Abstract
This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.
| Original language | English |
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| Title of host publication | 2013 IEEE Computational Intelligence Applications in Smart Grid |
| Publisher | IEEE |
| Publication date | 2013 |
| Pages | 146-153 |
| ISBN (Print) | 9781467360029 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
| Event | 2013 IEEE Symposium on Computational Intelligence Applications in Smart Grid - Grand Copthorne Waterfront Hotel, Singapore, Singapore Duration: 16 Apr 2013 → 19 Apr 2013 |
Conference
| Conference | 2013 IEEE Symposium on Computational Intelligence Applications in Smart Grid |
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| Location | Grand Copthorne Waterfront Hotel |
| Country/Territory | Singapore |
| City | Singapore |
| Period | 16/04/2013 → 19/04/2013 |
Keywords
- fuzzy systems
- investment
- particle swarm optimisation
- power distribution economics
- Bioengineering
- Power, Energy and Industry Applications