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ABSTRACT: This paper proposes a method of adaptive control of three-phase inverters for autonomous distributed generation systems (DGS). The proposed voltage regulator includes two control terms: an adaptive compensation term and a stabilization term. The adaptive compensation control term is constructed to avoid the direct calculation of the time derivatives of the state variables. Meanwhile, the stabilization control term is designed to asymptotically stabilize the dynamics of system errors. In addition, an optimal fourth order charge current observer is proposed to reduce the number of current sensors and improve the reliability and profitability of the system. The stability of the proposed voltage regulator and the proposed load current observer are fully tested using the Lyapunov theory. The proposed control system can establish a good voltage regulation, such as a fast dynamics response, a small steady state error and a low total harmonic distortion in case of sudden load variation, unbalanced load and non-linear load. Finally, the validity of the proposed control strategy is verified through simulations and experiments on a DGS test bench prototype with a TMS320F28335 DSP. For a comparative study, the feedback linearization control scheme for multiple inputs and outputs is implemented, and its results are presented in this document.
Keywords:
Index Terms-Adaptive control, distributed generation (DG) system (DGS), load current observer, stand-alone, three-phase inverter, voltage control.
Cite Article:
"Adaptive Voltage Control Strategy of Three-Phase Inverter for Standalone Distributed Generation System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.4, Issue 2, page no.54 - 57, February-2019, Available :http://www.ijrti.org/papers/IJRTI1902011.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator