LCL filter design of STATCOM using genetic algorithm scheme for SCIG based microgrid operation
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Taylor and Francis
Abstract
In a microgrid static Compensator (STATCOM) is the most prominent inverter circuit for stabilizing the bidirectional power flow requirements of the system. This inverter circuit is the primary source of harmonics when the supply current feeds from the microgrid to the main grid. Improved control strategy and proper filter design may give solution to these issues and so, there is a huge scope of research in the field of the converter control techniques and filter designing for such microgrid based power system. The key objectives of this paper are (i) to develop an adequate current control scheme for adjusting real and reactive power fluctuations produced by load time to time, and (ii) to reduce the harmonic level of output characteristics in terms of real and reactive power flow and current frequency. For this, an approach is presented to estimate the filter design parameters for current controlled STATCOM connected to squirrel cage induction generator (SCIG) based microgrid. A nature-inspired optimization namely, genetic algorithm (GA), is implemented to estimate the most suitable parameters for the LCL filter. Results obtained through GA are validated with a conventional mathematical method in terms of real and reactive power flow through microgrid along with harmonic-based studies.
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DATA AVAILABILITY STATEMENT : The data sources employed for analysis are presented in the text.
Keywords
Static compensator (STATCOM), Microgrid, LCL filter, GA optimization, Power system management, Squirrel cage induction generator (SCIG), Genetic algorithm (GA), Latching current limiter (LCL)
Sustainable Development Goals
SDG-07: Affordable and clean energy
Citation
Nitin Kumar Saxena, Anmol Gupta, Mohd Faisal Jalil, Varun Gupta & R. C. Bansal (20 Nov 2023): LCL Filter Design of STATCOM using Genetic Algorithm Scheme for SCIG Based Microgrid Operation, Electric Power Components and Systems, DOI: 10.1080/15325008.2023.2278628.