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Enhancing the Resilience of Operational Microgrids Through a Two-Stage Scheduling Strategy Considering the Impact of Uncertainties
handle: 11386/4774650
This article deals with the stochastic scheduling of a microgrid (MG) to balance the economical and resilience metrics. In the proposed model, the MG resilience indices are integrated into the economic criteria to ensure the resilience of MG operation alongside the main MG actors' profit/loss. The MG fragility index, recovery efficiency index, MG voltage index, and lost load index are considered in the proposed planning model. Further, to make the results more realistic, the uncertainties associated with energy price and wind production, alongside with planning of energy storage systems and electric vehicles parking lots are considered. To achieve a better solution for the security-constraint operation of MG, AC network equations are included in the system modeling. Finally, a large-scale MG based on the IEEE-33 bus testbed is utilized to evaluate the effectiveness of the proposed stochastic scheduling program.
- National Institute for Nuclear Physics Italy
- Azarbaijan Shahid Madani University Iran (Islamic Republic of)
- Tishreen University Syrian Arab Republic
- Università degli studi di Salerno Italy
- University of Mohaghegh Ardabili Iran (Islamic Republic of)
HIR natural event, General Computer Science, General Engineering, Energy Research, TK1-9971, stochastic programming, microgrid resilience, HIR Natural event; Indexes; Mathematical model; Microgrid resilience; Microgrids; Real-time systems; Resilience; Smart grid; Stochastic processes; Stochastic programming; Uncertainty, General Materials Science, Electrical engineering. Electronics. Nuclear engineering, smart grid
HIR natural event, General Computer Science, General Engineering, Energy Research, TK1-9971, stochastic programming, microgrid resilience, HIR Natural event; Indexes; Mathematical model; Microgrid resilience; Microgrids; Real-time systems; Resilience; Smart grid; Stochastic processes; Stochastic programming; Uncertainty, General Materials Science, Electrical engineering. Electronics. Nuclear engineering, smart grid
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