Abstract
This paper describes how to obtain optimal power flow (OPF) in power systems that integrate wind turbine (WT) and solar photovoltaic (PV) producers. A modified technique called modified turbulent water flow-based optimization (MTFWO) is presented to solve the nonconvex and nonlinear OPF problem effectively. In the OPF model, power output from renewable sources is regarded as a dependent variable. At the same time, the voltage at the bus terminals of WT/PV is used as a controller (decision variable). The amount of power generated by WT and PV generators is modeled using data collected in real time on the wind speed and the amount of irradiation from the sun. Although the TFWO algorithm has its benefits, it also has certain shortcomings in solving challenging problems. By more effectively searching the feasible space using different interaction mechanisms and improving exploitation capabilities, this paper improves the TFWO algorithm’s performance. We compare the performance and effectiveness of the suggested MTFWO method with cutting-edge optimization algorithms for solving the OPF problems, using the same system-specific data, limitations, and control variables in the comparisons.
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