An MPC-based energy management system for multiple residential microgrids

Alessandra Parisio, Christian Wiezorek, Timo Kyntäjä, Joonas Elo, Karl H. Johansson

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

19 Citations (Scopus)

Abstract

In this study we present a Model Predictive Control (MPC) approach to Energy Management Systems (EMSs) for multiple residential microgrids. The EMS is responsible for optimally scheduling end-user smart appliances, heating systems and local generation devices at the residential level, based on end-user preferences, weather-dependent generation and demand forecasts, electric pricing, technical and operative constraints. The core of the proposed framework is a mixed integer linear programming (MILP) model aiming at minimizing the overall costs of each residential microgrid. At each time step, the computed optimal decision is adjusted according to the actual values of weather-dependent local generation and heating requirements; then, corrective actions and their corresponding costs are accounted for in order to cope with imbalances. At the next time step, the optimization problem is re-computed based on updated forecasts and initial conditions. The proposed method is evaluated in a virtual testing environment that integrates accurate simulators of the energy systems forming the residential microgrids, including electric and thermal generation units, energy storage devices and flexible loads. The testing environment also emulates real-word network medium conditions on standard network interfaces. Numerical results show the feasibility and the effectiveness of the proposed approach.
Original languageEnglish
Title of host publicationAutomation Science and Engineering (CASE), 2015 IEEE International Conference on
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages7-14
ISBN (Electronic)978-1-4673-8183-3, 978-1-4673-8182-6
DOIs
Publication statusPublished - 8 Oct 2015
MoE publication typeA4 Article in a conference publication
Event11th Annual IEEE International Conference on Automation Science and Engineering - Gothenburg, Sweden
Duration: 24 Aug 201528 Aug 2015
Conference number: 11

Publication series

Name
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference11th Annual IEEE International Conference on Automation Science and Engineering
Abbreviated titleIEEE CASE
CountrySweden
CityGothenburg
Period24/08/1528/08/15

Fingerprint

Energy management systems
Model predictive control
Heating
Costs
Testing
Linear programming
Energy storage
Interfaces (computer)
Simulators
Scheduling

Keywords

  • Smart Grids
  • Micro Grids
  • simulations
  • distributed communication system

Cite this

Parisio, A., Wiezorek, C., Kyntäjä, T., Elo, J., & Johansson, K. H. (2015). An MPC-based energy management system for multiple residential microgrids. In Automation Science and Engineering (CASE), 2015 IEEE International Conference on (pp. 7-14). Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/CoASE.2015.7294033
Parisio, Alessandra ; Wiezorek, Christian ; Kyntäjä, Timo ; Elo, Joonas ; Johansson, Karl H. / An MPC-based energy management system for multiple residential microgrids. Automation Science and Engineering (CASE), 2015 IEEE International Conference on. Institute of Electrical and Electronic Engineers IEEE, 2015. pp. 7-14
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title = "An MPC-based energy management system for multiple residential microgrids",
abstract = "In this study we present a Model Predictive Control (MPC) approach to Energy Management Systems (EMSs) for multiple residential microgrids. The EMS is responsible for optimally scheduling end-user smart appliances, heating systems and local generation devices at the residential level, based on end-user preferences, weather-dependent generation and demand forecasts, electric pricing, technical and operative constraints. The core of the proposed framework is a mixed integer linear programming (MILP) model aiming at minimizing the overall costs of each residential microgrid. At each time step, the computed optimal decision is adjusted according to the actual values of weather-dependent local generation and heating requirements; then, corrective actions and their corresponding costs are accounted for in order to cope with imbalances. At the next time step, the optimization problem is re-computed based on updated forecasts and initial conditions. The proposed method is evaluated in a virtual testing environment that integrates accurate simulators of the energy systems forming the residential microgrids, including electric and thermal generation units, energy storage devices and flexible loads. The testing environment also emulates real-word network medium conditions on standard network interfaces. Numerical results show the feasibility and the effectiveness of the proposed approach.",
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Parisio, A, Wiezorek, C, Kyntäjä, T, Elo, J & Johansson, KH 2015, An MPC-based energy management system for multiple residential microgrids. in Automation Science and Engineering (CASE), 2015 IEEE International Conference on. Institute of Electrical and Electronic Engineers IEEE, pp. 7-14, 11th Annual IEEE International Conference on Automation Science and Engineering, Gothenburg, Sweden, 24/08/15. https://doi.org/10.1109/CoASE.2015.7294033

An MPC-based energy management system for multiple residential microgrids. / Parisio, Alessandra; Wiezorek, Christian; Kyntäjä, Timo; Elo, Joonas; Johansson, Karl H.

Automation Science and Engineering (CASE), 2015 IEEE International Conference on. Institute of Electrical and Electronic Engineers IEEE, 2015. p. 7-14.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AB - In this study we present a Model Predictive Control (MPC) approach to Energy Management Systems (EMSs) for multiple residential microgrids. The EMS is responsible for optimally scheduling end-user smart appliances, heating systems and local generation devices at the residential level, based on end-user preferences, weather-dependent generation and demand forecasts, electric pricing, technical and operative constraints. The core of the proposed framework is a mixed integer linear programming (MILP) model aiming at minimizing the overall costs of each residential microgrid. At each time step, the computed optimal decision is adjusted according to the actual values of weather-dependent local generation and heating requirements; then, corrective actions and their corresponding costs are accounted for in order to cope with imbalances. At the next time step, the optimization problem is re-computed based on updated forecasts and initial conditions. The proposed method is evaluated in a virtual testing environment that integrates accurate simulators of the energy systems forming the residential microgrids, including electric and thermal generation units, energy storage devices and flexible loads. The testing environment also emulates real-word network medium conditions on standard network interfaces. Numerical results show the feasibility and the effectiveness of the proposed approach.

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Parisio A, Wiezorek C, Kyntäjä T, Elo J, Johansson KH. An MPC-based energy management system for multiple residential microgrids. In Automation Science and Engineering (CASE), 2015 IEEE International Conference on. Institute of Electrical and Electronic Engineers IEEE. 2015. p. 7-14 https://doi.org/10.1109/CoASE.2015.7294033