DOI: 10.5281/zenodo.17570105
title: FRAM demo dataset

description: This is an open dataset for power market modelling. It's purpose is to demonstrate the functionality of FRAM modeling framework and the JulES power market model. The dataset is focused on Northern Europe. 

A demo of FRAM and JulES using this dataset can be found here. 

Only open sources has been used to create the dataset, mainly ENTSO-E, the Norwegian Water Resources and Energy Directorate (NVE) and PyPSA. 

The dataset is a work in progress. We welcome your feedback, suggested improvements, alternative data sources or any other contributions to help us improve it.

Contact information: fram@nve.no
description: Important information!

This dataset is simplified and has not undergone sufficient validation for operational use. NVE has only tested that the dataset is sufficiently consistent to run our models and FRAM demo. It may contain errors that significantly distort model outputs and analyses. Model results produced using the dataset should not be used as a base for decision or investment making. The dataset does not reflect NVEs expected development for the European power system. NVE is not liable for any direct or indirect losses as a result of the use of the demo dataset or in connection with copying or further distribution of the information from the modelling using this demo dataset. 
description: File structure and formats 



Data is divided into three types which are structured differently and stored in different file formats: 
















Table Type 









Format 









Description 









Example











Attribute tables 









excel 









IDs and parameters, may include references to other tables 









Hydropower.generators.xlsx











Time series tables 









excel, yaml, h5









Timestamped values (e.g. generation, profiles). Time resolution varies. Timestamps follow ISO 8601 format (e.g. 2025-09-04 15:30:00). Isocalendar years are used for profiles. 









Wind.Generators.profiles.h5











Curve tables 









yaml 









Two-dimensional data that shows dependency of one parameter on another. For example, reservoir curve, technology adoption curve etc.  









Hydropower.pqcurves.yaml











 

Metadata 



Each table is accompanied by metadata. Metadata describes each column and defines what type of data it holds. In the first version of the database, metadata is stored together with the data in a separate sheet within the same Excel file or as a separate schema associated with the table in parquet-files. Units are defined in metadata, not in column names. ID fields use lowercase Latin characters, no spaces.


File Naming

Filenames consist of two parts: 





A reference to a thematic category (e.g. thermal, hydropower) 

A reference to a high-level group (e.g. generators, energy_carriers, pumps, load)





Examples: Hydropower.generators.xlsx, Wind.Generators.capacity.xlsx 




 

Scope and limitations

The dataset contains data to represent the Northern European power system, including thermal power plants, solar and wind generation, hydropower production, transmission grid, and consumption. 


 






The dataset models the following areas endogenously:



Denmark (DK1, DK2)

Estonia (EST)

Finland (FIN)

Germany (DEU)

United Kingdom (GBR)

Lithuania (LTU)

Netherlands (NLD)

Norway (NO1, NO2, NO3, NO4, NO5)

Poland (POL)

Sweden (SE1, SE2, SE3, SE4)


These are defined as exogenous zones:



Austria (AUT)

Belgium (BEL)

Switzerland (CHE)

Czech Republic (CZE)

France (FRA)

Latvia (LVA)

Slovakia (SVK)


The exogenous zones represent boundaries to the endogenously modelled area through fuel price (masking the power price in the zone), dummy power generation and dummy consumption. Dummy power consumption is oversized relative to production in the zone, so that the power price in the zones is set from a pre-defined level through the fuel price. 

Country and bidding zone abbreviations

We follow NVE’s naming convention and use three-character abbreviations to represent each country or bidding zone, e.g. DEU and SVK. Where one country has multiple bidding zones, the bidding zones are two-letter followed by the associated number, e.g. NO1, DK2. 




 

Data sources

Nodes

Nodes represent specific geographical or logical areas within the modeled power system. Each node is linked to one or more bidding zones and serves as the connection point for generation, consumption, and transmission data. In the dataset files, each node includes information such as: Node identifier, Type, Mapping to bidding zone.







In this demo dataset there are nodes for the following commodities: power, fuel and emissions. Nodes can have price and profile. 

Fuel costs are based on PyPSA-Eur's implementation.  




Sources: 



Brown, T., Victoria, M., Zeyen, E., Hofmann, F., Neumann, F., Frysztacki, M., Hampp, J., Schlachtberger, D., Hörsch, J., Schledorn, A., Schauß, C., van Greevenbroek, K., Millinger, M., Glaum, P., Xiong, B., & Seibold, T. PyPSA-Eur: An open sector-coupled optimisation model of the European energy system (Version v2025.04.0) [Computer software]





Wind and solar generators

Installed capacities for recent years are sourced from ENTSO-E. Profiles for 1951–2020 are developed by NVE. See source below for more information.

Note on Swedish capacity: Swedish installed capacity is only available aggregated on the whole country. Capacity has been distributed between bidding zones by share of total installed capacity.

Note on Lithuania: NVE has not succeeded in getting in contact with the TSO of Lithuania. Production profiles for Estonia have been used for Lithuania. 

Sources: 






ENTSO-E Installed Generation Capacity Aggregated, [14.1.A]. Installed Capacity per Production Type [14.1.A] – Transparency Platform. Included in data set with permission from respective data owners. 

Data providers to ENTSO-E: 



Norway: Statnett/ statnett.no.

Estonia: Elering/ elering.ee. 

Sweden: Svenska kraftnät / svk.se. 

Denmark: Energinet / energinet.dk. 

The Netherlands: TenneT Netherlands / tennet.eu/nl-en. 

Poland: PSE / pse.pl. PSE is committed to ensuring the accuracy of the data it provides. However, PSE does not accept responsibility for business decisions made by market participants based on the published data. 

Finland: Fingrid / data.fingrid.fi, license CC 4.0 BY.

Germany: Bundesnetzagentur / SMARD.de, license CC 4.0 BY.

Great Britain: Contains BMRS data © Elexon Limited copyright and database right [2025] https://www.elexon.co.uk/bsc/data/balancing-mechanism-reporting-agent/copyright-licence-bmrs-data/.



Generation capacity in Lithuania: Litgrid. Generation Capacity. https://www.litgrid.eu/index.php/power-system/power-system-information/generation-capacity/546 [14.08.25]

Swedish capacity distribution: From Elhandelsavtal.se. Elproduktion i Sverige. https://www.elhandelsavtal.se/elproduktion [12.06.2025]

NVE. Værdatasett for kraftsystemmodellene. https://www.nve.no/energi/analyser-og-statistikk/vaerdatasett-for-kraftsystemmodellene/ [10.6.25] 






Hydropower data

Derived from NVE's description of the hydropower system for Norway, Sweden and Finland for 2024 (with plants operational as of 31.12.2024). The dataset aims at modelling all major hydropower plants (≥ 10 MW) and hydropower plants with regulated inflow. 

The dataset has been tuned to provide a representative average annual production through weekly-resolution modeling. It is primarily used for long-term analysis, medium-term prognosis and regulatory licensing processes.

Smaller plants have been aggregated to a residual module per area. The residual module can also be used to adjust the total production from the dataset.

Description of the datastructure

The file Hydropower.Modules.xlsx describes the main components in the river system. Each module has a unique ID and has the main attributes such as a release, a generator, pump, reservoir, inflow, or a bypass depending on its function. Each of these attributes (except release) is defined in a separate file that contains the relevant technical and operational parameters. 

The inflow is described in Hydropower.Inflow.xlsx, which includes both a yearly volume (referenced to 1991–2020) and a time series profile (1981–2020). 

The generator is described in Hydropower.Generators.xlsx, which includes tailwater elevation, nominal head, energy equivalent, and a PQ curve. 

The reservoir is described in Hydropower.Reservoirs.xlsx, which contains reservoir capacity, reservoir curves, operational filling limits, and penalty costs for violating these bounds. 

The pump is described in Hydropower.Pumps.xlsx, which includes pump capacity, mean energy equivalent, and head–flow characteristics.

The bypass, together with the ReleaseTo and SpillTo fields in Hydropower.Modules.xlsx, defines the topology of the system by determining the downstream connections for controlled and uncontrolled flow. 

Both the bypass, the release, and the reservoirs can have operational bounds that are enforced through minimum and maximum flow or volume constraints. Violations of these bounds can be penalized using soft constraints, defined through penalty costs in the respective files. These constraints are used in the optimization model to ensure realistic operation of the hydropower system under physical and regulatory limitations.

 

Note

This is an early version of this dataset and it is therefore subject to change. Especially the operational bounds (in db21_hydropower_profiles) and the curves (in db22_hydropower_curves) which have not been fully tested yet.

Most of this data has previously been published by NVE. It can be downloaded here, in both excel and detd format. The original dataset has a slightly different structure, as the hydropower modules can have both regulated and unregulated inflows. In the open Fram demo dataset, these modules have been split into two. The regulated inflow, reservoir and bypass are assigned to the first module, while the unregulated inflow and production unit are assigned to a second module downstream of the first. 

Sources: 








The Norwegian dataset is compiled from several sources maintained by NVE.



Topology: NVE Atlas and hydropower concession applications.

Reservoir volumes and min/max regulated water levels are primarily sourced from NVE’s internal database which is not publicly available. However, the relevant data used in the hydropower model is accessible through NVE Atlas. In some cases, operational reservoir limits from HYDRA II are applied.  

Parameters such as energy equivalent, maximum turbine capacity, and mean gross head are retrieved from NVE’s hydropower database, typically based on commissioning forms and concession documentation. The mapping between the modules and the hydropower database can be found in the original dataset download.

Mean annual inflow is based on NVE’s runoff maps for the period 1991–2020. Available for download.

Inflow profiles are based on catchment area assessments from NVE’s Hydrology Department. Available for download.

Reservoir restrictions and minimum flow requirements are taken from NVE’s concession database, where only legally binding conditions are included—self-imposed or court-mandated requirements are not part of the model. Many restrictions are available here. 



The Finnish dataset was recently provided by Fingrid. We use inflow profiles from the Finnish Environment Institute (SYKE), produced with their Watershed Simulation and Forecasting System. 

The Swedish dataset is an old dataset, which we only adjust the residual modules of. The Swedish inflow profiles are downloaded from the Swedish Meteorological and Hydrological Institute (SMHI, with license CC0), se example query used by NVE here. Some profiles have been extended to cover all of 1981-2020. 





Thermal generators

Based on thermal generators compiled by PyPSA-powerplantmatching.

Additional assumptions: 



Plants with missing efficiency data (part load and full load) have been given the mean efficiency (). Mean efficiency is calculated from all plants. Variations in efficiency due to technology/fuel are not accounted for.

Ringhals nuclear powerplant: Capacity reduced to current operational capacity. From Vattenfall. Ringhals. Source:  https://powerplants.vattenfall.com/ringhals/ [09.10.25]

Oil-fueled thermal generation in Estonia: Most thermal capacity missing from PyPSA-Eur dataset. Implemented as an oil shale plant with capacity from ENTSO-E for 2023. From ENTSO-E Installed Capacity per Production Type. Transparency Platform [14.10.2025] 


Sources: 









F. Gotzens, H. Heinrichs, J. Hörsch, and F. Hofmann, Performing energy modelling exercises in a transparent way - The issue of data quality in power plant databases, Energy Strategy Reviews, vol. 23, pp. 1–12, Jan. 2019. https://doi.org/10.5281/zenodo.14785651





Demand data

Actual electricity demand per year and consumption profiles for 2023 for each bidding zone in the endogen zones are based on day-ahead total loads from ENTSO-E. The ReservePrice is set to the "harmonised maximum clearing price for SDAC" from ENTSO-E. 

For the Norwegian bidding zones NO1-NO5, consumption for residential commercial buildings and industry has been separated based on output data for 2023 from NVE’s 2025 long-term power market analysis. Buildings are coupled with profiles based on ENTSO-E data, corrected for industry and other consumption profiles. Industry is implemented with a flat profile. The remaining demand has been categorized as “other consumption”, with a flat profile. 

The dataset also contains consumption profiles for selected countries from NVE for 1951–2020, not applied in the current model scenarios. 

Sources: 






ENTSO-E Total Load - Day Ahead, [6.1.B]. Total Load - Day Ahead / Actual [6.1.A] & [6.1.B] – Transparency Platform. Available for free re-use under CC-BY 4.0.

ENTSO-E. SDAC COMMUNICATION NOTE. “13 September 2022: No changes in harmonised maximum clearing price for SDAC from 20 September: it remains at 4,000 EUR/MWh”. SDAC_Coms_note_suspension_of_HMMCP_final.pdf [Online]

NVE. Værdatasett for kraftsystemmodellene. https://www.nve.no/energi/analyser-og-statistikk/vaerdatasett-for-kraftsystemmodellene/ [10.6.25]

NVE. Langsiktig kraftmarkedsanalyse 2025. Langsiktig kraftmarkedsanalyse 2025 - NVE [02.09.2025]. 








Transmission data

The Transmission grid is represented by transfer data from ENTSO-E. Transmission loss is assumed at 1% for both AC and DC grid lines.

Sources: 






ENTSO-E Forecast Transfer Capacities Day-ahead and Week-ahead, [11.1]. Forecasted Day-ahead Transfer Capacities [11.1] – Transparency Platform. Available for free re-use under CC-BY 4.0. 
description: Changelog

****************************************v0.2 - 17th December 2025****************************************



Folder structure.

Country abbreviations: changed from two-character to three-character. 

Renamed columns from ExogenPrice to ExogenousPrice.

Wind and solar: generation capacities for DK1 and DK2 for 2023 applied to 2025 where missing.

Demand:



profiles for industry and other consumption deducted from Norwegian buildings profiles.

Profiles: Based on 3 years of data (previously 1). Now the average value of each datapoint is 1. Previously, the profile summed to 1.

Capacity (hourly consumption) changed to yearly average value. Previously: yearly maximum. 

Removed unused demand normal prices file.



Transmission: line capacity adjustments, e.g. for NO4-FIN.

Thermal:



Oil-fueled generators added for Estonia.

Capacity of Ringhals nuclear plant in Sweden corrected.

Adjusted plant efficiencies, for more correct CO2 price.

Added data for start hours.



Adjusted CO2 prices.

Hydorpower: added watershed.


****************************************v0.1 - 6th October 2025****************************************

First published dataset version. Must be considered as work in progress.