Feng Wang

Large-scale photovoltaic (PV)–hydrogen production systems are increasingly regarded as a promising solution for mitigating renewable energy curtailment and supporting the transition toward low-carbon energy systems. However, when connected to weak grids, such systems often suffer from insufficient voltage–frequency support capability and pronounced Direct current (DC) bus voltage fluctuations, which limit their operational stability and practical deployment. To address these challenges, this paper proposes a dual virtual motor coordinated control strategy for PV-based hydrogen production systems, integrating a grid-forming virtual synchronous generator (VSG) with a virtual DC motor (VDCM). By exploiting the complementary dynamic characteristics of grid-side converters and hydrogen production loads, the proposed approach enhances grid support capability while simultaneously providing inertia and damping to the hydrogen production DC bus without relying on additional physical energy storage. Dynamic response analysis is conducted to investigate the influence of virtual inertia and damping parameters on system stability. Simulation results under weak-grid conditions demonstrate that the proposed strategy effectively improves frequency and voltage support performance and significantly suppresses DC bus voltage fluctuations during load and power disturbances. The proposed control framework offers a practical and scalable solution for improving the operational robustness of PV–hydrogen production systems, contributing to the reliable integration of renewable energy and the development of green hydrogen infrastructure.

Grid-connected PV inverters (GCPI) are key components that enable photovoltaic (PV) power generation to interface with the grid. Their control performance directly influences system stability and grid connection quality. However, as PV penetration increases, conventional controllers encounter difficulties in managing nonlinear dynamics and weak-grid conditions. This paper reviews both conventional and artificial intelligence (AI)-based control methods for GCPI. It compares their performance characteristics, application scenarios, and limitations and summarizes current research progress and remaining challenges. The potential and issues of applying AI to enhance system intelligence are also highlighted. Finally, future development trends are discussed, emphasizing high efficiency, strong adaptability, and intelligent integration in GCPI technologies.

As a pivotal clean energy carrier for achieving carbon neutrality, green hydrogen technology has attracted growing global attention. This review systematically examines four mainstream water electrolysis technologies—alkaline electrolysis, proton exchange membrane electrolysis, solid oxide electrolysis, and anion exchange membrane electrolysis—analyzing their fundamental principles, material challenges, and development trends. It further classifies and compares power electronic converter topologies, including non-isolated and isolated DC–DC converters as well as AC–DC converter architectures, and summarizes advanced control strategies such as dynamic power regulation and fault-tolerant operation aimed at enhancing system efficiency and stability. A holistic “electrolyzer–power converter–control strategy” integration framework is proposed to provide tailored technological solutions for diverse application scenarios. Finally, the challenges and future prospects of green hydrogen across the energy, transportation, and industrial sectors are discussed, underscoring its potential to accelerate the global transition toward a sustainable, low-carbon energy system.