AC Dynamic Transmission Expansion Planning Using Memetic Algorithms

被引：0

作者：

Luna, Carlos A. ^{[1
]}

Carangui, Martin S. ^{[1
]}

Torres, Santiago P. ^{[1
]}

Jara-Alvear, Jose ^{[2
]}

Gavela, Ximena P. ^{[3
]}

Siguenza-Guzman, Lorena ^{[4
]}

Ballari, Daniela ^{[5
]}

Zurita, Ana F. ^{[6
]}

机构：

[1] Univ Cuenca, Dept Elect Elect & Telecommun Engn DEET, Cuenca, Ecuador

[2] Univ Azuay UDA, CIENER Res Grp, Cuenca, Ecuador

[3] Escuela Politec Nacl, Dept Elect Engn, Quito, Ecuador

[4] Univ Cuenca, Dept Comp Sci, Cuenca, Ecuador

[5] Univ Azuay, Inst Estudios Regimen Secc Ecuador, Fac Sci & Technol, Cuenca, Ecuador

[6] Corporac Elect Ecuador CELEC EP, Cuenca, Ecuador

来源：

2023 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES LATIN AMERICA, ISGT-LA | 2023年

关键词：

AC Model; Dynamic Transmission Expansion; Planning; Hill Climbing; Memetic Algorithm; Optimization; Particle Swarm Optimization (PSO); Renewable Energy;

D O I：

10.1109/ISGT-LA56058.2023.10328269

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The objective of Dynamic Transmission Expansion Planning (DTEP) is to determine which, where, and when electric infrastructure should be added to a power system within a planning horizon. Adding new components to the system aims to meet future demand and efficiency parameters such as service quality, reliability, and economy. Few research works aim to solve the DTEP problem using the AC network model. In this research work, a solution method using Memetic Algorithms (MA) is proposed. The solution method solves the DTEP problem by combining population-based solution techniques and local search. The full non-convex AC model is used to deal with the DTEP problem. The proposed algorithm combines the Particle Swarm Optimization (PSO) metaheuristic with the Hill Climbing local search technique and it is evaluated using the Garver system.

引用

页码：510 / 514

页数：5

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