Work

An evolutionary computational approach for the identification of distribution networks models

Year: 2024

Type: article

Abstract: In this paper, we present a novel methodology for generating low-voltage distribution network models. The methodology is based on leveraging the existing knowledge of the network topology and a comprehensive catalog of the conductors that are installed in each segment of the grid. By using genetic algorithms and data obtained from the smart-meters in the network, the proposed method can produce highly accurate network models. The effectiveness of this methodology has been confirmed by extensive simulation studies achieving errors of less than 0.4 V in the estimation of nodal voltages in scenarios without measurements noise and on the order of the standard deviation of the error considered in the measurements when disturbances are added to the problem.

Source: Engineering Applications of Artificial Intelligence

DOI: 10.1016/j.engappai.2024.109184

Authors: Álvaro Rodríguez del Nozal, Rubén Carmona-Pardo, Juan M. Mauricio, Esther Romero-Ramos

Institution: Universidad de Sevilla

Language: English

Topic: Optimal Power Flow Distribution

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: hybrid

Estimated APC paid: $3,270