Work place: Department of Electrical Engineering, Madhav Institute of Technology & Science, Gwalior-474005, INDIA
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Research Interests: Computational Science and Engineering, Artificial Intelligence, Data Structures and Algorithms
Biography
Deepak Kumar Sharma obtained his B.E degree in Electrical Engineering from Rewa Engineering College, Rewa, (India) in 2015. He is currently pursuing his M.E degree in Electrical Engineering (Industrial Systems and Drives), from M.I.T.S, Gwalior, (India). His areas of interest includes application of evolutionary computing and artificial intelligence applications to Power System.
By Deepak Kumar Sharma Hari Mohan Dubey Manjaree Pandit
DOI: https://doi.org/10.5815/ijisa.2020.03.03, Pub. Date: 8 Jun. 2020
This paper presents modified salp swarm algorithm (MSSA) for solution of power system scheduling problems with diverse complexity level. Salp swarm algorithm (SSA) is a recently proposed efficient nature inspired (NI) optimization method inspired by foraging behaviour of salps found in deep ocean. SSA sometimes suffers to stagnation at local minima, to overcome this problem and enhancing searching capability by both exploration and exploitation MSSA is proposed in this paper. MSSA applied and tested on two types of problems. Type one is having five benchmark functions of diverse nature, whereas type two is related with real world problem of power system scheduling of a standard IEEE 114 bus system with 54 thermal units for (i) single area system, (ii) two area system and (iii) three area system. Finally Outcome of simulation results are validated with reported results by other method available in literature.
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