Implementation Method of Distributed Partial Discharge Sensing Technology for Power Distribution Equipment
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Implementation Method of Distributed Partial Discharge Sensing Technology for Power Distribution Equipment
Vol. 46, Issue 6, Pages: 1929-1938(2020)
作者机构:
西安交通大学电力设备电气绝缘国家重点实验室
作者简介:
基金信息:
DOI:
CLC:
Published Online:30 June 2020,
Published:2020
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YU Boning, REN Ming, ZHANG Zhibin, et al. Implementation Method of Distributed Partial Discharge Sensing Technology for Power Distribution Equipment[J]. 2020, 46(6): 1929-1938.
DOI:
YU Boning, REN Ming, ZHANG Zhibin, et al. Implementation Method of Distributed Partial Discharge Sensing Technology for Power Distribution Equipment[J]. 2020, 46(6): 1929-1938.DOI:
Implementation Method of Distributed Partial Discharge Sensing Technology for Power Distribution Equipment
Insulation state detection is an important method to discover potential failures of power equipment and maintain the safe operation of the power grid. However
due to the complexity and the large scale of the distribution network
traditional online monitoring schemes are difficult to implement. In order to sense the insulation status of power distribution equipment and pre-warn the faults
this paper proposes a distributed wireless sensor network(WSN) based on the Internet of Things(IoT) technology and demonstrates its feasibility. In this paper
the top-level design of the architecture of the wireless sensor network is firstly researched
then the design of data communication and sensor nodes are studied according to the requirements of economics
low power consumption
and security. Next
wireless sensor networks are adopted to conduct the partial discharge monitoring on high/compact distribution switchgeasr and low density/loose distribution cables(accessories) so as to realize the design of transient earth voltage(TEV) and high-frequency current(HFCT) sensor nodes based on LPWAN-based data transmission and management
measurement and evaluation of node energy consumption and battery life. Finally
the evaluation of equipment insulation status and pre-warning strategies which are applicable to wireless sensor networks are discussed. The research and exploration of this method are expected to provide references for more distribution network condition monitoring applications based on IoT.