A solution to multi Objective Stochastic Optimal Power Flow problem using mutualism and elite strategy based Pelican Optimization Algorithm

Wind Energy is rapidly growing into one of the most popular energy options for power generation. However, the unpredictability of wind necessitates the employment of a distribution function when describing the wind environment. In the depiction of wind speeds, the two significant parameters of the W...

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Veröffentlicht in:Applied soft computing 2024-06, Vol.158, p.111548, Article 111548
Hauptverfasser: Dora, Bimal Kumar, Bhat, Sunil, Halder, Sudip, Srivastava, Ishan
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Sprache:eng
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Zusammenfassung:Wind Energy is rapidly growing into one of the most popular energy options for power generation. However, the unpredictability of wind necessitates the employment of a distribution function when describing the wind environment. In the depiction of wind speeds, the two significant parameters of the Weibull distribution, such as the scale parameter and the shape parameter are often utilized. Therefore, it is essential to choose the most appropriate approach for estimating these parameters. Furthermore, the uncertainty in delegated power from variable wind speeds makes system management challenging. In this paper, the Weibull distribution parameters were determined using the Pelican Optimization Algorithm (POA). POA has gained extensive popularity among the research community and is currently used to address a wide range of optimization problems. However, the exploration and exploitation are not properly balanced in this algorithm. To overcome this problem a novel hybrid algorithm namely Mutualism phase based POA (MPOA) is proposed with the help of mutualism phase of Symbiotic Organisms Search (SOS) algorithm. To demonstrate the efficacy and robustness MPOA is applied on multi-objective Optimal Power Flow (MO-OPF) problems. For this study IEEE 30 bus standard system and modified IEEE 30 bus system consisting of two wind farms are taken. The purpose of this work is to examine the impact of changing the Weibull parameters, reverse and penalty cost coefficients on the overall generation cost while considering all the security aspects. ●The efficiency and robustness of Pelican Optimization Algorithm (POA) is investigated for single objective and multi-objective Optimal Power Flow (OPF) as well as Stochastic Optimal Power Flow (SOPF) problems.●A novel hybrid Algorithm namely Mutualism phase based Pelican Optimization Algorithm (MPOA) is developed.●Results shows the superiority of MPOA over POA.●MPOA and POA are implemented in IEEE 30 bus test system and modified IEEE 30 bus system contains two wind generator having capacity of 80 MW and 50 MW respectively.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2024.111548