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Approximate dynamic programming with feasibility guarantees

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Bibliographic Details
Title: Approximate dynamic programming with feasibility guarantees
Authors: Engelmann, Alexander, Faulwasser, Timm
Source: IEEE transactions on control of network systems. 12(2):1565-1576
Publisher Information: 2025.
Publication Year: 2025
Subject Terms: ADP | flexibility aggregation | hierarchical optimization | large-scale optimization | tree structures | TSO-DSO coordination
Description: Safe and economic operation of networked systems is challenging. Optimization-based schemes are frequently considered, since they achieve near-optimality while ensuring safety via the explicit consideration of constraints. In applications, these schemes often require solving large-scale optimization problems. Iterative techniques from distributed optimization are frequently proposed for complexity reduction. Yet, they achieve feasibility only asymptotically, which induces a substantial computational burden. This work presents an approximate dynamic programming scheme, which is guaranteed to deliver a feasible solution in "one shot", i.e., in one backward-forward iteration over all subproblems provided they are coupled by a tree structure. Our approach generalizes methods from seemingly disconnected domains such as power systems and optimal control. We demonstrate its efficacy for problems with nonconvex constraints via numerical examples from both domains.
Document Type: Article
Language: English
ISSN: 2325-5870
Accession Number: edsair.dris...01170..4672f29b39ae6f5b53d1a459ceb7d294
Database: OpenAIRE
Description
Abstract:Safe and economic operation of networked systems is challenging. Optimization-based schemes are frequently considered, since they achieve near-optimality while ensuring safety via the explicit consideration of constraints. In applications, these schemes often require solving large-scale optimization problems. Iterative techniques from distributed optimization are frequently proposed for complexity reduction. Yet, they achieve feasibility only asymptotically, which induces a substantial computational burden. This work presents an approximate dynamic programming scheme, which is guaranteed to deliver a feasible solution in "one shot", i.e., in one backward-forward iteration over all subproblems provided they are coupled by a tree structure. Our approach generalizes methods from seemingly disconnected domains such as power systems and optimal control. We demonstrate its efficacy for problems with nonconvex constraints via numerical examples from both domains.
ISSN:23255870