Optimal Power Flow Solution of Wind-Integrated Power System Using Novel Metaheuristic Method

Amr Khaled Khamees, Almoataz Y. Abdelaziz, Makram R. Eskaros, Adel El-Shahat and Mahmoud A. Attia
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Amr Khaled Khamees: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Almoataz Y. Abdelaziz: Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt
Makram R. Eskaros: Engineering Physics and Mathematics Department, Ain Shams University, Cairo 11517, Egypt
Adel El-Shahat: Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 46202, USA
Mahmoud A. Attia: Electrical Power & Machines Department, Ain Shams University, Cairo 11517, Egypt

Energies, 2021, vol. 14, issue 19, 1-19

Abstract: Wind energy is particularly significant in the power system today since it is a cheap and clean power source. The unpredictability of wind speed leads to uncertainty in devolved power which increases the difficulty in wind energy system operation. This paper presents a stochastic optimal power flow (SCOPF) for obtaining the best scheduled power from wind farms while lowering total operational costs. A novel metaheuristics method called Aquila Optimizer (AO) is used to address the SCOPF problem due to its highly nonconvex and nonlinear nature. Wind speed is represented by the Weibull probability distribution function (PDF), which is used to anticipate the cost of wind-generated power from a wind farm based on scheduled power. Weibull parameters that provide the best match to wind data are estimated using the AO approach. The suggested wind generation cost model includes the opportunity costs of wind power underestimation and overestimation. Three IEEE systems (30, 57, and 118) are utilized to solve optimal power flow (OPF) using the AO method to prove the accuracy of this method, and results are compared with other metaheuristic methods. With six scenarios for the penalty and reverse cost coefficients, SCOPF is applied to a modified IEEE-30 bus system with two wind farms to obtain the optimal scheduled power from the two wind farms which reduces total operation cost.

Keywords: wind energy; stochastic optimal power flow; Weibull probability distribution; Aquila Optimizer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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