Scenario-based model predictive operation control of islanded microgrids

Christian Andreas Hans, Pantelis Sopasakis, Alberto Bemporad, Jörg Raisch, Carsten Reincke-Collon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)

Abstract

We propose a model predictive control (MPC) approach for the operation of islanded microgrids that takes into account the stochasticity of wind and load forecasts. In comparison to worst case approaches, the probability distribution of the prediction is used to optimize the operation of the microgrid, leading to less conservative solutions. Suitable models for time series forecast are derived and employed to create scenarios. These scenarios and the system measurements are used as inputs for a stochastic MPC, wherein a mixed-integer problem is solved to derive the optimal controls. In the provided case study, the stochastic MPC yields an increase of wind power generation and decrease of conventional generation.
Original languageEnglish
Title of host publication54th IEEE Conference on Decision and Control (CDC)
Place of PublicationOsaka, Japan
Publisher IEEE
Pages3272-3277
Number of pages6
ISBN (Electronic)978-1-4799-7886-1
DOIs
Publication statusPublished - 11 Feb 2016

Keywords

  • Scenario-based MPC
  • Stochastic model predictive control
  • Stochastic control
  • Microgrids
  • Islanded microgrids
  • Operation control
  • Energy management

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  • Cite this

    Hans, C. A., Sopasakis, P., Bemporad, A., Raisch, J., & Reincke-Collon, C. (2016). Scenario-based model predictive operation control of islanded microgrids. In 54th IEEE Conference on Decision and Control (CDC) (pp. 3272-3277). IEEE . https://doi.org/10.1109/CDC.2015.7402711