LAUSR

Abstract Optimal power flow is a nonlinear optimization method to enhance the performance and flexibility of a power system. This paper explores the use of particle swarm optimization (PSO) algorithm as an artificial intelligence technique to solve a single objective function of the optimal power flow problem. The objective function is the minimization of the transmission power losses by keeping the equality and inequality constraints on their secure limits. To test the effectiveness of the proposed method, different scenarios of the Nordic 44 model include maximum import to Norway and maximum export from Norway to the other Nordic networks, as well as hourly load data variations are tested with MATLAB software. The Nordic 44 model is the test system that has been used to analyze stability and control problems that are relevant to the Nordic power network. The test results show the convergence and effectiveness of the proposed method to solve OPF problem compared to Genetic Algorithm (GA) as intelligent method and OPF by MATPOWER as the other classical method to test convergence and effectiveness of the proposed method to solve OPF problem under various load cases (heavy and light loading) of Nordic 44 test system.