Distributed MPC-based energy scheduling for islanded multi-microgrid considering battery degradation and cyclic life deterioration
In this paper, distributed model predictive control (MPC) based energy scheduling problem is presented for islanded multi-microgrids. The objective is to achieve supply–demand balance in an individual microgrid through energy coordination and reduce the battery degradation for its extended cycle lif...
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Veröffentlicht in: | Applied energy 2023-01, Vol.329, p.120168, Article 120168 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this paper, distributed model predictive control (MPC) based energy scheduling problem is presented for islanded multi-microgrids. The objective is to achieve supply–demand balance in an individual microgrid through energy coordination and reduce the battery degradation for its extended cycle life. In order to achieve desired objective, the battery state of charge is taken as zone control optimization problem and new slack variable is introduced as optimized variable to restrict the battery state of charge in optimal range with considering battery degradation. Furthermore, accelerated distributed augmented Lagrangian (ADAL) based distributed coordination strategy is presented, which can improve power supply reliability through coordinated cooperation among MGs for energy exchanges. The system framework is modeled as mixed-integer dynamic model which switches between different operating conditions. A mixed-integer quadratic programming approach is addressed to solve the MPC optimization problem. The effectiveness of the proposed scheme is validated through comparative performance with existing model. Finally, convergence analysis and comparative fast convergence performance of the proposed scheme is provided.
•This paper proposed energy scheduling for isolated multi-microgrids (MMGs).•Distributed Zone-MPC based EMS strategy is proposed for individual MG.•Battery life is improved through Zone constraint MPC.•ADAL method is utilized for distributing the interconnected optimization problem. |
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ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2022.120168 |