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View all- Zhang LZhang B(2022)Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach2022 North American Power Symposium (NAPS)10.1109/NAPS56150.2022.10012237(1-6)Online publication date: 9-Oct-2022
An iterative approach to improving solution quality for AC optimal power flow problems
Authors: 
Ling Zhang, Baosen ZhangAuthors Info & Claims
Ling Zhang, Baosen ZhangAuthors Info & ClaimsPages 289 - 301
Abstract
The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades. Existing solvers are generally successful in finding local solutions, which satisfy first and second order optimality conditions, but may not be globally optimal. In this paper, we propose a simple iterative approach to improve the quality of solutions to ACOPF problems. First, we call an existing solver for the ACOPF problem. From the solution and the associated dual variables, we form a partial Lagrangian. Then we optimize this partial Lagrangian and use its solution as a warm start to call the solver again for the ACOPF problem. By repeating this process, we can iteratively improve the solution quality, moving from local solutions to global ones. We show the effectiveness of our algorithm on standard IEEE networks. The simulation results show that our algorithm can escape from local solutions to achieve global optimums within a few iterations.
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Published: 28 June 2022
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View all- Zhang LZhang B(2022)Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach2022 North American Power Symposium (NAPS)10.1109/NAPS56150.2022.10012237(1-6)Online publication date: 9-Oct-2022
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