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A decentralized framework for the optimal coordination of distributed energy resources

Miguel F. Anjos(anjos***at***stanfordalumni.org)
Andrea Lodi(andrea.lodi***at***polymtl.ca)
Mathieu Tanneau(mathieu.tanneau***at***polymtl.ca)

Abstract: Demand-response aggregators are faced with the challenge of how to best manage numerous and heterogeneous Distributed Energy Resources (DERs). This paper proposes a decentralized methodology for optimal coordination of DERs. The proposed approach is based on Dantzig-Wolfe decomposition and column generation, thus allowing to integrate any type of resource whose operation can be formulated within a mixed-integer linear program. We show that the proposed framework offers the same performance guarantees as a centralized formulation, with the added benefits of distributed computation. The practical efficiency of the algorithm is demonstrated through extensive computational experiments, on a set of 1120 instances generated using data from Ontario energy markets. The proposed approach was able to solve all test instances to proven optimality, while achieving significant speed-ups over a centralized formulation solved by state-of-the-art optimization software.

Keywords: Column generation, Dantzig-Wolfe decomposition, demand response aggregation, distributed energy resources, mixed-integer linear programming, smart grid

Category 1: Applications -- Science and Engineering (Smart Grids )

Category 2: Integer Programming ((Mixed) Integer Linear Programming )

Citation: Technical Report, Polytechnique Montreal, Department of Mathematics and Industrial Engineering, Montreal, QC, Canada & Groupe d’études et de recherche en analyse des décisions (GERAD), Montréal, QC, Canada

Download: [PDF]

Entry Submitted: 12/19/2017
Entry Accepted: 12/19/2017
Entry Last Modified: 12/19/2017

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