Transmission Network Expansion Planning With Complex Power Flow Models

2012 ◽  
Vol 27 (2) ◽  
pp. 904-912 ◽  
Author(s):  
Russell Bent ◽  
G. Loren Toole ◽  
Alan Berscheid
Keyword(s):  
Power Flow ◽  
Transmission Network ◽  
Flow Models ◽  
Network Expansion ◽  
Expansion Planning ◽  
Complex Power

Transmission Network Expansion Planning with Security Constraints and Uncertainty in Load Specifications

2008 ◽  
Vol 9 (4) ◽  
Author(s):  
Ashu Verma ◽  
Pradeep R. Bijwe ◽  
Bijaya Ketan Panigrahi
Keyword(s):  
Power Flow ◽  
Planning Problem ◽  
Transmission Network ◽  
Network Expansion ◽  
Security Issues ◽  
Expansion Planning ◽  
Dc Power ◽  
Sample Test ◽  
Binary Genetic Algorithm ◽  
Long Range Planning

Transmission network expansion planning is a very critical problem due to not only the huge investment cost involved, but also the associated security issues. Any long range planning problem is confronted with the challenge of non-statistical uncertainty in the data. Although large number of papers have been published in this area, the efforts to tackle the above mentioned security and uncertainty issues have been relatively very few, due to the formidable complexity involved. This paper tries to bridge this gap by proposing a technique to tackle these problems. Boundary DC power flow is used to ascertain the worst power flows on the lines. A simple basic binary Genetic algorithm is used to solve the optimization problem as an illustration. Results for two sample test systems have been obtained to demonstrate the potential of the proposed method.

A Comparative Study of Metaheuristic Methods for Transmission Network Expansion Planning

2012 ◽  
pp. 319-339 ◽  
Author(s):  
Ashu R. Verma ◽  
P. K. Bijwe ◽  
B. Panigrahi
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Optimization Techniques ◽  
Transmission Network ◽  
Swarm Optimization ◽  
Network Expansion ◽  
Expansion Planning ◽  
Dc Power ◽  
Metaheuristic Methods ◽  
Discrete Nature

Transmission network expansion planning is a very complex and computationally demanding problem due to the discrete nature of the optimization variables. This complexity has increased even more in a restructured deregulated environment. In this regard, there is a need for development of more rigorous optimization techniques. This paper presents a comparative analysis of three metaheuristic algorithms known as Bacteria foraging (BF), Genetic algorithm (GA), and Particle swarm optimization (PSO) for transmission network expansion planning with and without security constraints. The DC power flow based model is used for analysis and results for IEEE 24 bus system are obtained with the above three metaheuristic drawing a comparison of their performance characteristic.

A Comparative Study of Metaheuristic Methods for Transmission Network Expansion Planning

2010 ◽  
Vol 1 (4) ◽  
pp. 71-91 ◽  
Author(s):  
Ashu R. Verma ◽  
P. K. Bijwe ◽  
B. Panigrahi
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Optimization Techniques ◽  
Transmission Network ◽  
Swarm Optimization ◽  
Network Expansion ◽  
Expansion Planning ◽  
Dc Power ◽  
Metaheuristic Methods ◽  
Discrete Nature

Transmission network expansion planning is a very complex and computationally demanding problem due to the discrete nature of the optimization variables. This complexity has increased even more in a restructured deregulated environment. In this regard, there is a need for development of more rigorous optimization techniques. This paper presents a comparative analysis of three metaheuristic algorithms known as Bacteria foraging (BF), Genetic algorithm (GA), and Particle swarm optimization (PSO) for transmission network expansion planning with and without security constraints. The DC power flow based model is used for analysis and results for IEEE 24 bus system are obtained with the above three metaheuristic drawing a comparison of their performance characteristic.

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