Output Power Allocation Control Strategy Considering Strong Nonlinearity of HCSY-MG Grid-Connected System

The half-bridge converter series Y-connection microgrid (HCSY-MG), as a novel type of series-connected microgrid, has received limited attention regarding output power allocation and control. Moreover, existing power allocation and control strategies for microgrids are not directly applicable to HCSY-MG grid-connected system. To achieve the output power distribution and control of the HCSY-MG grid-connected system across various generation modules (GMs), while considering the system’s strong nonlinearity constraints, a control strategy for output power distribution based on the Lagrange-proximal policy optimization (Lagrange-PPO) algorithm was proposed. First, the output power mathematical model of the HCSY-MG grid-connected system was established under the carrier disposition sinusoidal pulse width modulation (CD-SPWM) method. Based on the output power range of each GM and microsource output power, the corresponding relationship between each GM and the carrier layers was derived. Then, considering the strong nonlinearity in the output power constraints of each GM under the CD-SPWM strategy, the output power control problem is reformulated as a constrained Markov decision process (MDP) to reduce algorithmic complexity. To address this constrained MDP, a Lagrange-proximal policy optimization algorithm is proposed. Finally, the feasibility and effectiveness of the proposed strategy, along with its superiority over conventional methods, are validated through both simulations and experimental comparisons.

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Publication Details

Journal
IEEE Journal of Emerging and Selected Topics in Power Electronics
Published
2025-08-04
DOI
https://doi.org/10.1109/jestpe.2025.3595623
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00

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article

Output Power Allocation Control Strategy Considering Strong Nonlinearity of HCSY-MG Grid-Connected System

Weiman Yang, Sheng Xue, Xinggui Wang, Hailiang Wang et al.
IEEE Journal of Emerging and Selected Topics in Power Electronics
Power Systems and Renewable Energy
article

Output Power Allocation Control Strategy Considering Strong Nonlinearity of HCSY-MG Grid-Connected System

Weiman Yang, Sheng Xue, Xinggui Wang, Hailiang Wang, Jinjian Li
article en

Abstract

The half-bridge converter series Y-connection microgrid (HCSY-MG), as a novel type of series-connected microgrid, has received limited attention regarding output power allocation and control. Moreover, existing power allocation and control strategies for microgrids are not directly applicable to HCSY-MG grid-connected system. To achieve the output power distribution and control of the HCSY-MG grid-connected system across various generation modules (GMs), while considering the system’s strong nonlinearity constraints, a control strategy for output power distribution based on the Lagrange-proximal policy optimization (Lagrange-PPO) algorithm was proposed. First, the output power mathematical model of the HCSY-MG grid-connected system was established under the carrier disposition sinusoidal pulse width modulation (CD-SPWM) method. Based on the output power range of each GM and microsource output power, the corresponding relationship between each GM and the carrier layers was derived. Then, considering the strong nonlinearity in the output power constraints of each GM under the CD-SPWM strategy, the output power control problem is reformulated as a constrained Markov decision process (MDP) to reduce algorithmic complexity. To address this constrained MDP, a Lagrange-proximal policy optimization algorithm is proposed. Finally, the feasibility and effectiveness of the proposed strategy, along with its superiority over conventional methods, are validated through both simulations and experimental comparisons.

IEEE Journal of Emerging and Selected Topics in Power ElectronicsVol. 13(6)
Lanzhou University of Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 80%
Power Systems and Renewable Energy
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