Advanced feasibility cuts in decoupled cooperative optimization of power flow. (January 2022)

• Record Type: Journal Article
• Authors: Varelmann, Tim; Lipow, Adrian W.; Baldea, Michael; Mitsos, Alexander
• Is Part Of: Computers & chemical engineering. Volume 157(2022)
• Publication Date: 2022-01
• Subjects: Demand-side management -- Cooperative optimal power flow -- Congestion management -- Cutting plane algorithm; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2021.107635
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Cutting plane generation problems can be formulated with different normalizations. A novel normalization leads to better cuts, improving algorithmic performance. Our previous normalization leads to better feasible points. We solve cooperative OPF problems with up to 17 cooperating loads. Abstract: Solving the optimal power flow problem in a cooperative way between power generators and industrial users can reduce electricity costs more effectively than price-based demand side management. In previous work, we recently developed a decomposition-based algorithm based on Benders-type cuts to solve cooperative optimal power flow problems, which allows to protect sensitive load information. However, the algorithm suffers from unfavorable scaling behavior when the number of cooperating load entities increases. Herein, we improve the quality of the cutting planes that cooperating electricity users generate for the grid in lieu of sharing their dynamic process models. After comparing different cutting strategies and combinations thereof, we develop a tailored cutting strategy. This strategy improves the scaling behavior of our decomposition-based algorithm with multiple cooperating electricity user locations drastically. We obtain speedups factors up to almost 60 compared to our algorithm with the initial cutting strategy.