Abstract
The practitioners and researchers have received considerable attention solving complex optimization problems with meta-heuristic algorithms during the past decade. Many of these algorithms are inspired by various phenomena of nature. One of the promising solutions for secure and continuous power flow in the transmission line is rescheduling-based congestion management approach, but the base problem is rescheduling cost. To solve the congestion with minimized rescheduling cost, a new population-based algorithm, the Lion Algorithm (LA), is introduced in this paper. The basic motivation for development of this optimization algorithm is based on special lifestyle of lions and their cooperation characteristics. Based on some benchmark, Lion Algorithm (LA) is compared with the existing conventional algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), artificial bee colony (ABC) and firefly (FF) by analysing the convergence, cost and congestion. In IEEE 30 bus system, experimental investigation is carried out and the obtained results by the proposed algorithm Lion Algorithm (LA) in comparison with the other algorithms used in this paper.
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Tapre, P.C., Singh, D.K., Paraskar, S. (2018). Lion Algorithm: A Nature-Inspired Algorithm for Generation Rescheduling-Based Congestion Management. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_1
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DOI: https://doi.org/10.1007/978-981-10-7386-1_1
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