Flow direction algorithm-based optimal power flow analysis in the presence of stochastic renewable energy sources

Abstract

In recent years, power systems have expanded significantly, especially with the incorporation of various renewable energy sources (RESs). The optimal operation of the existing modern power system is an opportunity to maximize energy efficiency by increasing stochastic RESs participation in the power grid. Generally, optimal power flow (OPF) is a complex, non-linear optimization problem, the complexity of which increases when stochastic RESs are integrated into the network. Therefore, this research article presents a new physics-based optimization method, namely, the Flow Direction Algorithm (FDA), inspired by the movement of the Flow directed toward the drainage basin outlet to solve OPF problems. The FDA algorithm find optimal solutions with more precision by strategically allocating a portion of the search process to global search and the remainder to local search. Three distinct RESs are considered in the proposed OPF model, solar photovoltaic, wind, and small hydropower generators. Uncertainties in wind speed and solar irradiation are addressed using Monte Carlo simulation, whereas small hydro unit is treated as a fixed power generating source. The FDA algorithm is validated on IEEE 30, 57, and 118-bus systems, and the results have been compared with the state-of-the-art algorithms. It is found that FDA provides better OPF solutions when compared to other recent existing methods.