Transmission Network Expansion Planning of a Large Power System

Author(s):  
Gerald Sanchís
Author(s):  
Ashu Verma ◽  
Soumya Das ◽  
P. R. Bijwe

Abstract Transmission network expansion planning (TNEP) is an important and computationally very demanding problem in power system. Many computational approaches have been proposed to handle TNEP in the past. The problem is mixed integer, large scale and its complexity increases exponentially with the size of the system. Metaheuristic techniques have gained a lot of importance in last few years to solve the power system optimization problems, due to their ability to handle complex optimization functions and constraints. Many of them have been successfully applied for TNEP. The biggest challenge in these techniques is the requirement of large computational efforts. This paper uses a two-stage solution process to solve the TNEP problems. The first stage uses compensation based method to generate a quick, suboptimal solution. The valuable information contained in this solution is used to generate a set of heuristics aimed at drastically reducing the number of population for fitness evaluations required in the 2nd stage with application of metaheuristic method. The resulting hybrid approach produces very good quality solutions very efficiently. Results for 24 bus and 93 bus test systems have been obtained with the proposed method to ascertain the potential of the method in comparison to earlier approaches.


Author(s):  
Ashu Verma ◽  
Pradeep R. Bijwe ◽  
Bijaya Ketan Panigrahi

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.


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