Title: Improved real coded genetic algorithm-based short-term hydrothermal generation planning

Authors: Dipanwita Ganguly; Saborni Das; Abhik Hazra; Ashish Laddha; Mousumi Basu

Addresses: Department of Electrical Engineering, Techno India College of Technology, New Town, Mega City, DG Block, Kolkata – 700156, India ' Power Engineering Department, Jadavpur University, LB-8, Sector-III, Salt Lake, Kolkata – 700098, India ' Power Engineering Department, Jadavpur University, LB-8, Sector-III, Salt Lake, Kolkata – 700098, India ' Department of Electrical Engineering, Malaviya National Institute of Technology, JLN Marg, Jaipur-302017, India ' Power Engineering Department, Jadavpur University, LB-8, Sector-III, Salt Lake, Kolkata – 700098, India

Abstract: Real coded genetic algorithm (RCGA) and improved real coded genetic algorithm (IRCGA) have been applied for the solution of short-term hydrothermal scheduling problem. The improved technique has been developed and tested on a multi reservoir cascaded hydroelectric system having generation-load power balance, upper and lower limits on reservoir capacity, water discharge rate, water spillage rate, hydraulic continuity restriction and operating capacity limits of different hydro and thermal units. The water transport delay between connected reservoirs has also been taken into consideration. The performance of the proposed approach is validated with four test systems. The results of the proposed algorithm are compared with those of modified differential evolution (MDE), teaching learning-based optimisation (TLBO), clonal selection algorithm (CSA), improved fast evolutionary programming (IFEP), improved particle swarm optimisation (IPSO), and genetic algorithm (GA). From numerical results, it has been found that the IRCGA-based approach is able to provide better solutions in lesser computational time.

Keywords: hydrothermal operation planning; improved real coded genetic algorithm; IRCGA; limiting values of ramping rate; loading effect of valve point; restricted operating sections.

DOI: 10.1504/IJHI.2019.103574

International Journal of Hybrid Intelligence, 2019 Vol.1 No.2/3, pp.118 - 146

Received: 05 Mar 2018
Accepted: 21 Mar 2018

Published online: 05 Nov 2019 *

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