@Article{ee.2024.057380,
AUTHOR = {Chao Zhou, Narisu Wang, Fuyin Ni, Wenchao Zhang},
TITLE = {Grid-Connected/Islanded Switching Control Strategy for Photovoltaic Storage Hybrid Inverters Based on Modified Chimpanzee Optimization Algorithm},
JOURNAL = {Energy Engineering},
VOLUME = {122},
YEAR = {2025},
NUMBER = {1},
PAGES = {265--284},
URL = {http://www.techscience.com/energy/v122n1/59128},
ISSN = {1546-0118},
ABSTRACT = {Uneven power distribution, transient voltage, and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes. In response to these issues, this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm. The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control. Then, it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy. Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage. Additionally, two novel operators, learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm. These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters. A Simulink model was constructed for simulation analysis, which validated the optimized control strategy’s ability to evenly distribute power under load transients. This strategy effectively mitigated transient voltage and current surges during mode transitions. Consequently, seamless and efficient switching between grid-connected and island modes was achieved for the photovoltaic storage hybrid inverter. The enhanced energy utilization efficiency, in turn, offers robust technical support for grid stability.},
DOI = {10.32604/ee.2024.057380}
}