266 lines
14 KiB
ReStructuredText
266 lines
14 KiB
ReStructuredText
.. _supply_demand:
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##########################################
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Supply and demand
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##########################################
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An initial orientation to the supply and demand options in the model
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PyPSA-Eur-Sec can be found in the description of the model
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PyPSA-Eur-Sec-30 in the paper `Synergies of sector coupling and
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transmission reinforcement in a cost-optimised, highly renewable
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European energy system <https://arxiv.org/abs/1801.05290>`_ (2018).
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The latest version of PyPSA-Eur-Sec differs by including biomass,
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industry, industrial feedstocks, aviation, shipping, better carbon
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management, carbon capture and usage/sequestration, and gas networks.
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The basic supply (left column) and demand (right column) options in the model are described in this figure:
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.. image:: ../graphics/multisector_figure.png
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Electricity supply and demand
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=============================
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Electricity supply and demand follows the electricity generation and
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transmission model `PyPSA-Eur <https://github.com/PyPSA/pypsa-eur>`_,
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except that hydrogen storage is integrated into the hydrogen supply,
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demand and network, and PyPSA-Eur-Sec includes CHPs.
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Unlike PyPSA-Eur, PyPSA-Eur-Sec does not distribution electricity demand for industry according to population and GDP, but uses the
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geographical data from the `Hotmaps Industrial Database
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<https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database>`_.
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Also unlike PyPSA-Eur, PyPSA-Eur-Sec subtracts existing electrified heating from the existing electricity demand, so that power-to-heat can be optimised separately.
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The remaining electricity demand for households and services is distributed inside each country proportional to GDP and population.
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Heat demand
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=============================
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Heat demand is split into:
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* ``urban central``: large-scale district heating networks in urban areas with dense heat demand
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* ``residential/services urban decentral``: heating for individual buildings in urban areas
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* ``residential/services rural``: heating for individual buildings in rural areas, agriculture heat uses
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Heat supply
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=======================
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Oil and gas boilers
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--------------------
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Heat pumps
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-------------
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Either air-to-water or ground-to-water heat pumps are implemented.
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They have coefficient of performance (COP) based on either the
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external air or the soil hourly temperature.
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Ground-source heat pumps are only allowed in rural areas because of
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space constraints.
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Only air-source heat pumps are allowed in urban areas. This is a
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conservative assumption, since there are many possible sources of
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low-temperature heat that could be tapped in cities (waste water,
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rivers, lakes, seas, etc.).
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Resistive heaters
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--------------------
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Large Combined Heat and Power (CHP) plants
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--------------------------------------------
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A good summary of CHP options that can be implemented in PyPSA can be found in the paper `Cost sensitivity of optimal sector-coupled district heating production systems <https://doi.org/10.1016/j.energy.2018.10.044>`_.
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PyPSA-Eur-Sec includes CHP plants fuelled by methane, hydrogen and solid biomass from waste and residues.
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Hydrogen CHPs are fuel cells.
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Methane and biomass CHPs are based on back pressure plants operating with a fixed ratio of electricity to heat output. The methane CHP is modelled on the Danish Energy Agency (DEA) "Gas turbine simple cycle (large)" while the solid biomass CHP is based on the DEA's "09b Wood Pellets Medium".
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The efficiencies of each are given on the back pressure line, where the back pressure coefficient ``c_b`` is the electricity output divided by the heat output. The plants are not allowed to deviate from the back pressure line and are implement as ``Link`` objects with a fixed ratio of heat to electricity output.
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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 `Synergies paper <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.
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Micro-CHP for individual buildings
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-----------------------------------
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Optional.
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Waste heat from Fuel Cells, Methanation and Fischer-Tropsch plants
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-------------------------------------------------------------------
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Solar thermal collectors
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-------------------------
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Thermal energy storage using hot water tanks
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---------------------------------------------
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Small for decentral applications.
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Big water pit storage for district heating.
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.. _retro:
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Retrofitting of the thermal envelope of buildings
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===================================================
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Co-optimising building renovation is only enabled if in the ``config.yaml`` the
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option :mod:`retro_endogen: True`. To reduce the computational burden
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default setting is
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.. literalinclude:: ../config.default.yaml
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:language: yaml
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:lines: 134-135
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Renovation of the thermal envelope reduces the space heating demand and is
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optimised at each node for every heat bus. Renovation measures through additional
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insulation material and replacement of energy inefficient windows are considered.
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In a first step, costs per energy savings are estimated in :mod:`build_retro_cost.py`.
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They depend on the insulation condition of the building stock and costs for
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renovation of the building elements.
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In a second step, for those cost per energy savings two possible renovation
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strengths are determined: a moderate renovation with lower costs and lower
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maximum possible space heat savings, and an ambitious renovation with associated
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higher costs and higher efficiency gains. They are added by step-wise
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linearisation in form of two additional generations in
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:mod:`prepare_sector_network.py`.
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Settings in the config.yaml concerning the endogenously optimisation of building
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renovation
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.. literalinclude:: ../config.default.yaml
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:language: yaml
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:lines: 136-140
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Further information are given in the publication
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`Mitigating heat demand peaks in buildings in a highly renewable European energy system, (2021) <https://arxiv.org/abs/2012.01831>`_.
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Hydrogen demand
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=============================
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Hydrogen is consumed in the industry sector (link to industry) to produce ammonia [link to ammonia industry section] and direct reduced iron (DRI) [link to DRI industry section]. Hydrogen is also consumed to produce synthetic methane [link to section “Methane supply”] and liquid hydrocarbons [link to fossil-oil based supply”] which have multiple uses in industry and other sectors.
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Hydrogen is also used for transport applications (link to transport), where it is exogenously fixed. It is used in `heavy-duty land transport <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L181>`_ and as liquified hydrogen in the shipping sector [add link to shipping sector]. Furthermore, stationary fuel cells may re-electrify hydrogen (with waste heat as a byproduct) to balance renewable fluctuations [Add a link to the section where we describe the Electricity sector and how storage is modelled there]. The waste heat from the stationary fuel cells can be used in `district-heating systems <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L256>`_.
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Hydrogen supply
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=============================
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Today, most of the H2 consumed globally is produced from natural gas by steam methane reforming (SMR)
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$$
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CH_4 + H_2O → CO + 3H_2
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$$
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combined with a water-gas shift reaction
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$$
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CO + H_2O → CO_2 + H_2
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$$
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SMR is included `here <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L245>`_.
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PyPSA-Eur-Sec allows this route of H2 production with and without [carbon capture (CC)] (Link to section on Carbon Capture Storage and Utilization). These routes are often referred to as blue and grey hydrogen. Here, methane input can be both of fossil or synthetic origin.
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Green hydrogen can be produced by electrolysis to split water into hydrogen and oxygen
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$$
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2H_2O → 2H_2 + O_2
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$$
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For the electrolysis, alkaline electrolysers are chosen since they have lower cost and higher cumulative installed capacity than polymer electrolyte membrane (PEM) electrolysers. The techno-economic assumptions are taken from the technology-data repository. Waste heat from electrolysis is not leveraged in the model.
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*Transport*
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Hydrogen is transported by pipelines. H2 pipelines are endogenously generated, either via a greenfield H2 network, or by `retrofitting natural gas pipelines <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L262>`_). Retrofitting is implemented in such a way that for every unit of decommissioned gas pipeline, a share (60% is used in [link to H2 backbone study]) of its nominal capacity (exogenously determined in the `config file <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L266>`_.) is available for hydrogen transport. When the gas network is not resolved, this input denotes the potential for gas pipelines repurposed into hydrogen pipelines.
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New pipelines can be built additionally on all routes where there currently is a gas or electricity network connection. These new pipelines will be built where no sufficient retrofitting options are available. The capacities of new and repurposed pipelines are a result of the optimisation.
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*Storage*
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Hydrogen can be stored in overground steel tanks or `underground salt caverns <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L250>`_. For the latter, energy storage capacities in every country are limited to the potential estimation for onshore salt caverns within `50 km <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L251>`_ of shore to avoid environmental issues associated with brine solution disposal. Underground storage potentials for hydrogen in European salt caverns is acquired from `Caglayan et al. <https://doi.org/10.1016/j.ijhydene.2019.12.161>`_
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Methane demand
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==================
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Can be used in boilers, in CHPs, in industry for high temperature heat, in OCGT.
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Not used in transport because of engine slippage.
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Methane supply
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=================
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Fossil, biogas, Sabatier (hydrogen to methane), HELMETH (directly power to methane with efficient heat integration).
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Solid biomass demand
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=====================
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Solid biomass provides process heat up to 500 Celsius in industry, as well as feeding CHP plants in district heating networks.
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Solid biomass supply
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=====================
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Only wastes and residues from the JRC ENSPRESO biomass dataset.
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Oil-based products demand
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========================
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Naphtha is used as a feedstock in the chemicals industry[LINK TO CHEMICAL INDUSTRY]. Furthermore, kerosene is used as transport fuel in the aviation sector[LINK TO AVIATION SECTOR]. Non-electrified agriculture machinery also consumes gasoline.
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Land transport [LINK TO LAND TRANSPORT] that is not electrified or converted into using H2-fuel cells also consumes oil-based products. While there is regional distribution of demand, the carrier is copperplated in the model, which means that transport costs and constraints are neglected.
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Oil-based products supply
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========================
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Oil-based products can be either of fossil origin or synthetically produced by combining H2 [link to hydrogen] and captured CO2 [link to carbon capture] in Fischer-Tropsch plants
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$$
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𝑛CO+(2𝑛+1)H_2 → C_{n}H_{2n + 2} +𝑛H_2O
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$$
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with costs as included from the `technology-data repository <https://github.com/PyPSA/technology-data/blob/master/latex_tables/tables_in_latex.pdf>`_. The waste heat from the Fischer-Tropsch process is supplied to `district heating networks <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L255>`_. The share of fossil and synthetic oil is an optimisation result depending on the techno-economic assumptions.
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Oil-based transport
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========================
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Liquid hydrocarbons are assumed to be transported freely among the model region since future demand is predicted to be low, transport costs for liquids are low and no bottlenecks are expected.
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Industry demand
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================
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Based on materials demand from JRC-IDEES and other sources such as the USGS for ammonia.
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Industry is split into many sectors, including iron and steel, ammonia, other basic chemicals, cement, non-metalic minerals, alumuninium, other non-ferrous metals, pulp, paper and printing, food, beverages and tobacco, and other more minor sectors.
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Inside each country the industrial demand is distributed using the `Hotmaps Industrial Database <https://gitlab.com/hotmaps/industrial_sites/industrial_sites_Industrial_Database>`_.
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Industry supply
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================
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Process switching (e.g. from blast furnaces to direct reduction and electric arc furnaces for steel) is defined exogenously.
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Fuel switching for process heat is mostly also done exogenously.
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Solid biomass is used for up to 500 Celsius, mostly in paper and pulp and food and beverages.
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Higher temperatures are met with methane.
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Carbon dioxide capture, usage and sequestration (CCU/S)
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=========================================================
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Carbon dioxide can be captured from industry process emissions,
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emissions related to industry process heat, combined heat and power
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plants, and directly from the air (DAC).
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Carbon dioxide can be used as an input for methanation and
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Fischer-Tropsch fuels, or it can be sequestered underground.
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