Mar 12, 2020 · This work presents the application of an adaptive non-dominated sorting genetic algorithm (ANSGA II) for optimal insertion of distributed generators (DG) in ...

This work presents the application of an adaptive non-dominated sorting genetic algorithm (ANSGA II) for optimal insertion of distributed generators (DG) in ...

An adaptive non-dominated sorting genetic algorithm (ANSGA II) for optimal insertion of distributed generators (DG) in radial distribution systems is ...

This method optimizes them simultaneously as multiple cost functions to find out non-dominated solutions set, named Pareto optimal front, instead of aiming to ...

The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system ...

In this paper, a comprehensive review on the optimal allocation of distributed generators was carried out for different objectives, constraints, and algorithms.

May 10, 2024 · “An adaptive NSGA II for optimal insertion of distributed generators in radial distribution systems.” 2019 International Conference on ...

This paper presents multi-objective optimization for optimal multi DG location and sizes in radial networks based on NSGA-II and Fuzzy logic to minimize ...

The findings recommend that the hybrid meta-heuristic algorithm be used for DG placement has it significantly improves voltage profile and lowers power loss.

In this article, in order to identify the optimal location of DGs, increase voltage stability and improve reliability in 119-bus distribution network,