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Demand response algorithm design for flight simulator energy management system

By: Wongpanyo, Watchara.
Contributor(s): Sukdee, Kritsana.
Publisher: USA Springer 2023Edition: Vol.104(4), Aug.Description: 921-934p.Subject(s): Humanities and Applied SciencesOnline resources: Click here In: Journal of the institution of engineers (India): Series BSummary: The purpose of this research was to study the demand side management (DSM) application and gain the smart grid technological benefits to design the optimized algorithm. The algorithm’s responsibility was specific management during outage crisis phases for assuring the energy supplies and protecting the flight simulator unit and data servers which were the high-value assets and first prioritized Demand Response (DR) in terms of aviation risk management. The experimental methodology verified the considerate risk management matrix by following the RRSSQ Checklist, and the algorithm was simulated by the Homer@microgrid Software. The results evaluated the algorithm was able to heal the blackout and the fluctuated distributed energy resources (DERs) by utilizing the distributed energy resources automatically from the isolated 40 kW photovoltaics rooftop microgrid and the standby 800 kW diesel generator to back up and supply the DRs priority in time. The results reported the efficiency was 99.725% which was n 99.5% of the efficient demand value which the local regulator standard requirement, which required the efficient demand of at least 99.5%. The optimization model reported the 1,452 resolved solutions from the 8,712 significant grid unstable events. The ratio of system unstable probability was 1:726 or 0.275%. The conclusion is, to sustain the reliability, this algorithm has required the operation of an 800 kW diesel generator as the DSM is redundant. Moreover, the technical challenge of grid integration is the limitation of the local Grid Code regulator which is not ready to comply with the smart grid standard. Therefore, to avoid the Grid Code violation, the islanded mode (behind the meter) concept and an energy storage system installation are recommended during off-grid.
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The purpose of this research was to study the demand side management (DSM) application and gain the smart grid technological benefits to design the optimized algorithm. The algorithm’s responsibility was specific management during outage crisis phases for assuring the energy supplies and protecting the flight simulator unit and data servers which were the high-value assets and first prioritized Demand Response (DR) in terms of aviation risk management. The experimental methodology verified the considerate risk management matrix by following the RRSSQ Checklist, and the algorithm was simulated by the Homer@microgrid Software. The results evaluated the algorithm was able to heal the blackout and the fluctuated distributed energy resources (DERs) by utilizing the distributed energy resources automatically from the isolated 40 kW photovoltaics rooftop microgrid and the standby 800 kW diesel generator to back up and supply the DRs priority in time. The results reported the efficiency was 99.725% which was n 99.5% of the efficient demand value which the local regulator standard requirement, which required the efficient demand of at least 99.5%. The optimization model reported the 1,452 resolved solutions from the 8,712 significant grid unstable events. The ratio of system unstable probability was 1:726 or 0.275%. The conclusion is, to sustain the reliability, this algorithm has required the operation of an 800 kW diesel generator as the DSM is redundant. Moreover, the technical challenge of grid integration is the limitation of the local Grid Code regulator which is not ready to comply with the smart grid standard. Therefore, to avoid the Grid Code violation, the islanded mode (behind the meter) concept and an energy storage system installation are recommended during off-grid.

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