Bio-inspired metaheuristics applied to Volt/VAr Control optimization problem in smart grid context

摘要

Voltage quality can be improved in modern smart grids through Volt/VAr Control (VVC). Integrated VVC based on a distribution system model is an approach that meets all the requirements for VVC in this context. One of the main challenges for solving the VVC optimization problem is the huge search space, leading to unacceptable computational time to find the optimal solution. This paper presents a performance comparison between different bio-inspired metaheuristics applied to the VVC optimization problem. Methods considered in this paper include ant colony optimization, canonical genetic algorithm and its variants as well as the memetic algorithm. All methods were implemented and evaluated for a midsize distribution feeder and results on convergence speed and solution quality were compared.