Abstract
Employing online monitoring (OLM) of circuit breakers (CBs) is increasing continuously due to its compatibility with future smart grids. The proper and reliable operation of CBs directly affects the resiliency, reliability, and continuity of power systems. Since there is a large number of CBs in power systems, installation of OLM systems to all CBs is not economically justifiable. Consequently, an effective prioritization framework to find critical CBs to be monitored online is essential. This paper provides a sensible correlation between the failure rate and the deterioration process of the CBs through the combination of the discrete Markov model and signal processing of diagnostic features. The results have been employed to assess the condition of the CBs equipped with OLM, to set a proper maintenance activity, and to predict the subsequent condition. To prove its feasibility, the proposed approach is applied to a real utility substation using the Monte Carlo method based on real monitoring data. The CBs have been prioritized from both reliability and financial viewpoints. In addition, sensitivity analyses results interestingly indicate that the old CBs are not the optimistic choices all the time due to the dependency of the problem to the important parameters such as deterioration process, failure rates, operation frequency, and the location of the CBs in the power system. The proposed approach enables us to find the optimum choice in such a complex environment.
| Original language | English |
|---|---|
| Pages (from-to) | 1569-1577 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Power Delivery |
| Volume | 34 |
| Issue number | 4 |
| Early online date | 11 Apr 2019 |
| DOIs | |
| Publication status | Published - Aug 2019 |
Keywords
- Maintenance engineering
- Monitoring
- Circuit breakers
- Indexes
- Clustering
- Algorithms
- Aging
- Markov processes
- prioritization
- decision making
- online monitoring (OLM)
- Circuit breakers (CBs)
- maintenance
