TITLE:
Risk Identification based on Hidden Semi-Markov Model in Smart Distribution Network
AUTHORS:
Fangyuan Chang, Wanxing Sheng, Tianshu Zhang, Yu Zhang, Xiaohui Song
KEYWORDS:
Risk Identification; Hidden Semi-Markov Models; Smart Distribution Network
JOURNAL NAME:
Energy and Power Engineering,
Vol.5 No.4B,
November
12,
2013
ABSTRACT: The smart distribution system is the critical part of
the smart grid, which also plays an important role in the safe and reliable
operation of the power grid. The self-healing function of smart distribution
network will effectively improve the security, reliability and efficiency,
reduce the system losses, and promote the development of sustainable energy of
the power grid. The risk identification process is the most fundamental and
crucial part of risk analysis in the smart distribution network. The risk
control strategies will carry out on fully recognizing and understanding of the
risk events and the causes. On condition that the risk incidents and their
reason are identified, the corresponding qualitative / quantitative risk
assessment will be performed based on the influences and ultimately to develop
effective control measures. This paper presents the concept and methodology on
the risk identification by means of Hidden Semi-Markov Model (HSMM) based on
the research of the relationship between the operating characteristics/indexes
and the risk state, which provides the theoretical and practical support for
the risk assessment and risk control technology.