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Pré-Publication, Document De Travail Année : 2023

Solving a bilevel stochastic generation and transmission expansion planning problem

Résumé

We consider a strategic version of a stochastic generation and transmission expansion planning problem. This problem is tackled by the French Transmission System Operator for producing prospective reports on the evolution of the electricity network. We study how a regulatory constraint limiting the loss of load expectation (i.e., a measure of unserved demand) can be incorporated into the problem. We show that the resulting problem is a bilevel problem in which the leader and follower have the same objective function. We propose a heuristic method for this problem that embeds a Benders decomposition algorithm in a binary search on the total investment cost. For each investment value tested, the algorithm disregards the regulatory constraint as well as the bilevel nature of the problem, and tests a posteriori whether the computed solutions can be converted to feasible solutions to the problem. We performed computational experiments on randomly generated instances to study the practical difficulty of the problem and validate the proposed solution method. We show that solving the KKT reformulation of the problem is intractable even for our small instances, whereas our heuristic method produces feasible solutions even for large instances.
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Dates et versions

hal-03957750 , version 1 (26-01-2023)
hal-03957750 , version 2 (21-07-2023)

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Paternité

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  • HAL Id : hal-03957750 , version 1

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Xavier Blanchot, François Clautiaux, Aurélien Froger, Manuel Ruiz. Solving a bilevel stochastic generation and transmission expansion planning problem. 2023. ⟨hal-03957750v1⟩
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