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Main Authors: Zhan, Sen, Jin, Lingkang, Zhang, Haoyang, Paterakis, Nikolaos G.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.16408
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author Zhan, Sen
Jin, Lingkang
Zhang, Haoyang
Paterakis, Nikolaos G.
author_facet Zhan, Sen
Jin, Lingkang
Zhang, Haoyang
Paterakis, Nikolaos G.
contents The secure operation of power distribution systems is challenged by the growing integration of distributed energy resources. Leveraging the flexibility of battery storage offers a cost-effective alternative to measures like generation curtailment, which results in energy losses. However, developing an effective operational model for battery storage is hindered by inaccurate grid models, unavailability of load data, nonlinear relationship between power injections and network states, intertemporal constraints, and complex electrochemical and thermal dynamics. To address these challenges, this paper proposes a data-driven operational control scheme for battery storage in distribution systems. Linear and convex quadratic operational constraints are constructed based on real-time distribution system and battery storage measurements. Lyapunov optimization decouples multi-period battery operation, enabling a real-time, forecast-free control strategy with low computational complexity. Numerical studies using nonlinear distribution system and battery storage simulators validate the effectiveness of the approach in ensuring secure distribution system operation and satisfaction of voltage and thermal constraints of battery storage.
format Preprint
id arxiv_https___arxiv_org_abs_2510_16408
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Real-time Measurement-based Optimization for Distribution System Operation Considering Battery Voltage and Thermal Constraints
Zhan, Sen
Jin, Lingkang
Zhang, Haoyang
Paterakis, Nikolaos G.
Systems and Control
The secure operation of power distribution systems is challenged by the growing integration of distributed energy resources. Leveraging the flexibility of battery storage offers a cost-effective alternative to measures like generation curtailment, which results in energy losses. However, developing an effective operational model for battery storage is hindered by inaccurate grid models, unavailability of load data, nonlinear relationship between power injections and network states, intertemporal constraints, and complex electrochemical and thermal dynamics. To address these challenges, this paper proposes a data-driven operational control scheme for battery storage in distribution systems. Linear and convex quadratic operational constraints are constructed based on real-time distribution system and battery storage measurements. Lyapunov optimization decouples multi-period battery operation, enabling a real-time, forecast-free control strategy with low computational complexity. Numerical studies using nonlinear distribution system and battery storage simulators validate the effectiveness of the approach in ensuring secure distribution system operation and satisfaction of voltage and thermal constraints of battery storage.
title Real-time Measurement-based Optimization for Distribution System Operation Considering Battery Voltage and Thermal Constraints
topic Systems and Control
url https://arxiv.org/abs/2510.16408