Wind farm cable layout optimization with constraints of load flow and robustness - Archive ouverte HAL
Communication Dans Un Congrès Année : 2020

Wind farm cable layout optimization with constraints of load flow and robustness

Résumé

We consider an offshore wind farm defined by the location of the wind turbines and the amount of energy supplied per turbine, as well as the location of the central station responsible for redistributing the collected energy to users on the power grid. Knowing the power injected at each node, the capacities, susceptance and costs of the cables that can be used, the goal is to determine the least expensive cabling to route the energy supplied by the wind turbines to the central station. This cabling must respect the capacity constraints on the cables as well as the electrical constraints of Load Flow defined at each node of the network. In a second step, we look for a cabling that is also robust in case of failure of a cable, the notion of robustness being seen here as the protection again the worst case of failure. This work was carried out in collaboration with EDF Energies renouvelables. We give a mathematical model of the problem taking into account all the constraints of capacity, connectivity, load flow, cable types and incompatibility between edges, in the form of a mixed integer quadratic program that can be linearized and solved using a MIP solver. We then propose two mathematical models for the robust problem, formulation inspired by the previous one and a bi-level program where the second level is a max min program. Finally we present the results of our tests which provide solutions for real data up to about 50 nodes, before concluding.
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Dates et versions

hal-02967066 , version 1 (14-10-2020)

Identifiants

  • HAL Id : hal-02967066 , version 1

Citer

Cédric Bentz, Marie-Christine Costa, Pierre-Louis Poirion, Thomas Ridremont, Camille Zakour. Wind farm cable layout optimization with constraints of load flow and robustness. ICREEE 2020: International Conference on Renewable Energy and Environment Engineering, Dec 2020, Tokyo (on line), Japan. ⟨hal-02967066⟩
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