Table of Contents

In a glance

This module can be run in two modes: 1)dispatch, 2)invest. In the dispatch mode, it calculates the cost-minimal operation of a portfolio of heat supply technologies in a defined district heating system for each hour of the year. The inputs to the module are hourly profiles for the heat demand in the network, for the potential heat supply from different sources and for energy carrier prices. Furthermore, cost and efficiency parameters for each technology are required. The module yields the costs of heat supply, the share of energy carriers used and the implied CO2 emissions. In the invest mode, the module optimizes the capacities of installed heat supply technologies to cover heat demand.

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Introduction

This module can be run in two modes: 1) dispatch, 2) invest. In the dispatch mode, it calculates the cost-minimal operation of a portfolio of heat supply technologies in a defined district heating system for each hour of the year. The inputs to the module are hourly profiles for the heat demand in the network, for the potential heat supply from different sources and for energy carrier prices. Furthermore, cost and efficiency parameters for each technology are required. The module yields the costs of heat supply, the share of energy carriers used and the implied CO2 emissions. In the invest mode, the module optimizes the capacities of installed heat supply technologies to cover heat demand.

The district heating supply dispatch module is a dispatch model which tries to find a cost optimum solution for covering the heat demand at every hour of the year.

concept.png

The method described here is to be understood as a first concept and can deviate from the actual implementation (model complexity, inputs and outputs, etc. must be seen from this point of view). This wiki page, explains the the version of calculation module that is integrated to the toolbox. A stand-alone version of the calculation module is much more comprehensive and can be downloaded from HERE. This version requires however, basic knowledge of python programming. The documentation of the stand-alone version can be found HERE.

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Inputs and outputs

Main inputs

The module requires a long array of input parameters. The main input parameters are however: 1. Heat demand of the grid (selected region) 1. Installed capacities of heat generators/storage 1. Technical(en-efficiencies) and financial parameters(opex,capex,lifetime) of heat generators/storages 1. Profiles (time series of the heat demand, solar radiation, temperature, electricity prices, etc..)

Main outputs

The main output indicators of the calculation module are:

  • Heat generation costs
  • Investment, operation and fuel costs
  • Heat generation mix per heat generator
  • CO2 Emissions
  • Full Load Hours,

IMPORTANT NOTE In Hotmaps biomass emissions are not assumed zero because Hotmaps is a tool aimed at supporting the ongoing energy transition. Considering biomass as a carbon-neutral source of energy implies that burning biomass reduces the current total emissions compared to burning fossil fuels, which is not true. The storage of carbon dioxide in trees happens over decades, while its release in the atmosphere takes place all at once. Therefore, the net carbon balance of biomass is zero in the long run, but not in the short run and climate change mitigation measures need to bring results in reducing carbon emissions in the short run.

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Method

The module is implemented as a linear program and can be used on the one hand as a pure dispatch model and on the other hand for investment planning to cover a load profile. The objective function tries to find the minimum of the difference from the costs for providing the heat and revenues from electricity production.

Equation fragments of the linear program:

lp_fragment.png

The total costs ctotal yield from the sum of:

investment costs IC (installed capacities multiplied by the annuities of the specific investment costs)

ic.png

captial costs CC :

cc.png

the variable costs OPEX :

opex.png

ramp costs of CHP and waste incineration plants (rough Estimation) :

ramp.png

assumed costs for the peak electrical load in the winter time (rough Estimation):

peak.png

The total revenues revtotal yield from::

the sale of electricity (for example from CHP plants and waste incineration plants).:

rev.png

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Legend

legend.png

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GitHub repository of this calculation module

Here you get the bleeding-edge development for this calculation module.

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Sample run

After you select a region and make no changes to the default parameters, the model will run in investment mode. This means that the installed capacities are also optimized for the optimal cost coverage of the heat demand.

Below you can see all input parameters that can be changed

Output Indicators

Output Charts

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How to cite

Jeton Hasani, in Hotmaps Wiki, CM District heating supply dispatch (September 2020)

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Authors and reviewers

This page was written by Jeton Hasani (EEG - TU Wien).

☑ This page was reviewed by Mostafa Fallahnejad (EEG - TU Wien).

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License

Copyright © 2016-2020: Jeton Hasani

Creative Commons Attribution 4.0 International License

This work is licensed under a Creative Commons CC BY 4.0 International License.

SPDX-License-Identifier: CC-BY-4.0

License-Text: https://spdx.org/licenses/CC-BY-4.0.html

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Acknowledgement

We would like to convey our deepest appreciation to the Horizon 2020 Hotmaps Project (Grant Agreement number 723677), which provided the funding to carry out the present investigation.

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