Problem
Regional-specific linetypes are essential to ensure accurate representation of the line parameters. In particular, it has been demonstrated previously that default PyPSA linetypes lead to significant errors for the transmission capacity.
Solution
The approach has been elaborated basing of experience of regional case studies for Bolivia, Colombia, USA, Zambia and Japan. A solution has been implemented into PyPSA-Earth in pypsa-meets-earth/pypsa-earth#1933 and includes the following steps.
Search for reference data
Physical parameters of conductors are normally defined by the national standards and parameters of the transmission development project and can be restored by using published data. That implies answering to the following questions.
- Which line types and line parameters present in the power system? That includes both physical parameters of conductors, as well as major operational parameters. The latter include voltages, polarity and frequency.
- What is the correspondence between the voltage levels and line types used? Ideally, voltage must be mapped into line types in an unambiguous way, while there may be also the need to accommodate some diversity across the line types
- What are physical parameters of each line type?
Generation of standardised reference dataset
The outputs of the analytical steps are translated into the following artifacts:
- parameters of the line types
- a regional-specific set of configuration features
For the now, we are using PyPSA conventions which are shared with pandapower (see custom_line_types.csv for an example).
The configuration features are region-specific, and include currently the voltage and line type id (a USA example)
Proof-of-concept
Zambia
An example of such a restoration procedure is given in this issue open-energy-transition/pypsa-zambia#400, including dealing with data gaps and unambiguities.
The main challenges in this case are:
- the need to collate and analyse multiple reference sources
- rapid changes which are to be expected in the national power system during the next years
USA
A concept of automated procedure on the linetype extraction is available in build_us_line_types script of PyPSA-Earth. The script is parsing a synthetic network into the standardised inputs. The major challenge has been to manage richness of the reference data. That has implied format transformation, clean-up and verification. The line types in this case have been restored from physical parameters of the conductors.
Problem
Regional-specific linetypes are essential to ensure accurate representation of the line parameters. In particular, it has been demonstrated previously that default PyPSA linetypes lead to significant errors for the transmission capacity.
Solution
The approach has been elaborated basing of experience of regional case studies for Bolivia, Colombia, USA, Zambia and Japan. A solution has been implemented into PyPSA-Earth in pypsa-meets-earth/pypsa-earth#1933 and includes the following steps.
Search for reference data
Physical parameters of conductors are normally defined by the national standards and parameters of the transmission development project and can be restored by using published data. That implies answering to the following questions.
Generation of standardised reference dataset
The outputs of the analytical steps are translated into the following artifacts:
For the now, we are using PyPSA conventions which are shared with pandapower (see custom_line_types.csv for an example).
The configuration features are region-specific, and include currently the voltage and line type id (a USA example)
Proof-of-concept
Zambia
An example of such a restoration procedure is given in this issue open-energy-transition/pypsa-zambia#400, including dealing with data gaps and unambiguities.
The main challenges in this case are:
USA
A concept of automated procedure on the linetype extraction is available in build_us_line_types script of PyPSA-Earth. The script is parsing a synthetic network into the standardised inputs. The major challenge has been to manage richness of the reference data. That has implied format transformation, clean-up and verification. The line types in this case have been restored from physical parameters of the conductors.