Developing a strategy based on weighted mean of vectors (INFO) optimizer for optimal power flow considering uncertainty of renewable energy generation

Mohamed Farhat; Salah Kamel; Ahmed M Atallah; Almoataz Y Abdelaziz; Marcos Tostado-Véliz

doi:10.1007/s00521-023-08427-x

Developing a strategy based on weighted mean of vectors (INFO) optimizer for optimal power flow considering uncertainty of renewable energy generation

Neural Comput Appl. 2023;35(19):13955-13981. doi: 10.1007/s00521-023-08427-x. Epub 2023 Mar 18.

Authors

Mohamed Farhat¹, Salah Kamel², Ahmed M Atallah¹, Almoataz Y Abdelaziz³, Marcos Tostado-Véliz⁴

Affiliations

¹ Electrical Power and Machines Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, 11517 Egypt.
² Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, 81542 Egypt.
³ Faculty of Engineering and Technology, Future University in Egypt, Cairo, 11835 Egypt.
⁴ Electrical Engineering Department, EPS, University of Jaen, 23700 Linares, Spain.

Abstract

In recent years, more efforts have been exerted to increase the level of renewable energy sources (RESs) in the energy mix in many countries to mitigate the dangerous effects of greenhouse gases emissions. However, because of their stochastic nature, most RESs pose some operational and planning challenges to power systems. One of these challenges is the complexity of solving the optimal power flow (OPF) problem in existing RESs. This study proposes an OPF model that has three different sources of renewable energy: wind, solar, and combined solar and small-hydro sources in addition to the conventional thermal power. Three probability density functions (PDF), namely lognormal, Weibull, and Gumbel, are employed to determine available solar, wind, and small-hydro output powers, respectively. Many meta-heuristic optimization algorithms have been applied for solving OPF problem in the presence of RESs. In this work, a new meta-heuristic algorithm, weighted mean of vectors (INFO), is employed for solving the OPF problem in two adjusted standard IEEE power systems (30 and 57 buses). It is simulated by MATLAB software in different theoretical and practical cases to test its validity in solving the OPF problem of the adjusted power systems. The results of the applied simulation cases in this work show that INFO has better performance results in minimizing total generation cost and reducing convergence time among other algorithms.

Keywords: INFO algorithm; Optimal power flow; Renewable energy sources; Uncertainty modeling.

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