A General Framework for the Power Flow Solution in Radial and Meshed AC/DC Microgrids

Silva, Elson N. M.; Rodrigues, A.B.; Silva, Maria da Guia da

doi:10.1109/tsg.2023.3271205

IEEE Trans. Smart Grid

2024

DOI: 10.1109/tsg.2023.3271205

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A General Framework for the Power Flow Solution in Radial and Meshed AC/DC Microgrids

Elson N. M. Silva¹,

A.B. Rodrigues²,

Maria da Guia da Silva³

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Multi-Objective Optimal Scheduling for Microgrids—Improved Goose Algorithm

Sun,

Wang,

Gao

et al. 2024

Energies

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Against the background of the dual challenges of global energy demand growth and environmental protection, this paper focuses on the study of microgrid optimization and scheduling technology and constructs a smart microgrid system integrating energy production, storage, conversion, and distribution. By integrating high-precision load forecasting, dynamic power allocation algorithms, and intelligent control technologies, a microgrid scheduling model is proposed. This model simultaneously considers environmental protection and economic efficiency, aiming to achieve the optimal allocation of energy resources and maintain a dynamic balance between supply and demand. The goose optimization algorithm (GO) is innovatively introduced and improved, enhancing the algorithm’s ability to use global search and local fine search in complex optimization problems by simulating the social aggregation of the goose flock, the adaptive monitoring mechanism, and the improved algorithm, which effectively avoids the problem of the local optimal solution. Meanwhile, the combination of super-Latin stereo sampling and the K-means clustering algorithm improves the data processing efficiency and model accuracy. The results demonstrate that the proposed model and algorithm effectively reduce the operating costs of microgrids and mitigate environmental pollution. Using the improved goose algorithm (IGO), the combined operating and environmental costs are reduced by 16.15%, confirming the model’s effectiveness and superiority.

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Multi-Objective Optimal Scheduling for Microgrids—Improved Goose Algorithm

Sun,

Wang,

Gao

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

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A General Framework for the Power Flow Solution in Radial and Meshed AC/DC Microgrids

Cited by 1 publication

References 23 publications

Multi-Objective Optimal Scheduling for Microgrids—Improved Goose Algorithm

Multi-Objective Optimal Scheduling for Microgrids—Improved Goose Algorithm

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