Economics-based transmission expansion planning in restructured power systems using decimal codification genetic algorithm

2011 ◽  
Author(s):  
Vahid Asadzadeh ◽  
Masoud Aliakbar Golkar ◽  
S. Masoud Moghaddas-Tafreshi
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion

scholarly journals Optimal Transmission Expansion Planning considering Distributed Generations by using Non-dominated sorting genetic algorithm-II (NSGAII)

2020 ◽  
Author(s):  
Mehrdad Ahmadi Kamarposhti ◽  
Ersan Kabalci ◽  
Reza Alayi
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Mixed Integer ◽  
Distributed Generations ◽  
Multi Objective ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Multi Objective Genetic Algorithm ◽  
Integer Problem

Reconstructing power systems has changed the traditional planning of power systems and has raised new challenges in transmission expansion planning (TEP). In this paper, investment cost, cost of density and dependability have been considered three objectives of optimization. Also, multi-objective genetic algorithm NSGAII was used to solve this non-convex and mixed integer problem. A fuzzy decision method has been used to choose the final optimal answer from the Pareto solutions obtained from NSGAII. Moreover, to confirm the efficiency of NSGAII multi-objective genetic algorithm in solving TEP problem, the algorithm was implemented in an IEEE 24 bus system and the gained results were compared with previous works in this field.

scholarly journals Scenario Selection for Iterative Stochastic Transmission Expansion Planning

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1203 ◽  
Author(s):  
Faezeh Akhavizadegan ◽  
Lizhi Wang ◽  
James McCalley
Keyword(s):  
Power Systems ◽  
Accurate Estimation ◽  
High Quality ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Generation Capacity ◽  
Temporal Dimensions ◽  
Selection Algorithms

Reliable transmission expansion planning is critical to power systems’ development. To make reliable and sustainable transmission expansion plans, numerous sources of uncertainty including demand, generation capacity, and fuel cost must be taken into consideration in both spatial and temporal dimensions. This paper presents a new approach to selecting a small number of high-quality scenarios for transmission expansion. The Kantorovich distance of social welfare distributions was used to assess the quality of the selected scenarios. A case study was conducted on a power system model that represents the U.S. Eastern and Western Interconnections, and ten high-quality scenarios out of a total of one million were selected for two transmission plans. Results suggested that scenarios selected using the proposed algorithm were able to provide a much more accurate estimation of the value of transmission plans than other scenario selection algorithms in the literature.

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