AUTHOR=Ilyas Muhammad Arsalan , Alquthami Thamer , Awais Muhammad , Milyani Ahmad H. , Rasheed Muhammad Babar 

TITLE=(DA-DOPF): A Day-Ahead Dynamic Optimal Power Flow With Renewable Energy Integration in Smart Grids

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2021.696837

DOI=10.3389/fenrg.2021.696837

ISSN=2296-598X

ABSTRACT=The performance of a power system can be measured and evaluated by its power flow analysis. Along with the penetration of renewable energies such as wind and solar, the power flow problem has become a complex optimization problem. In addition to this, constraints handling is another challenging task of this problem. \textcolor{black}{The main critical problem of this dynamic power system having such Variable Energy Sources (VESs) is the intermittency of these VESs, and the complexity of constraints handling for a real-time optimal power flow (RT-OPF) problem. Therefore, optimal scheduling of generation sources with the constraints satisfaction is the main goal of this study. Hence, a renewable energy forecasting-based, Day Ahead Dynamic Optimal Power Flow (DA-DOPF) is presented in this paper} with the forecasting of solar and wind patterns by using Artificial Neural Networks (ANNs). Moreover, contribution factors are calculated using Triangular Fuzzy Membership Function (T-FMF) in the sub-interval time slots. Furthermore, the Superiority of Feasible (SF) solution constraint handling approach is used to avoid the constraint violation of inequality constraints of OPF. The IEEE 30-bus transmission network has been amended to integrate \textcolor{green}{solar photovoltaic (PV)} and wind farm at different buses. In this approach computing program is based on MATPOWER which is a tool of MATLAB for load flow analysis that uses \textcolor{black}{the} Newton-Raphson technique because of its rapid convergence. Meteorological information has been gathered during the time frame 1 January 2015 to 31 December 2017 from Danyore Weather Station (DWS) at Hunza, Pakistan. Levenberg-Marquardt (LM) calculation based ANN model is utilized to foresee the breeze speed and sunlight based irradiance in light of its versatile nature. Finally, results are discussed analytically to select the best generation schedule and control variables values.