INTRODUCTION
The OPF is one of most important tool for achieving the economic and secure operation of the power system. The OPF problem solution aims to optimize a chosen objective function through optimal adjustment of the power system control variables while at the same time satisfying various operating constraints [1]. In its most general formulation, the OPF is a nonlinear, non-convex, large-scale, static optimization problem with both continuous and discrete control variables [2].
In recent years, various population-based metaheuristic optimization methods has been suggested for solving the OPF problem. Their main advantage compared to the classical (deterministic) optimization methods is that they are not limited with requirements for differentiability, non-convexity and continuity of the objective function or types of control variables. Moreover, these methods can be used for practical power systems taking into account various types of objective function and constraints. The essence of metaheuristic methods is iterative correction of solutions, ie. generating new populations by applying stochastic search operators on individuals from the current population. The main performances of metaheuristics are fast search of large solution spaces, ability to find global solutions and avoiding local optimum [3].
This paper presents an innovative approach to education in the field of optimal power flow. A computer program, called optimal power flow graphical user interface (opfgui ), has been developed to present the efficiency of different metaheuristic optimization methods in solving the OPF problem. In this context, the opfgui can be used as an experimentation tool during the practical lectures. The aim of this program is to encompass the main steps in solving the OPF problem using metaheuristic methods. These steps include: (i) selection of test system, display single-line diagram and edit system data; (ii) selection of objective function; (iii) selection of solution method, setting the algorithm parameters; (iv) program execution; (v) display of the results.
The opfgui has been implemented in MATLAB, because it integrates computation, programming, analyze data, and producing graphical displays and graphical user interfaces in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation [4]. When designing the program, special care was paid to its graphical user interface, so the opfgui is very friendly to the students.
The opfgui program offers a choice of seven standard IEEE test systems, six objective functions, and ten optimization methods. The program generates not only optimal solution, that is, optimum control variables and objective function, but also important results such as, convergence profile, bus voltages and bus powers, brunch power flows and losses, violating constraints (if exist), and statistical evaluation of the results. Using opfgui , the students can compare the performances of different optimization methods based on statistical evaluation of the results.
The rest of the paper is organized as follows: In the Optimal Power Flow Problem Formulation, the OPF problem is mathematically formulated. In the section Metaheuristic Optimization Methods, ten optimization methods are briefly described. The program is described in OPF Software section. The use of opfgui is presented in section Educational Example. In the final section the main conclusions of the paper are given.