Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
ANN-Based Peak Load Prediction and MMC-Solar PV with ANFIS MPPT

ANN-Based Peak Load Prediction and MMC-Solar PV with ANFIS MPPT

Alemu, Wondiferaw Asmare
Anley, Alebachew Kassie
Tadege, Addisu Menigesha

Paperback

Technology & Engineering

ISBN10: 6209206743
ISBN13: 9786209206740
Publisher: LAP Lambert Academic Publishing
Published: Mar 25 2026
Pages: 148
Weight: 0.46
Height: 0.34 Width: 6.00 Depth: 9.00
Language: English
This book presents an integrated approach that combines peak load prediction and advanced control of a grid-connected solar PV system to support distribution substations. Peak load forecasting for the Bahir Dar 15 kV substation is carried out using an Artificial Neural Network trained with newly registered domestic customers, their sanction loads, and corresponding substation peak load data. The model predicts that the substation will face overloading within 22 months. Because the peak demand occurs during daytime and the city has strong solar resources, a solar PV system is proposed as a peak load shaving solution and as an ancillary support source.A 100 kW PV system is designed to replace the diesel generators at the EEU data center. An ANFIS-based boost converter regulates the DC-link voltage under changing environmental conditions. A five-level Modular Multilevel Converter interfaces the PV system with the grid, using voltage-oriented control, circulating current suppression, and capacitor voltage balancing. The designed system achieves low harmonic distortion, with injected current THD reduced to 1.12%, well below the 5% international standard.

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