Direct Adaptive Control of Grid-Connected Power Converters via Output-Feedback Data-Enabled Policy Optimization

Fuente: arXiv
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Main Authors: Zhao, Feiran, Leng, Ruohan, Huang, Linbin, Xin, Huanhai, You, Keyou, Dörfler, Florian
Format: Preprint
Published: 2024
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author Zhao, Feiran
Leng, Ruohan
Huang, Linbin
Xin, Huanhai
You, Keyou
Dörfler, Florian
author_facet Zhao, Feiran
Leng, Ruohan
Huang, Linbin
Xin, Huanhai
You, Keyou
Dörfler, Florian
contents Power electronic converters are becoming the main components of modern power systems due to the increasing integration of renewable energy sources. However, power converters may become unstable when interacting with the complex and time-varying power grid. In this paper, we propose an adaptive data-driven control method to stabilize power converters by using only online input-output data. Our contributions are threefold. First, we reformulate the output-feedback control problem as a state-feedback linear quadratic regulator (LQR) problem with a controllable non-minimal state, which can be constructed from past input-output signals. Second, we propose a data-enabled policy optimization (DeePO) method for this non-minimal realization to achieve efficient output-feedback adaptive control. Third, we use high-fidelity simulations to verify that the output-feedback DeePO can effectively stabilize grid-connected power converters and quickly adapt to the changes in the power grid.
format Preprint
id arxiv_https___arxiv_org_abs_2411_03909
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Direct Adaptive Control of Grid-Connected Power Converters via Output-Feedback Data-Enabled Policy Optimization
Zhao, Feiran
Leng, Ruohan
Huang, Linbin
Xin, Huanhai
You, Keyou
Dörfler, Florian
Systems and Control
Optimization and Control
Power electronic converters are becoming the main components of modern power systems due to the increasing integration of renewable energy sources. However, power converters may become unstable when interacting with the complex and time-varying power grid. In this paper, we propose an adaptive data-driven control method to stabilize power converters by using only online input-output data. Our contributions are threefold. First, we reformulate the output-feedback control problem as a state-feedback linear quadratic regulator (LQR) problem with a controllable non-minimal state, which can be constructed from past input-output signals. Second, we propose a data-enabled policy optimization (DeePO) method for this non-minimal realization to achieve efficient output-feedback adaptive control. Third, we use high-fidelity simulations to verify that the output-feedback DeePO can effectively stabilize grid-connected power converters and quickly adapt to the changes in the power grid.
title Direct Adaptive Control of Grid-Connected Power Converters via Output-Feedback Data-Enabled Policy Optimization
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2411.03909