Reactive Power Optimization Using Genetic Algorithm

Resource Overview

Implementation of reactive power optimization on a 12-node test case using genetic algorithm - ready-to-run with optimized results

Detailed Documentation

This implementation applies genetic algorithm to solve reactive power optimization for a 12-node power system case study. The code is configured to execute directly and produce optimal compensation solutions. The genetic algorithm implementation includes fitness functions evaluating power loss minimization, voltage constraint handling, and population evolution operators for capacitor placement optimization. The solution automatically converges to the best configuration through selection, crossover, and mutation operations while maintaining system stability constraints.