Optimal Long-Term Distributed Generation Planning and Reconfiguration of Distribution Systems: An Accelerating Benders’ Decomposition Approach

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 conve...

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Vydané v:Journal of optimization theory and applications Ročník 179; číslo 1; s. 283 - 310
Hlavní autori: Khodayifar, Salman, Raayatpanah, Mohammad A., Rabiee, Abbas, Rahimian, Hamed, Pardalos, Panos M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.10.2018
Springer Nature B.V
Predmet:
Applications of Mathematics
Benders decomposition
Calculus of Variations and Optimal Control; Optimization
Distributed generation
Engineering
Mathematics
Mathematics and Statistics
Nonlinear programming
Operations Research/Decision Theory
Optimization
Production scheduling
Reconfiguration
Theory of Computation
Multi-period optimal power flow
Benders’ decomposition
90C30
90C11
90C06
Distributed generation
90C27
Combinatorial optimization
Non-convex mixed-integer nonlinear programming
Semi-definite programming
ISSN:0022-3239, 1573-2878
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-018-1367-5