Application of Whale Optimization Algorithm for Environmental Constrained Economic Dispatch of Fixed Head Hydro-Wind-Thermal Power System
Sangita Rani Kar1, Deba Prasad Dash2, S.K. Sanyal3
1Sangita Rani Kar*, B.E., UCE, M.Tech BPUT, Ph.D. SOA University Department of is Power System Engineering.
2Dr. Deba Prasad Dash, B.Tech, M.Tech Utkal University Associate Professor, Department of Electrical Engineering, Government College of Engineering, Kalahandi.
3Prof. S.K. Sanyal, Professor of Electrical Engineering Department UCE, Burla. SOA University, Bhubaneswar.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 5608-5616 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2261109119/2019©BEIESP | DOI: 10.35940/ijeat.A2261.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work applies whale optimization algorithm for emission constrained economic dispatch of hydrothermal units including wind power. As the wind power has a characteristic of cleanliness and is renewable, this is convincing to include this for better operation of electric power system keeping in view both economic and environmental aspects. Hydrothermal scheduling integrated with wind power establishes a multi-objective problem that becomes economic emission hydro-thermal-wind scheduling problem while taking into consideration the cost due to wind uncertainty. Whale optimization algorithm is proposed to solve this emission constrained economic dispatch problem with competing objectives. This algorithm is recently developed and gives the best solution among other nature inspired algorithms. The objectives minimum generations as well as emission cost, both are optimized together including different constraints. A daily scheduling of all the three types of systems – hydro, thermal and wind is considered to evaluate the competency of this optimization technique to get a solution for this multi-objective problem. The experiments are carried out on two systems for determining the effectiveness of the suggested method. Besides, results found using the whale optimization technique have been compared with the results obtained from other evolutionary methods. From the comparison, it is experimentally justified that the whale optimization works faster and the cost of generation as well as cost of emission are lower than the other approaches.
Keywords: Economic environmental dispatch , multi-objective optimization whale optimization algorithm, water discharge rate, wind energy.