Improved Genetic Algorithm Approach for Multi-Objective contingency constrained Reactive Power Planning

Reactive Power Planning (RPP) is one of the important tasks in the operation and control of power system. This paper presents a Genetic Algorithm (GA) based approach for solving the contingency-constrained reactive power optimization problem. Voltage bus magnitude, transformer tap setting and reactive power generation of capacitor bank are the control variables. A binary-coded GA with tournament selection, two point crossover and bit-wise mutation is used to solve this complex optimization problem. In the proposed algorithm, some modifications are applied to the original GA in order to take into account the discrete nature of transformer tap setting and capacitor bank. The proposed approach has been evaluated with four different objective functions namely, loss minimization, voltage profile improvement, voltage stability enhancement and total cost minimization. Voltage stability level of the system is defined based on the L-index of load buses. The optimal locations of the VAR sources are also identified using the GA based algorithm. The proposed algorithm has been tested on IEEE 30-bus and IEEE 57-bus test systems and successful results have been obtained.