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doc/supply_demand.rst
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@ -55,6 +55,7 @@ Further information are given in the publication :
`Mitigating heat demand peaks in buildings in a highly renewable European energy system, (2021) <https://arxiv.org/abs/2012.01831>`_.
*Water heating*
Hot water demand is assumed to be constant throughout the year.
*Urban and rural heating*
For every country, heat demand is split between low and high population density areas. These country-level totals are then distributed to each region in proportion to their rural and urban populations respectively. Urban areas with dense heat demand can be supplied with large-scale district heating systems. The percent of urban heat demand that can be supplied by district heating networks as well as lump-sum losses in district heating systems is exogenously determined in the `Config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L153>`_.
@ -105,9 +106,11 @@ The methane CHP is modeled on the Danish Energy Agency (DEA) “Gas turbine simp
NB: The old PyPSA-Eur-Sec-30 model assumed an extraction plant (like the DEA coal CHP) for gas which has flexible production of heat and electricity within the feasibility diagram of Figure 4 in the study by `Brown et al. <https://arxiv.org/abs/1801.05290>`_ We have switched to the DEA back pressure plants since these are more common for smaller plants for biomass, and because the extraction plants were on the back pressure line for 99.5% of the time anyway. The plants were all changed to back pressure in PyPSA-Eur-Sec v0.4.0.
*Micro-CHP*
Pypsa-eur-sec allows individual buildings to make use of `micro gas CHPs <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L236>`_ that are assumed to be installed at the distribution grid level.
*Heat pumps*
The coefficient of performance (COP) of air- and ground-sourced heat pumps depends on the ambient or soil temperature respectively. Hence, the COP is a time-varying parameter[refer to `Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L206>`_ file). Generally, the COP will be lower during winter when temperatures are low. Because the ambient temperature is more volatile than the soil temperature, the COP of ground-sourced heat pumps is less variable. Moreover, the COP depends on the difference between the source and sink temperatures:
$$ &Delta; T = T_(sink) − T_(source) $$
@ -120,23 +123,32 @@ for ground-sourced heat pumps (GSHP), we use the function:
$$ COP(&Delta; T) = 8.77 + 0.150&Delta; T + 0.000734&Delta; T^2 $$
• Resistive heaters (can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ option)
*Resistive heaters*
Can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ option
Resistive heaters produce heat with a fixed conversion efficiency (refer to `Technology-data repository <https://github.com/PyPSA/technology-data>`_ ).
• Gas, oil, and biomass boilers (can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ , `oil boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L233>`_ , and `biomass boiler <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L234>`_ option)
*Gas, oil, and biomass boilers*
Can be activated in Config from the `boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L232>`_ , `oil boilers <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L233>`_ , and `biomass boiler <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L234>`_ option.
Similar to resistive heaters, boilers have a fixed efficiency and produce heat using gas ,oil or biomass.
• Solar thermal collectors (can be activated in the Config file from the `solar_thermal <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L237>`_ option)
*Solar thermal collectors*
Can be activated in the Config file from the `solar_thermal <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L237>`_ option.
Solar thermal profiles are built based on weather data and also have the `options <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L134>`_ for setting the sky model and the orientation of the panel in the Config file, which are then used by the atlite tool to calculate the solar resource time series.
• Waste heat from Fuel Cells, Methanation and Fischer-Tropsch plants
*Waste heat from Fuel Cells, Methanation and Fischer-Tropsch plants*
Waste heat from `fuel cells <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L256>`_ in addition to processes like `Fischer-Tropsch <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L255>`_ , methanation, and Direct Air Capture (DAC) is dumped into district heating networks.
*Existing heating capacities and decommissioning*
For the myopic transition paths, capacities already existing for technologies supplying heat are retrieved from `“Mapping and analyses of the current and future (2020 - 2030)” <https://ec.europa.eu/energy/en/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment>`_ . For the sake of simplicity, coal, oil and gas boiler capacities are assimilated to gas boilers. Besides that, existing capacities for heat resistors, air-sourced and ground-sourced heat pumps are included in the model. For heating capacities, 25% of existing capacities in 2015 are assumed to be decommissioned in every 5-year time step after 2020.
*Thermal Energy Storage* (Activated in Config from the `tes <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L228>`_ option)
*Thermal Energy Storage*
Activated in Config from the `tes <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L228>`_ option.
Thermal energy can be stored in large water pits associated with district heating systems and individual thermal energy storage (TES), i.e., small water tanks. Water tanks are modeled as `stores <https://pypsa.readthedocs.io/en/latest/components.html?highlight=distribution#store, which are connected to heat demand buses through water charger/discharger links>`_.
A thermal energy density of 46.8 kWhth/m3 is assumed, corresponding to a temperature difference of 40 K. The decay of thermal energy in the stores: 1-exp(-1/24τ) is assumed to have a time constant of  t=180 days for central TES and  t=3 days for individual TES, both modifiable through `tes_tau <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L229>`_ in Config file. Charging and discharging efficiencies are 90% due to pipe losses.
@ -346,15 +358,15 @@ Transportation
=========================
Annual energy demands for land transport, aviation and shipping for every country are retrieved from `JRC-IDEES data set <http://data.europa.eu/89h/jrc-10110-10001>`_. Below, the details of how each of these categories are treated is explained.
Land transport
-----------------
*Land transport*
*Aviation*
Aviation
-----------------
The `demand for aviation <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L2193>`_ includes international and domestic use. It is modeled as an oil demand since aviation consumes kerosene. This can be produced synthetically or have fossil-origin [link to oil product].
Shipping
-----------------
*Shipping*
Shipping energy demand is covered by a combination of oil and hydrogen. The amount of oil products that are converted into hydrogen follow an `exogenously defined path <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L198>`_. To estimate the `hydrogen demand <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/scripts/prepare_sector_network.py#L2089>`_, the average fuel efficiency of the fleet is used in combination with the efficiency of the fuel cell defined in the technology data. The average fuel efficiency is set in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L196>`_.
The consumed hydrogen comes from the general hydrogen bus where it can be produced by SMR, SMR+CC or electrolysers [link to hydrogen]. The fraction that is not converted into hydrogen use oil products, i.e. is connected to the general oil bus.