Optimization of reactive power pricing by using ant colony algorithm / Nur Azzammudin Rahmat
Reactive power involves optimal placement and sizing of capacitors in a network such that operating and investment costs are reasonable. The amount of reactive power necessary to be supplied must follow system reliability in a way to guarantee that the transmission voltage is at the required level....
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2011
|
| Online Access: | https://ir.uitm.edu.my/id/eprint/84781/1/84781.pdf https://ir.uitm.edu.my/id/eprint/84781/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Reactive power involves optimal placement and sizing of capacitors in a network such that operating and investment costs are reasonable. The amount of reactive power necessary to be supplied must follow system reliability in a way to guarantee that the transmission voltage is at the required level. In this research, reactive power dispatch is planned by using Newton-Raphson Load Flow equation and Economic Dispatch problems. Then, by using Ant Colony Optimization technique, the optimal problem is expected to be solved. The algorithm is based on ant's behaviour. Ant tends to use the shortest routes between their nest and food source. During exploration, the left behind chemical trail namely as "pheromone" trail. The trail guides other ants along the routes. Unpopular routes will have the pheromone trail evaporated. The algorithm has enhanced the power flow and the fees were comprehensively decreased. The analysis was performed on two types of bus system; IEEE 9-Bus system and IEEE 30-Bus system. The calculation was simulated by using MATLAB software. The obtained results display the reduced cost of reactive power. The results should helps to determine the best price that energy provider can use to represent the cost of reactive power dispatch. In the future, the reactive power planning can be enhanced further by running several optimization techniques. The results should be compared to indicate the most optimum reactive power pricing. |
|---|