A multi-objective optimisation algorithm with swarm intelligence for contingency surveillance

This paper proposes a new multi-objective optimization model to minimize congestion cost, load curtailment and generation cost simultaneously to restore the equilibrium of operating point of the system under contingency. The solution algorithms of the proposed method are based on the Particle Swarm...

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Vydáno v:Proceedings of the 2011 International Conference on Electrical Engineering and Informatics s. 1 - 6
Hlavní autoři: Sen, S., Chanda, S., Sengupta, S., Chakrabarti, A.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.07.2011
Témata:
congestion
Generators
load curtailment
Load flow
Load modeling
Optimization
particle swarm optimisation
Reliability
Security
value of congestion cost
value of excess loss
ISBN:1457707535, 9781457707537
ISSN:2155-6822
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Shrnutí:This paper proposes a new multi-objective optimization model to minimize congestion cost, load curtailment and generation cost simultaneously to restore the equilibrium of operating point of the system under contingency. The solution algorithms of the proposed method are based on the Particle Swarm Optimization (PSO) in which load curtailment and generation cost have been optimized without breaching line flow constraints for congestion management. The significance of the proposed method has been presented in this paper by a comparative study with the conventional cost optimization method in terms of operating cost considering VOLL (Value of lost load) and two more proposed analytical indices namely Value of Congestion Cost (VOCC) and Value of Excess Loss (VOEL) in contingent states of power system. It has been depicted that the proposed method effectively reduces the operating cost volatility in spot power market with respect to the conventional methods. The applicability of the developed method has been tested on the IEEE 30 bus system.
ISBN:1457707535
9781457707537
ISSN:2155-6822
DOI:10.1109/ICEEI.2011.6021632