Abstract
In this paper, we study the multi-period distributed generation planning problem in a multistage hierarchical distribution network. We first formulate the problem as a non-convex mixed-integer nonlinear programming problem. Since the proposed model is non-convex and generally hard to solve, we convexify the model based on semi-definite programming. Then, we use a customized Benders’ decomposition method with valid cuts to solve the convex relaxation model. Computational results show that the proposed algorithm provides an efficient way to solve the problem for relatively large-scale networks.
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The authors are grateful to the editors for their constructive comments, which helped us improve the presentation of this paper substantially.
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Khodayifar, S., Raayatpanah, M.A., Rabiee, A. et al. Optimal Long-Term Distributed Generation Planning and Reconfiguration of Distribution Systems: An Accelerating Benders’ Decomposition Approach. J Optim Theory Appl 179, 283–310 (2018). https://doi.org/10.1007/s10957-018-1367-5
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DOI: https://doi.org/10.1007/s10957-018-1367-5
Keywords
- Combinatorial optimization
- Distributed generation
- Multi-period optimal power flow
- Non-convex mixed-integer nonlinear programming
- Semi-definite programming
- Benders’ decomposition