By Topic

New dynamic, branch exchange method for optimal distribution system planning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
G. J. Peponis ; Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece ; M. P. Papadopoulos

The optimisation of distribution system expansion planning constitutes a combinatorial problem. The application of accurate methods has been restricted to power systems of small size, while approximate but more effective heuristic methods have been proposed. This paper presents a new, branch exchange method for the optimisation of multiyear distribution system planning. The problem is faced in two steps: first, a set of economical and technically accepted system configurations is constructed; second, the optimal sequence of system configurations, for a multiyear study period, is determined based on the set of economical configurations. The proposed method is fully dynamic, models accurately the economical and technical data and constraints, while all the power system reinforcement and extension alternatives are modelled and optimised. The effectiveness is demonstrated by applications on a 134 node and 177 branch typical distribution system. Load patterns, for two different seasons, are used to model load variations, while the installation or construction of capacitors, voltage regulators, lines and substations is optimised

Published in:

IEE Proceedings - Generation, Transmission and Distribution  (Volume:144 ,  Issue: 3 )