arXiv subjects

Anton Hinneck

Publications and source records attributed to Anton Hinneck.

5 recordsLinked to original sources

arXiv2026

Location-Invariant Assessment of Flexibility Potential under Distribution System Reconfiguration

The growing integration of renewable and decentralized generation increases the need for flexibility in distribution systems. This flexibility, typically represented in a PQ capability curve, is constrained by network limits and topology. Distribution system reconfiguration (DSR) introduces additional degrees of freedom through switching actions. This paper proposes an AC-constrained methodology to assess flexibility under network reconfiguration, explicitly considering radial operation. The impact of topology changes on PQ capability curves, which serve as a measure of flexibility potential, is analyzed. To that end, a novel measure called location-invariant flexibility potential (LI-FP) is introduced. Results show that reconfiguration can significantly influence and improve operational flexibility. The approach presented enables transparency for system operators, facilitating improved coordination of flexibility providers.

eess.SY↗

arXiv2025

On Loss-Minimal Radial Topologies in MV Systems

Distribution system reconfiguration (DSR) means optimizing the topology of a distribution grid using switching actions. Switching actions are a degrees of freedom available to distribution system operators, e.g. to manage planned and unplanned outages. DSR is a NP-hard combinatorial problem. Finding good or even optimal solutions is computationally expensive. While transmission and high-voltage grids are generally operated in a meshed state, MV distribution systems are commonly operated as radial networks even though meshed operation would be supported. This improves resilience because faults can be isolated more easily keeping the rest of the system operational and minimizing impact on customers. We propose an AC DSR formulation and benchmark it against a common formulation from the literature. Our results indicate that additional acyclicity constraints can significantly improve solver performance.

eess.SY↗

arXiv2025

Optimal Transmission Switching: Improving Solver Performance Using Heuristics

The optimal transmission switching problem (OTSP) is an established problem of changing a power grid's topology to obtain an improved operation by controlling the switching status of transmission lines. This problem was proven to be NP-hard. Proposed solution techniques based on mixed-integer formulations can guarantee globally optimal solutions but are potentially intractable in realistic power grids. Heuristics methods cannot guarantee global optimality but can provide tractable solution approaches. This paper proposes solving the OTSP using exact formulations alongside parallel heuristics that generate good candidate solutions to speed up conventional branch-and-bound algorithms. The innovative aspect of this work is a new asynchronous parallel algorithmic architecture. A solver instance solving the full OTSP formulation is run in parallel to another process that asynchronously generates solutions to be injected into the full OTSP solution procedure during run time. Our method is tested on 14 instances of the pglib-opf library: The largest problem consisting of 13659 buses and 20467 branches. Our results show a good performance for large problem instances, with consistent improvements over off-the-shelf solver performance. We find that the method scales well with an increase in parallel processors.

eess.SY↗

arXiv2021

Electricity and Reserve Pricing in Chance-Constrained Electricity Markets with Asymmetric Balancing Reserve Policies

Recently, chance-constrained stochastic electricity market designs have been proposed to address the shortcomings of scenario-based stochastic market designs. In particular, the use of chance-constrained market-clearing avoids trading off in-expectation and per-scenario characteristics and yields unique energy and reserves prices. However, current formulations rely on symmetric control policies based on the aggregated system imbalance, which restricts balancing reserve providers in their energy and reserve commitments. This paper extends existing chance-constrained market-clearing formulations by leveraging node-to-node and asymmetric balancing reserve policies and deriving the resulting energy and reserve prices. The proposed node-to-node policy allows for relating the remuneration of balancing reserve providers and payment of uncertain resources using a marginal cost-based approach. Further, we introduce asymmetric balancing reserve policies into the chance-constrained electricity market design and show how this additional degree of freedom affects market outcomes.

math.OC↗

arXiv2020

Segmentation and Defect Classification of the Power Line Insulators: A Deep Learning-based Approach

Power transmission networks physically connect the power generators to the electric consumers. Such systems extend over hundreds of kilometers. There are many components in the transmission infrastructure that require a proper inspection to guarantee flawless performance and reliable delivery, which, if done manually, can be very costly and time consuming. One essential component is the insulator. Its failure can cause an interruption of the entire transmission line or a widespread power failure. Automated fault detection could significantly decrease inspection time and related costs. Recently, several works have been proposed based on convolutional neural networks, which address the issue mentioned above. However, existing studies focus on a specific type of insulator faults. Thus, in this study, we introduce a two-stage model that segments insulators from their background to then classify their states based on four different categories, namely: healthy, broken, burned/corroded and missing cap. The test results show that the proposed approach can realize the effective segmentation of insulators and achieve high accuracy in detecting several types of faults.

cs.CV↗