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.