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Journal Articles Journal of Global Optimization Year : 2023

Configuring an heterogeneous smartgrid network: complexity and approximations for tree topologies

Abstract

We address the problem of configuring a power distribution network with reliability and resilience objectives by satisfying the demands of the consumers and saturating each production source as little as possible. We consider power distribution networks containing source nodes producing electricity, nodes representing electricity consumers and switches between them. Configuring this network consists in deciding the orientation of the links between the nodes of the network. The electric flow is a direct consequence of the chosen configuration and can be computed in polynomial time. It is valid if it satisfies the demand of each consumer and capacity constraints on the network. In such a case, we study the problem of determining a feasible solution that balances the loads of the sources, that is their production rates. We use three metrics to measure the quality of a solution: minimizing the maximum load, maximizing the minimum load and minimizing the difference of the maximum and the minimum loads. This defines optimization problems called respectively min-M, max-m and min-R. In the case where the graph of the network is a tree, it is known that the problem of building a valid configuration is polynomial. We show the three optimization variants have distinct properties regarding the theoretical complexity and the approximability. Particularly, we show that min-M is polynomial, that max-m is NP-Hard but belongs to the class FPTAS and that min-R is NP-Hard, cannot 1 be approximated to within any exponential relative ratio but, for any ε > 0, there exists an algorithm for which the value of the returned solution equals the value of an optimal solution shifted by at most ε.
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Dates and versions

hal-04289472 , version 1 (17-11-2023)

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Cite

Dominique Barth, Thierry Mautor, Dimitri Watel, Marc-Antoine Weisser. Configuring an heterogeneous smartgrid network: complexity and approximations for tree topologies. Journal of Global Optimization, 2023, ⟨10.1007/s10898-023-01338-0⟩. ⟨hal-04289472⟩
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