluster

Availability of real time data

Quality of open data

Use of standard interfaces

Improved interoperability between systems

Number of smart apps developed using open data

platforms

Project level KPIs:E-mobility cluster

Number of public EV charging stations

Renewable energy use

Annual CO2 emission reduction

kWh recharged in the EV charging stations

City level KPIs:Common city level cluster

Involvement of city administration

Number of ways in which citizens can communicate

with the municipality

Local community involvement in implementation

phase

Increase in online municipal services

Increased consciousness of citizenship

Stimulating an innovative environment

City level KPIs:Long-term effects

Interoperability of solutions

Payback period

Total investment costs vs. subsidies

Market demand

Diffusion to other locations

New forms of financing

VTT has studied the possibilities of circular energy

CASE studies covered homes, public and business buildings

Most interesting result were obtained from grocery stores

Main innovations were:• Heat pump technology for cooling/heating

• Heat dwells for energy storaging and heat generation

• CO2 used instead of F-gases; higher COP

• Renewable energy (solar&heat) used

RESULT 50% reduction in total energy consumption

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Two Shops comparison: Shop1 (2000 m2)

Shop2: 7 year older design (1750 m2)

Results:

Advanced cooling technology saves up to 50% of energy bill

In this case study the savings are 200 000 euro/year

Energy consumption was reduced to average 240 kWh/m2/year

Payback time for investment was less than two years

In Finland this supermarket chain has got 1800 shops

They consume 1.1 TWh energy annually

This could be reduced to 0.7 TWh with the new technology

Thank you, any questions?

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