The power distribution network expansion planning based on stackelberg minimum weight K-star game

Document Type

Article

Publication Date

7-1-2013

Abstract

The reliability of power distribution network is important. For high reliability, it is necessary for some nodes to have backup connections to other feeders in the network. The substation operator wants to expand the network such that some nodes have k redundant connection lines (i.e., k redundancy) in case the current feeder line does not work. The corporation is given this task to design the expansion planning to construct new connection lines. The substation operator will choose the minimum charged k redundant connection lines based on both of the existing network and the expansion network, which is designed by the corporation. The existing network has the cost for the redundant connection due to the operational expense. The corporation proposes the design with its own price, which may include the operational expense and the construction expense. Thus, for the corporation, how to assign the low price on the connection lines while maximizing the revenue becomes a Stackelberg minimum weight k-star game for the power distribution network expansion. A heuristic algorithm is proposed to solve this Stackelberg minimum weight k-star game for the power distribution network expansion, using three heuristic rules for price setting in a scenario by scenario fashion. The experimental results show that the proposed algorithm always outperforms the greedy algorithm which is natural to k-star game in terms of corporation revenue. Compared to the greedy algorithm, the proposed algorithm improves up to 60.7% in the corporation revenue in the chosen minimum weight k-star, which is the minimum charged k connection lines. The average improvement is 7.5%. This effectively handles k redundancy in the power distribution network expansion while maximizing the corporation revenue. © 2013 World Scientific Publishing Company.

Publication Title

Journal of Circuits, Systems and Computers

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