This is the repository for the Nordic44, that is a synthetic power system model of the Nordic high voltage transmission system, described in IEC Common Information Model (CIM) .
The main objective of Nordic44 is to provide the necessary CIM model information to simulation business and application processes and information exchanges relevant for the Nordic electrical power grid.
Relevant business function that the model aim to support are:
- Network Operation (NO)
- Emergency Simulation (ES)
- Engineering Design Management (EDM)
- Fault Management (FM)
- Network Model Management (NMM)
- Predictive Operation Planning (POP)
- System Development Planning (SDP)
Relevant application function that the model aim to support are:
- Static Power Flow (SPF)
- Remedial Action and Contingency Analysis (RACA)
- Short-Circuit Analysis (SCA)
- Capacity Calculation Analysis (CCA)
- Transient Dynamic Stability Analysis (TDSA)
- Market information and transparency
The Nordic44 is intendent to be created so that it can be merged with the DIGN10 project so that is possible to do analysis accross High Voltage (HV), Medium Voltage (MV) and Low Voltage (LV).
A version of Nordic44 has been used in the NYPA Model Transformation. In the repository there are multiple version of Nordic44 and relevant PSSE.
The first released version of the Nordic44 model was published in the following paper, with the following authors: L. Vanfretti, S.H. Olsen, V.S. Narasimham Arava, G. Laera, A. Bidadfar, T. Rabuzin, S. H. Jakobsen, J. Lavenius, M. Baudette and F.J. Gómez-López, “An Open Data Repository and a Data Processing Software Toolset of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data,” Data in Brief (Elsevier), February 17th 2017. http://dx.doi.org/10.1016/j.dib.2017.02.021 The original PSSE based model was provided by Emil Hillberg at STRI (https://www.stri.se/).
The original Nordic44 model was created to support static power flow and dynamic stability analysis under relevant marked condition for the nordic power system based on the market data published by Nord Pool (https://www.nordpoolgroup.com/en/). It was trained and validated for all electricity market's operation hours during 2015 with power flow and dynamic response. The result was used to train and test Machine Learning techniques (e.g. Decision Trees) and other computational techniques that are essential in the work flows used for dynamic security assessment of electrical power systems.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
