Social spider algorithm for solving the transmission expansion planning problem

2017 ◽  
Vol 143 ◽  
pp. 235-243 ◽  
Author(s):  
M.S. El-bages ◽  
W.T. Elsayed
Keyword(s):  
Planning Problem ◽  
Social Spider ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Social Spider Algorithm

scholarly journals Analysis of Constraint-Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Lourdes Martínez-Villaseñor ◽  
Hiram Ponce ◽  
José Antonio Marmolejo-Saucedo ◽  
Juan Manuel Ramírez ◽  
Agustina Hernández
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Stochastic Approach ◽  
Constraint Handling ◽  
Complex Case ◽  
Planning Problem ◽  
Electricity Grid ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion

A multiperiod generation and transmission expansion planning (G&TEP) problem is considered. This model integrates conventional generation with renewable energy sources, assuming a stochastic approach. The proposed approach is based on a centralized planned transmission expansion. Due to the worldwide recent energy guidelines, it is necessary to generate expansion plans adequate to the forecast demand over the next years. Nowadays, in most energy systems, a public entity develops both the short and long of electricity-grid expansion planning. Due to the complexity of the problem, there are different strategies to find expansion plans that satisfy the uncertainty conditions addressed. We proposed to address the G&TEP problem with a pure genetic algorithm approach. Different constraint-handling techniques were applied to deal with two complex case studies presented. Numerical results are shown to compare the strategies used in the test systems, and key factors such as a prior initialization of population and the estimated minimum number of generations are discussed.

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