Enhanced Genetic Algorithm Based Model for Power System Optimal Load Flow

An Enhanced genetic algorithm (EGA) which is used to the solution of the optimal load flow (OPF) with both continuous and discrete control variables. The tenuous control variables modeled are unit active power outputs and generator–bus voltage magnitudes while the discrete ones are transformer – tap settings and switchable shunt devices. A number of functional operating constraints, such as branch flow limits, load bus voltage magnitude limits, and generator reactive capabilities, are included as penalties in the GA fitness function (FF). Advanced and problem specific Operators are introduced in order to enhance the algorithm’s efficiency and accuracy. A load flow analysis solves for the flows and voltages at all points in the system. On a typical system, those values are measured at only a handful of points (typically substations). A load flow lets you determine conditions throughout the entire system. Load flow analysis is fast, versatile, and powerful. Traditional load flow algorithms are not always suitable for the configuration, size or loading conditions found on distribution systems. Numerical results for the given test systems are compared with the results of other approaches. KeywordsEnhanced genetic algorithm (EGA), optimal power flow (OPF), Bus admittance matrix, Generator bus voltage modeling, load flow analysis, network layers, fitness function (FF), and penalty factor.