Solving Bilevel AC OPF Problems by Smoothing the Complementary Conditions - Part II: Solution Techniques and Case Study

This is a second part of the research on AC optimal power flow being used in the lower level of the bilevel strategic bidding or investment models. As an example of a suitable upper-level problem, we observe a strategic bidding of energy storage and propose a novel formulation based on the smoothing technique. After presenting the idea and scope of our work, as well as the model itself and the solution algorithm in the companion paper (Part I), this paper presents a number of existing solution techniques and the proposed one based on smoothing the complementary conditions. The superiority of the proposed algorithm and smoothing techniques is demonstrated in terms of accuracy and computational tractability over multiple transmission networks of different sizes and different OPF models. The results indicate that the proposed approach outperforms all other options in both metrics by a significant margin. This is especially noticeable in the metric of accuracy where out of total 422 optimizations over 9 meshed networks the greatest AC OPF error is 0.023% that is further reduced to 3.3e-4% in the second iteration of our algorithm.

Automated summary

This paper is the second part of a research on using AC optimal power flow in the lower level of bilevel strategic bidding or investment models. The strategic bidding of energy storage is used as an example of an upper-level problem, and a novel formulation based on the smoothing technique is proposed. Existing solution techniques and the proposed one based on smoothing the complementary conditions are presented and compared in terms of accuracy and computational tractability. The results show that the proposed algorithm and smoothing techniques outperform other options, with a significant improvement in accuracy.