Ontology and Multi-Agent Based Intelligent Retrieval Model for Power Quality Monitoring Information

Abstract:

A power quality monitoring information intelligent retrieval model based on ontology and multi-Agent is proposed. Combining ontology technology with multi-Agent technology, establish a four layer alliance structure of the intelligent retrieval model. At first, the function of the model for each layer has been described in detail. Then, the concrete building method of the power quality ontology knowledge base which is the core part of the model has been explained. Finally, example analysis shows the whole intelligent retrieval process. Each layer of the model uses agent alliance mode, according with the demand of intelligent retrieval; realizing the user's retrieval request with the aid of ontology knowledge base can not only improve retrieval efficiency, but also realize deep mining of the basic retrieval information. Example analysis shows that the model can realize intelligent retrieval quickly and efficiently and have certain practical value.

• Periodical: Applied Mechanics and Materials (Volume 574)
• Pages: 436-444
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.574.436
• Online since: July 2014
• Authors: Jia Fu Yin*, Juan Suo, Dan Tan
• Keywords: Intelligent Retrieval, Model, Multi-Agent, Ontology, Power Quality Monitoring

References

[1] DUAN Cheng-gang, OUYANG Sen, SONG Zheng-xiang, et al(2004). Design of a new online and real-time power quality monitor. Power System Technology 28(2): 60-63.

[2] JIAO Dongsheng, LU Dongliang, YING Junhao, et al(2011). Design and Implementation of Dynamic Power Quality Real-Time Monitoring System. Power System Technology 35(5): 110-114.

[3] Dilek Kucuk, Tolga Inan, Ozgul Salor, et al(2010). An extensible database architecture for nationwide power quality monitoring [J]. Electrical Power and Energy Systems 32 (6): 559-570.

DOI: 10.1016/j.ijepes.2009.11.012

[4] Dilek Kucuk, Ozgul Salor, Tolga Inan, et al(2010). PQONT: A domain ontology for electrical power quality. Advanced Engineering Informatics 24 (1): 84-95.

DOI: 10.1016/j.aei.2009.06.009

[5] WANG Ling, KANG Jian, Zou Hongliang, et al(2011). Construction and application of real-time power quality monitoring system. Power System Protection and Control 39 (2): 108-111.

[6] HE Wei-guo, XIE Wei, ZHANG Jian(2010). Power quality monitoring system of Shanghai Grid. East China Electric Power 38 (4): 497-499.

[7] LU Jian-jiang, ZHANG Ya-fei, XU Wei-guang, ea al(2009). Intelligent retrieval technology. Beijing: Science Press. 250.

[8] CHEN Bing-yan, WU Jun-hua(2009). The Research on the Ontology based Intelligent Information Retrieval System. Microprocessor 3(5): 89-91.

[9] YIN Huan-liang, SUN Si-ming, ZHANG Feng(2009). Research of web intelligent retrieval based on ontology. Computer Engineering 35 (23): 44-49.

[10] ZHANG Yi, YANG Hong-geng, YE Mao-qing, et al(2012). A Power Quality Ancillary Service Platform Based on Multi-Agent. Electric Power Automation Equipment 32(12): 92-96.

[11] LI Bin, XU Jian-yuan, LIN ZI, et al(2010). Application of Multi-Agent System in Control of Inter-Area Oscillation. Power System Technology 34(5): 109-115.

[12] SHENG Wan-xing, YANG Xu-sheng(2007). Muti-agent system with the application in electric power system. Beijing: China electric power press. 220.

[13] CHEN Zhenbao, ZHANG Jing, LI Junhuai(2007). Implementation of Agent-oriented programming platform based on O-O. Computer Applications 27(1): 35-37.

[14] Dilek Kücük, Ozgül Salor, Tolga Inan, et al(2008). Building an Ontology for Flexible Power Quality Querying. Computer and Information Science 33(8): 1-6.

DOI: 10.1109/iscis.2008.4717903

[15] ZHOU Hui, YANG Hong-geng, WU Chuan-lai(2012). A power quality comprehensive evaluation method based on grey clustering. Power System Protection and Control 40(15): 70-75.

[16] XU Yong-hai, JIN Yan, YAO Bao-qi, LIN Feng(2006). Simulation software of harmonic filter and reactive power compensation for distribution system. Electric Power Automation Equipment 26(12): 93-95.