Collective Intelligence for Optimal Power Flow Solution Using Ant Colony Optimization

This paper presents the performance ant collective intelligence efficiency for electrical network. Solutions for Optimal Power Flow (OPF) problem of a power system deliberate via an ant colony optimization metaheuristic method. The objective is to minimize the total fuel cost of thermal generating units and also conserve an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. Simulation results on the IEEE 30-bus electrical network show that the ant colony optimization method converges quickly to the global optimum

Electric distribution network optimal reconfiguration algorithm to contain operational costs

openIn this thesis an algorithm, made with python and padapower, is proposed to contain the operational costs of the distribution grid. The thesis analize the results of the algorithm and the benefits, from an economical point of view, in respect to the starting configuration of the grid. The possible operations considered are: driving the switchs in the net, building new lines or upgrading the existing ones and the curtailment of the generators.In this thesis an algorithm, made with python and pandapower, is proposed to contain the operational costs of the distribution grid. The thesis analize the results of the algorithm and the benefits, from an economical point of view, in respect to the starting configuration of the grid. The possible operations considered are: driving the switchs in the net, building new lines or upgrading the existing ones and the curtailment of the generators

Urban Transit Network Design Problems: A Review of Population-based Metaheuristics

The urban transit network design problem (UTNDP) involves the development of a transit route set and associated schedules for an urban public transit system. The design of efficient public transit systems is widely considered as a viable option for the economic, social, and physical structure of an urban setting. This paper reviews four well-known population-based metaheuristics that have been employed and deemed potentially viable for tackling the UTNDP. The aim is to give a thorough review of the algorithms and identify the gaps for future research directions