Optimal planning of a soft open point in a distribution network subject to typhoons

While Soft Open Point (SOP) shows its strong capability to control load transfer and regulate network voltage profile in a distribution network, there are limited considerations of the high investment costs of these special electric devices. This gap may hinder optimal planning of an SOP and even affect its wide usage in a distribution network. This paper proposes an optimal planning method for an SOP that fully considers the cost of an SOP in a coastal network where typhoon frequently lands. The benefit of the SOP consists of the reduction of energy loss in daily operations and the post-fault supply restorations under extreme typhoon environment. The evaluation of the benefit of the SOP from the reduction of energy loss in daily operations is based on simulations of multiple scenarios in the long-term life cycle of the SOP. In order to evaluate the damages to the distribution network from typhoon, the virtual typhoon samples are generated from historical data in the entire period of the life cycle of the SOP. A practical algorithm is designed for the scanning of the possible formations of islands that can be restored by an SOP when typhoon lands. In the end of the paper, both the location and the capacity of an SOP are optimized considering the balance among the benefit of energy-loss reduction in daily operations, the benefit of supply restoration after typhoon lands, and the investment and operation costs of the SOP. From numerous simulations, it is validated that implementing only one SOP in the distribution network is both optimal and practical in most simulation cases due to the restrictions of the extremely high implement costs of SOP, and this may greatly simplify the complexity of the optimal planning problem for the SOP in a distribution network.

Automated summary

This paper proposes an optimal planning method for an SOP in a coastal network, fully considering the cost and benefits, and evaluates the benefits of SOP through simulations of multiple scenarios.