Comparative Evaluation of Classical And Two-Phase Interleaved Boost Stages For 1 Kw Residential Photovoltaic Grid Interconnection

Authors

  • V. Srinivas
  • K. Narasimha Rao

Keywords:

Interleaved Boost Converter, Fuzzy Logic Control, Harmonic Mitigation, Grid Code Compliance, Proportional-Resonant Control.

Abstract

 Two-stage residential solar conditioning systems isolate maximum power tracking from low-frequency utility voltage fluctuations. This paper evaluates the electro-thermal and harmonic interactions of a 1 kW, 100 V array stepping up to a 400 V intermediate link connected to a 230 V, 50 Hz utility grid. This paper compares a classical boost stage directly against a symmetrical two-phase interleaved boost converter (IBC) implementing Intelligent MPPT algorithm using Fuzzy logic control (FLC). Both circuits are formulated via switched state-space representations and verified against closed-loop controls featuring stationary-frame proportional-resonant (PR) grid current tracking. Although the peak-to-peak 100 Hz voltage ripple experienced by the intermediate 400 V capacitor is 15.9 V due to single-phase power pulsation, the high-frequency current stress on the capacitor is reduced by 42.3% (from 4.33 A to 2.50 A) by interleaving. Also, active switch conduction dissipation is reduced from 6.00 W to 3.01 W, and the input current ripple goes down from 26.67% to 7.42%. This completely satisfies the criteria of IEEE 1547-2018 under the same magnetic volume constraints, since the resultant decrease in DC-link high-frequency harmonics results in a grid current total harmonic distortion (THD) of 1.62% as opposed to 2.84% in the conventional architecture.

Downloads

Published

2026-10-05

How to Cite

Srinivas, V., & Rao, K. N. (2026). Comparative Evaluation of Classical And Two-Phase Interleaved Boost Stages For 1 Kw Residential Photovoltaic Grid Interconnection. International Journal of Artificial Intelligence and Machine Learning, 6(13s), 1369–1378. Retrieved from https://www.svedbergopen.com/index.php/ijaiml/article/view/2844