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Method of Collaborative Scheduling of Acquisition Tasks Based on Artificial Intelligence

Published: 17 May 2021 Publication History

Abstract

The development of the Energy Internet puts forward higher requirements for new-type information acquisition systems of power consumption. A collaborative scheduling method for information acquisition tasks based on artificial intelligence is proposed in this paper, relying on artificial intelligence algorithms for the coordinated scheduling of concentrator tasks. The core task scheduling of acquisition system does not require the management of complete terminal tasks, and dramatically reduces the pressure of core task scheduling and efficiently completes the task of data acquisition. This paper gives specific implementation steps and detailed flowcharts, and through the analysis of examples, the effectiveness of the method is verified. The proposed method further expands the effective way for the intelligent acquisition of the system.

References

[1]
Xiangyu Kong, Chuang Li, Chengshan Wang, et al. Short-term electrical load forecasting based on error correction using dynamic mode decomposition [J]. Applied Energy 261 (2020):114368.
[2]
ZHU Li-peng1, RAO Wei1, QIU Hong-bin1, WU Shun2, JIN Dan3.Research on Task Flow Planning and Scheduling in Wide Area Computing for Power Big Data [J]. Electric Power ICT, 2017, 15(3): 62--66.
[3]
Liu Y, Lu X, Wang X, et al, TaskScheduling scheme in heterogeneous Hadoop cloud platform based on Task progress aware [J]. Application Research of Computers, 2017, 34(10): 3139--3143.
[4]
Ning Wenyu, Wu Qingbo, Tan Yusong. MapReduce oriented self-adaptive delay scheduling algorithm[J]. Computer Engineering & Science, 2013, 35(3): 52--57.
[5]
KONG Xiangyu, MA Yuying, LI Ye, et al. Remote Estimation Method for Measurement Error of Smart Meter Based on Limited Memory Recursive Least Squares Algorithm [J]. Proceedings of the CSEE, 2020, 40 (7): 2142--2151.
[6]
WU Yang, WANG Heng, MEI Zheng, et al. Application of Erupt Data Processing Model to Electric Power Dispatching System [J]. Proceedings of the CSU-EPSA, 2020, 32(1): 86--92, 115.
[7]
WANG De-wen, LIU Yang. A task scheduling strategy of cloud data center in electric power corporation[J]. Automation of Electric Power Systems, 2014, 38(8): 61--66, 97.
[8]
Xiangyu Kong, Feng Zheng, Zhijun E, et al. Short-term Load Forecasting Based on Deep Belief Network [J], Automation of Electric power system, 2018, 42(5): 133--139.
[9]
SONG Junhui, FENG Yan, ZHOU Guoqing. A divisible load scheduling model of maximizing service quality[J]. Journal of Xinyang Normal University (Natural Science Edition), 2017, 30(1): 1--5.
[10]
Fan Chaoqun. Research and Implementation of Multi-task Cooperative Scheduling Bottleneck Analysis System Based on Application Behavior Characteristics [D]. Beijing: Institute of Network Technology, Beijing University of Posts and Telecommunications, 2019.

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ICITEE '20: Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering
December 2020
687 pages
ISBN:9781450388665
DOI:10.1145/3452940
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 May 2021

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Author Tags

  1. Artificial intelligence
  2. Completeness
  3. Coordinated scheduling
  4. Data acquisition
  5. Power system

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • the Science and Technology Project of State Grid Corporation of China (Research on Key Technologies of Electricity Information Collection for Energy Internet)

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ICITEE2020

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