## In a glance

This module generates load profiles of demand for space heating and hot water generation for a selected region. It uses default load profiles for the residential and tertiary sector on NUTS2 level and scales it to a given demand in those sectors and provides the load profiles separated for space heating and hot water generation.

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## Introduction

Calculation of heat demand load profiles for selected regions.

## Inputs and outputs

### Input layers and parameters

• Heat density residential sector
• Heat density non-residential sector
• Gross floor area residential
• Gross floor area non-residential
• Industrial database
• Load profiles for industry
• Load profiles for residential heating
• Load profiles for tertiary heating
• Load profiles for residential domestic hot water
• Load profiles for tertiary domestic hot water

#### Provided by the user

• Residential heating factor

The residential heating demand is multiplied with this factor.

• Tertiary heating factor

The tertiary heating demand is multiplied with this factor.

• Residential hot water supply factor

The residential hot water demand is multiplied with this factor.

• Tertiary hot water supply factor

The tertiary hot water demand is multiplied with this factor.

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### Output

#### Indicators

• Heat demand by industry

Yearly heat demand by industry in the selected area.

• Heat demand by residential heating

Yearly heat required for residential heating in the selected area.

• Heat demand by residential warm water supply

Yearly heat required for residential warm water supply in the selected area.

• Heat demand by tertiary sector heating

Yearly heat required for tertiary sector heating in the selected area.

• Heat demand by tertiary sector warm water supply

Yearly heat required for tertiary sector warm water supply in the selected area.

• Total head demand

Yearly total heat required in the selected area.

#### Graphics

• Heat demand profiles

Graphic showing above listed indicators over the year. Details can be found here

#### Examples of Graphics

##### Heat demand profiles
Graphic showing the heat demand of the different sectors over the year.

The x-axis represents time and the y-axis power. It can be helpful to hide certain sectors to better see others.

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## Method

### Overview

Corresponding load profiles are assigned to industrial sites, residential and tertiary buildings in the user selection.

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### Details

#### Residential warm water supply

Based on the gross floor area of residential buildings and their Nuts0 ID the energy used for warm water supply is computed with the following list. With the Nuts2 ID of a specific area, a load profile is assigned. The residential hot water supply is multiplied with the residential hot water supply factor in case the user wants to adjust the value.

Specific energy per area for warm water supply in residential buildings in different countries

Nuts0 ID Warm water supply in kWh/m²/a
AT 21.67
BE 31.95
BG 12.93
HR 21.38
CY 8.80
CZ 22.83
DK 9.64
EE 14.35
FI 10.15
FR 9.66
DE 8.27
EL 12.51
HU 13.66
IE 15.91
IT 14.01
LV 15.71
LT 13.36
LU 8.29
MT 10.99
NL 8.91
PL 10.00
PT 9.48
RO 11.48
SK 21.51
SI 21.74
ES 23.34
SE 13.54
UK 49.03

#### Residential heating

The heat density for the residential sector is used. Since this dataset already contains the energy used for warm water, the previous computed warm water energy is subtracted from it. Based on the Nuts2 ID a residential heating profile is assigned for each tile of the heat density in the user selection. The residential heating is multiplied with the residential heating factor in case the user wants to adjust the value.

#### Tertiary warm water supply

Similar to the residential warm water supply the energy needed is computed with a table. With the Nuts2 ID of a specific area, a load profile is assigned. The tertiary warm water supply is multiplied with the tertiary hot water supply factor in case the user wants to adjust the value.

Specific energy per area for warm water supply in tertiary buildings in different countries

Nuts0 ID Warm water supply in kWh/m²/a
AT 6.57
BE 13.88
BG 15.88
HR 9.42
CY 6.26
CZ 9.18
DK 8.03
EE 14.13
FI 10.52
FR 9.57
DE 3.05
EL 6.99
HU 9.51
IE 10.87
IT 5.62
LV 7.16
LT 10.46
LU 7.20
MT 10.45
NL 6.89
PL 9.55
PT 21.47
RO 13.85
SK 8.49
SI 27.73
ES 12.44
SE 19.62
UK 13.45

#### Tertiary heating

The tertiary heating is computed similar to the residential heating. The tertiary heating is multiplied with the tertiary heating factor in case the user wants to adjust the value.

#### Industrial heat demand

The heat demand by industry is looked up the industrial database and based on the Nuts0 ID and the subsector a load profile is assigned.

#### Summation

The five resulting profiles are added together in an absolute way.

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### Implementation

The mentioned load profiles consist of 8760 points which represent the load for every hour of the 365 days. Further information about the load profiles can be found here. All load profiles are normalized so that the integral is equal to 1.

#### Industrial sites

The heat sources are taken from the industrial database. Based on their excess heat, Nuts0 ID and industrial sector a load profile covering every hour of the year is created for each site.

#### Heat densities

The heat density residential sector and heat density non-residential sector are raster files which can be found here.

#### Gross floor areas

The gross floor area residential and gross floor area non-residential are raster files which can be found here and here.

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## Sample run

Sample run in DK05.

Sample run in DK05. Only the selected blue area is considered. Graphic showing the heat demand of the different sectors over the year.

Data from this graphic can be exported by pressing the "EXPORT GRAPHS" button.

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## How to cite

Ali Aydemir and David Schilling, in Hotmaps Wiki, CM Heat load profiles (September 2020)

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## Authors and reviewers

This page is written by Ali Aydemir * and David Schilling *

• [ ] This page was reviewed by Tobias Fleiter*.

* Fraunhofer ISI Fraunhofer ISI, Breslauer Str. 48, 76139 Karlsruhe

Copyright © 2016-2018: Ali Aydemir, David Schilling

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