Original scientific paper
https://doi.org/10.1080/00051144.2023.2288489
An implementation of inertia control strategy for grid-connected solar system using moth-flame optimization algorithm
N. Nandakumar
; Department of EEE, Noorul Islam Centre for Higher Education, Kumaracoil, India
*
V. A. Tibbie Pon Symon
; Department of EEE, Noorul Islam Centre for Higher Education, Kumaracoil, India
* Corresponding author.
Abstract
As the solar power system power system grows rapidly, inertia control strategy (ICS) becomes
crucial to enable stable grid integration. However, the existing ICS lacks of dynamic weather
analysis with maximum power point tracking (MPPT) and fault-ride through (FRT) capabilities
such as low voltage ride-through (LVRT) and high voltage ride-through (HVRT). In this work, an
inertia weighting strategy and the Cauchy mutation operator are introduced to improve the
moth-flame optimization (MFO) algorithm to support vector machine prediction of photovoltaic
power generation. In this paper, the proposed adaptive VICS with variable moment of inertia
(J) and damping factor (DP) demonstrates its effectiveness with faster frequency recovery, less
overshooting and continuous stable operation under grid fault and dynamic weather. The MFO
algorithm is used to implement inertia control strategies for grid-connected solar systems. Accurate simulation results confirm the inertia control of the emulsion and the control of the solar
system. The results of the simulation show a significant improvement in frequency with the
designed MFO and compared to Horse Herd Optimization (HHO). The proposed method contributes to improve photovoltaic energy prediction, reduces the impact of photovoltaic power
penetration into the grid and maintains the system reliability.
Keywords
Inertia control strategy; maximum power point tracking; moth-flame optimization algorithm; solar power system; grid-connected PV
Hrčak ID:
322962
URI
Publication date:
12.12.2023.
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