Artificial Neural Network Controlled Electric Spring for SEIG based Isolated Microgrid

Islanded microgrid network is sensitive to voltage and frequency fluctuations which becomes more vulnerable in the presence of external disturbance and the intermittent nature of Renewable Energy Sources (RESs). The “Electric Spring” (ES) is one of the most effective and efficient solutions for enhancing operational flexibility and RESs integration. A Self‐Excited Induction Generator (SEIG) based Micro hydro system with ES, non‐critical and critical loads is considered. Both non‐critical and critical loads are connected in 2:1 ratio in parallel with SEIG. The concept of voltage‐sensitive and non‐sensitive loads and the “power demand following the supply” idea have been incorporated for pointing up the contribution of ES. The non‐critical load coupled with a three‐phase inverter acts like an ES and can be operated as a Smart Load (SL). SL can compensate the voltage deviation between demand‐supply side, therefore mitigating the voltage fluctuations. The effectiveness of ES in terms of voltage regulation at the point of standard coupling has been achieved which improved the overall voltage profile of the hybrid microgrid system which can be observed from various test cases. A hardware in loop microgrid experimental platform is established and its results highlight the excellent performance of the proposed method.

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“…The voltage profile can be enhanced by careful management of these parameters [27,28]. The system presented in Fig.…”

Section: Smart Load In Microgrid Systemmentioning

confidence: 99%