Location

Hilton Waikoloa Village, Hawaii

Event Website

http://hicss.hawaii.edu/

Start Date

1-3-2018

End Date

1-6-2018

Description

This paper proposes an adaptive optimization-based approach for under frequency load shedding (UFLS) in microgrids following an unintentional islanding. In the first step, the total amount of load curtailments is determined based on the system frequency response (SFR) model. Then, the proposed mixed-integer linear programming (MILP) model is executed to find the best location of load drops. The novel approach specifies the least cost load shedding scenario while satisfying network operational limitations. A look-up table is arranged according to the specified load shedding scenario to be implemented in the network if the islanding event occurs in the microgrid. To be adapted with system real-time conditions, the look-up table is updated periodically. The efficiency of the proposed framework is thoroughly evaluated in a test microgrid with a set of illustrative case studies.

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Jan 3rd, 12:00 AM Jan 6th, 12:00 AM

An Adaptive Optimization-Based Load Shedding Scheme in Microgrids

Hilton Waikoloa Village, Hawaii

This paper proposes an adaptive optimization-based approach for under frequency load shedding (UFLS) in microgrids following an unintentional islanding. In the first step, the total amount of load curtailments is determined based on the system frequency response (SFR) model. Then, the proposed mixed-integer linear programming (MILP) model is executed to find the best location of load drops. The novel approach specifies the least cost load shedding scenario while satisfying network operational limitations. A look-up table is arranged according to the specified load shedding scenario to be implemented in the network if the islanding event occurs in the microgrid. To be adapted with system real-time conditions, the look-up table is updated periodically. The efficiency of the proposed framework is thoroughly evaluated in a test microgrid with a set of illustrative case studies.

http://aisel.aisnet.org/hicss-51/es/renewable_resources/7