Energy system models for Finland, 2023 and 2030, incl. power and district heating sectors
Description
This dataset is used for modeling of Finnish energy system for reference years 2023 and 2030. The system model includes power and district heating sectors. Two different modeling frameworks were used: EnergyPLAN version 16.3 and Calliope version 0.6. The dataset contains the model files for both frameworks, distribution files used in the simulation, results files for Calliope and scripts used for post-processing the Calliope results. The approach is focused on optimisation of the district heat generation with expanding variable renewable electricity generation in the power side through the increase of wind power capacity. Various heat generation technologies are used; main focus is in the role of heat pumps and electric boilers. CHP, boilers, heat recovery and waste CHP are also included in the district heating system. The dataset contains the reference system model for both Calliope and EnergyPLAN. This is named Reference 2023. The 2030 scenarios are ran several times with varied wind generation capacity: SC0 has the original heat generation capacities. SC1.1 is a scenario where 1800MWth of boilers are replaced from both groups 2 and 3 with heat pumps (HPs). SC1.2 has 1800MWth and 3600MWth of HPs in G2 and G3. SC2.1 and SC2.2 utilise eletric boilers (EBs) instead of HP's, capacities are the same as in SC1.1 and SC1.2. SC3 is a Calliope optimization model, where the heat generation capacities are optimized. Furthermore the dataset contains a sensitivity analysis with varied heat pump COP and investment cost. The .ipynb-files are used for post processing of the Calliope results data with Python (Jupyterlab). In the selected approach the wind power capacity was varied - hence the optimization was run 10 times with Calliope, and the serial calculations tool was used in EnergyPLAN.
Files
Steps to reproduce
The timeseries for VRE production are based on PVGIS-database (Huld, T., Müller, R. and Gambardella, A., 2012. "A new solar radiation database for estimating PV performance in Europe and Africa". Solar Energy, 86, 1803-1815) and ERA5 database (Copernicus Climate Change Service, Climate Data Store, (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.adbb2d47) The electricity demand timeseries is extracted from Fingrid (Source Fingrid / data.fingrid.fi, license CC 4.0 BY). The district heat demand timeseries is generated based on ERA5 outdoor temperature data and DH statistics, for explanation of the methodology, refer to http://dx.doi.org/10.1016/j.ijggc.2026.104586 The current power and district heat generation capacities are extracted from Finnish Power Plant Registry as well as from the annual reports from Energy Authority, ENTSO-E and TSO Fingrid. Simulation is 1 node, although "virtual" nodes are used to separate the district heating into two groups - one without CHP and one with CHP capacity. EnergyPLAN uses the district heating Groups 2 and 3 for this division of heat demand.
Institutions
- Lappeenranta-Lahti University of TechnologySouth Karelia, Lappeenranta