Abstract
In this study a hybrid algorithm - Fletcher Reeves method and advanced Genetic Algorithm (GA) are suggested to solve reactive power problem. In this approach, each of the G Fletcher Reeves method again with progressive operators are calculated step length. These approaches are extended to a set of multi-point access instead of single point approximation to avoid the convergence of the available method at local optimum and a new method, named Population Based Fletcher Reeves Method (PFR), are proposed to solve the reactive power problem. PFR was tested in standard IEEE 30 bus test system and simulation results demonstrate obviously about the best performance of the recommended algorithm in reducing the real power loss with control variables within the limits.
Highlights
In this study a hybrid algorithm - Fletcher Reeves method and advanced Genetic Algorithm (GA) are suggested to solve reactive power problem
Proposed Population Based Fletcher Reeves Method (PFR) was tested in standard IEEE 30 bus test system and simulation study indicate the best performance of the proposed algorithm
Validity of PFR algorithm has been verified by testing in IEEE 30-bus system, 41 branch system and it has 6 generator-bus voltage magnitudes, 4 transformer-tap settings, and 2 bus shunt reactive compensators
Summary
Where F- objective function, PL – power loss, gk conductance of branch,Vi and Vj are voltages at buses i,j, Nbrtotal number of transmission lines in electric power systems. TO till date various methodologies has been applied to solve the electrical reactive power problems. Many type of mathematical methodologies like linear programming, gradient method [1-8] has been utilized to solve the electrical reactive power problem, but they lack in handling the constraints to reach a global optimization solution. In the level various types of Evolutionary algorithms [9-20] has been applied to solve the reactive power problem. Proposed Population Based Fletcher Reeves Method (PFR) was tested in standard IEEE 30 bus test system and simulation study indicate the best performance of the proposed algorithm. VD - voltage deviation, ωv- is a weighting factor of voltage deviation
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