TY  - JOUR
T1  - Economic Operation of Power Wheeling under Deregulated
Environment Using Soft Computing
AU - , Anumeha, AU - Agrawal, S. AU - Yadav, K.B. AU - Kumar, Jayendra 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 8
SP  - 2183
EP  - 2189
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.2183.2189
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.2183.2189
KW  - power system
KW  - particle swarm optimization
KW  -gravitational search algorithm
KW  -Soft computing optimization
KW  -MW-mile method
KW  -power wheeling
AB  - The electric power industry is undergoing many fundamental changes due to implementation of
deregulation policy. Traditionally, the electric power systems were structured vertically integrated, providing
the three services generation, transmission and distribution by a single party. After deregulation the three
service sectors may be operated (provided) by different company or party. As such the power can be generated
by a company, it could be sold to any other company for distribution at load centers and it may be transmitted
by a third party from the generation point of selling point (load center/buyer), i.e., power wheeling from the
generation point to the distribution point (buyer). In this study, it is proposed to consider the economic power
wheeling from the generation point to the distribution point through Gravitational Search Algorithm (GSA) on
the basis of MW-Mile method under two operating conditions with and without transmission line power limit.
The method is explained by an example of 4-grid power system. The result of GSA method is compared with the
result obtained by Particle Swarm Optimization (PSO) method. It has been shown that the GSA method is more
efficient than the PSO method as the computation time by GSA is less than computation time by PSO
method.
ER  -