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Overview

Organization: Joint Research Centre, European Commission
Version: |version|
Git Revision:|release|
Date: |today|

The Dispa-SET model is mainly developed within the “Joint Research Centre” of the European Commission and focuses on the balancing and flexibility problems in European grids [1].

It is written in GAMS an Python (Pyomo) and uses csv files for input data handling. The optimisation is defined as a Linear Programming (LP) or Mixed-Integer Linear Programming (MILP) problem, depending on the desired level of accuracy and complexity. Continuous variables include the individual unit dispatched power, the shedded load and the curtailed power generation. The binary variables are the commitment status of each unit. The main model features can be summarized as follows:

Features

  • Minimum and maximum power for each unit
  • Power plant ramping limits
  • Reserves up and down
  • Minimum up/down times
  • Load Shedding
  • Curtailment
  • Pumped-hydro storage
  • Non-dispatchable units (e.g. wind turbines, run-of-river, etc.)
  • Start-up, ramping and no-load costs
  • Multi-nodes with capacity constraints on the lines (congestion)
  • Constraints on the targets for renewables and/or CO2 emissions
  • Yearly schedules for the outages (forced and planned) of each units
  • CHP power plants and thermal storage
  • Different clustering methods

The demand is assumed to be inelastic to the price signal. The MILP objective function is therefore the total generation cost over the optimization period.

Libraries used

  • pyomo Optimization object library, interface to LP solver (e.g. CPLEX)
  • pandas for input and result data handling
  • matplotlib for plotting
  • GAMS_api for the communication with GAMS

Dispa-SET in the scientific literature

In the past years, Dispa-SET has been used in various scientific works covering different geographical areas and with different focus points. The works for which scientific articles have been published are summarized hereunder:

  • Contribution of hydropower for flexibility services in the European power system [2].
  • Ongoing work aiming at coupling the JRC-EU-TIMES model with Dispa-SET by generating simplified variable RES flexibility constraints [3] [4].
  • Impact of Electric Vehicle deployment in The Netherlands [5].
  • Open-source model of the Balkans area, with some simulations involving high shares of renewables [6] [7].
  • Available technical flexibility to balance variable RES generation in Belgium [8]
  • Comparison of clustering formulations [9] [10]

Ongoing developments

The Dispa-SET project is relatively recent, and a number of improvements will be brought to the project in a close future:

  • Grid constraints (DC power-flow)
  • Stochastic scenarios
  • Extension of the modeled areas
  • Modeling of the ancillary markets
  • User interface

Public administration reference

This software is primarily developed and used within the Institute for Energy and Transport, which is one of the 7 scientific institutes of the Joint Research Centre (JRC) of the European Commission. The IET is based both in Petten, the Netherlands, and Ispra, Italy. The Dispa-SET model is developed in the framework of the "Energy Systems Modelling" (ESM) project.

Licence

Dispa-SET is a free software licensed under the “European Union Public Licence" EUPL v1.2. It can be redistributed and/or modified under the terms of this license.

Main Developers

  • Sylvain Quoilin (University of Liège, KU Leuven)
  • Andreas Zucker (European Commission, Institute for Energy and Transport)
  • Konstantinos Kavvadias (European Commission, Institute for Energy and Transport)

References

[1]Quoilin, S., Hidalgo Gonzalez, I., & Zucker, A. (2017). Modelling Future EU Power Systems Under High Shares of Renewables: The Dispa-SET 2.1 open-source models. Publications Office of the European Union.
[2]Sánchez Pérez, A. (2017), Modelling Hydropower in detail to assess its contribution to flexibility services in the European power system. Master Thesis, University of Utrecht, Netherlands.
[3]Quoilin, S., Nijs, W., Gonzalez, I. H., Zucker, A. and Thiel, C. (2015), Evaluation of simplified flexibility evaluation tools using a unit commitment model, In 12th International Conference on the European Energy Market (EEM), pp. 1 5.
[4]Quoilin, S., Nijs, W. and Zucker, A. (2017), Evaluating flexibility and adequacy in future EU power systems: model coupling and long-term forecasting, In Proceedings of the 2017 ECOS Conference, San Diego.
[5]Beltramo, A., Julea, A., Refa, N., Drossinos, Y., Thiel, C. and Quoilin, S. (2017),`Using electric vehicles as flexible resource in power systems: A case study in the Netherlands, In 14th International Conference on the European Energy Market (EEM).
[6]Pavičević, M., Tomić, I., Quoilin, S., Zucker, A. and Pukšec, T. and Krajačić, G. (2017), Applying the Dispa-SET model on the Western Balkans power systems, In Proceedings of the 2017 SDEWES Conference
[7]Tomić, I., Pavičević, M., Quoilin, S., Zucker, A., Krajačić, G., Pukšec, T. and Duić, N. (2017), Applying the Dispa-SET model on the seven countries from the South East Europe, In 8th Energy Planning and Modeling of Energy Systems-Meeting, Belgrade
[8]Quoilin, S., Gonzalez Vazquez, I., Zucker, A., and Thiel, C. (2014). Available technical flexibility for balancing variable renewable energy sources: case study in Belgium. Proceedings of the 9th Conference on Sustainable Development of Energy, Water and Environment Systems.
[9]Pavičević, M., Quoilin, S. and Pukšec, T., (2018). Comparison of Different Power Plant Clustering Approaches for Modeling Future Power Systems, Proceedings of the 3rd SEE SDEWES Conference, Novi Sad.
[10]Pavičević, M., Kavvadias, K. and Quoilin, S. (2018). Impact of model formulation on power system simulations - Example with the Dispa-SET Balkans model, EMP-E conference 2018: Modelling Clean Energy Pathways, Brussels.