Transmission network expansion planning considering weighted transmission loading relief nodal indexes

Abstract

This paper presents a model and a solution approach for the transmission network expansion planning (TNEP) problem that integrates security constraints given by weighted transmission loading relief (WTLR) indexes. Such indexes integrate shift and power distribution factors and allow to measure the severity of overloads in normal conditions and under any single contingency. Furthermore, the inclusion of small-scale generation was considered as complementary to TNEP solutions. The proposed model was solved by means of the metaheuristic NSGA-II (Non-dominated Sorting Genetic Algorithm II), which enabled to find a set of solutions that represent a trade-off between the cost of the expansion plan and its security level. Several tests were performed on the 6-bus Garver system and the IEEE 24-bus reliability test system, thus showing the applicability of the proposed approach. It was found that the inclusion of small-scale generation in strategic nodes allows to reduce the cost of expansion plans and increases their level of security for single contingencies.

Long-Term Multiyear Transmission Expansion Planning in Turkish Power System

“…In the solution of TEP, novel metaheuristic algorithms such as constructive metaheuristic algorithm (CMA) [25], tree searching heuristic algorithm (TSHA) [26], orthogonal crossover-based diferential evolution (OXDE) [27], teaching learning-based optimization (TLBO) [28], shufed frog leap algorithm (SFLA) [29], and salp swarm algorithm (SSA) [30] have been widely used in recent years. In addition to novel approaches, relatively old metaheuristic algorithms such as particle swarm optimization (PSO) [31], nondominated sorting genetic algorithm-2 (NSGA-2) [32], ant colony optimization (ACO) [33], artifcial bee colony (ABC) [34], and grey wolf optimization (GWO) [35] continue to be used in TEP studies.…”

Evaluación de modelos de programación lineal y no lineal para la planeación de sistemas de transmisión en el software GAMS

“…Entre estos métodos se incluyen los de optimización convencionales (Nguyen y Santoso, 2021,Zhang, [18] 2013), los de inteligencia de inteligencia artificial (Ruan et al, 2020), los heurísticos (Lu et al, 2007) y los metaheurísticos (Morquecho et al, 2021, Saldarriaga-Zuluaga et al, 2019. A continuación se presenta el modelo para algunas de las estrategias utilizadas para el OPTS.…”