Inter-Organizational Cloud Computing and Robust Scalability in Current Scenario and Beyond

Khan, Adil; Junejo, A. R.; Naeem, M.; Sattar, Mariyam; Malik, Abdul Haseeb

doi:10.3103/s0146411622010060

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…If the power supply of a node fails or fails to work normally in case of other emergencies, it is necessary to detect whether all access points in the network are idle and whether the number of adjacent clusters exceeds the limit indicates that the network service range is higher. If there are multiple branch circuits on a line and there is no load, it is necessary to operate them in sections, Otherwise, divide this branch into two sections for inspection to obtain the monitored area [11][12]. In the distributed energy system, the number of nodes is obtained by comprehensive calculation of the environment, service capacity and other factors.…”

Section: Distributed Energy Detectionmentioning

confidence: 99%

Optimization of Distributed System Energy Detection Method Considering Cloud Computing

2022

DPS

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Distributed power generation is a new type of renewable energy that can improve energy utilization efficiency and reduce environmental pollution. Its power generation mode is wind power, photovoltaic and cogeneration. This paper introduces the problems faced by the application of cloud computing system in power network and studies its solutions. Aiming at the shortcomings of the traditional uncertainty analysis method based on the node voltage, such as low accuracy and easy loss of data, an improved algorithm is proposed to improve the power quality of the node and improve the global resource utilization ratio, combining with the characteristics of distributed power generation. After that, the energy detection method of the system is tested. The test results show that the distributed energy system has short detection time and low average detection time, which indicates that the distributed energy system has fast energy detection time, good performance, high detection power and low error rate.

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Section: Distributed Energy Detectionmentioning

confidence: 99%