Rapid Feasibility Assessment of Energy Unit Integration in Distribution Networks

In contemporary heavy-load distribution networks, preceding feasibility assessment is imperative before incorporating additional energy units. However, the feasibility examination for massive combined operational scenarios of relevant units is computationally intensive with repetitive power flow calculations. To this end, this paper proposes a rapid assessment framework, the kernel of which is to learn from formerly examined scenarios, thus forming expansive feasible/infeasible regions to geometrically rule in/out subsequent scenarios. By sidestepping the power flow computation in most scenarios, we accelerate the assessment process. Furthermore, enlightened by heuristic hypersurface search, such prechecking efficiency can be boosted by resorting the scenario sequence. In a risk-averse manner, this framework can be conceptualized using the exact grid model, though it is initially designed for the convex grid model. Evidenced by testing on two different-scale distribution grids, the framework shows a significant assessment efficiency improvement and strict accuracy guarantee, where we observe at least 76.13% assessment time reduction and zero accuracy loss. We anticipate this work to be a starting point for more sophisticated geometry-accelerating feasibility assessment methods.

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Publication Details

Journal
IEEE Transactions on Power Systems
Published
2024-09-02
DOI
https://doi.org/10.1109/tpwrs.2024.3453043
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.00

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article

Rapid Feasibility Assessment of Energy Unit Integration in Distribution Networks

Sicheng Gong, Koen Kok, J.F.G. Cobben
IEEE Transactions on Power Systems
Optimal Power Flow Distribution
article

Rapid Feasibility Assessment of Energy Unit Integration in Distribution Networks

Sicheng Gong, Koen Kok, J.F.G. Cobben
article en

Abstract

In contemporary heavy-load distribution networks, preceding feasibility assessment is imperative before incorporating additional energy units. However, the feasibility examination for massive combined operational scenarios of relevant units is computationally intensive with repetitive power flow calculations. To this end, this paper proposes a rapid assessment framework, the kernel of which is to learn from formerly examined scenarios, thus forming expansive feasible/infeasible regions to geometrically rule in/out subsequent scenarios. By sidestepping the power flow computation in most scenarios, we accelerate the assessment process. Furthermore, enlightened by heuristic hypersurface search, such prechecking efficiency can be boosted by resorting the scenario sequence. In a risk-averse manner, this framework can be conceptualized using the exact grid model, though it is initially designed for the convex grid model. Evidenced by testing on two different-scale distribution grids, the framework shows a significant assessment efficiency improvement and strict accuracy guarantee, where we observe at least 76.13% assessment time reduction and zero accuracy loss. We anticipate this work to be a starting point for more sophisticated geometry-accelerating feasibility assessment methods.

IEEE Transactions on Power SystemsVol. 40(2)
Eindhoven University of Technology (NL)
Technische Universiteit Eindhoven
Affordable and clean energy
Openalex Percentile: Top 88%
Optimal Power Flow Distribution
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