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Persistent Voltage Profiling of a Wind Energy-Driven Islanded Microgrid with Novel Neuro-fuzzy Controlled Electric Spring

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Abstract

Electricity from renewable energy is certainly the most prominent alternative to deliver power to remote locations; however, its reliability is affected by the intermittency of the renewable source. A smart load technology called ‘electric spring (ES)’ can compensate for the intermittency and thereby maintain the voltage level constant for critical loads with an efficient and reliable control approach. This paper suggests wind energy-fed generation as the only and primary source for an isolated remote microgrid. The voltage level of the system remained unaltered by deploying a voltage source converter-based ES with a novel artificial neural network-based fuzzy controller. The novelty of the system is that it can operate significantly under varying load, variable torque, and varying wind speed conditions by exchanging power between critical and non-critical loads. Further simulation results ensure the credibility of the electric spring–artificial neural network-based fuzzy controller system in terms of stability and performance parameters such as settling time, rise time, and maximum overshoot. Additionally, the total harmonic distortion of the system is found to be well within the boundary of the acceptable range that proclaims its feasibility and applicability in a real-world scenario.

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Authors and Affiliations

  1. Department of Electrical Engineering, ITER, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

    Soumya Mohanty, Swagat Pati & Sanjeeb Kumar Kar

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  1. Soumya Mohanty
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  2. Swagat Pati
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  3. Sanjeeb Kumar Kar
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Correspondence to Soumya Mohanty.

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Mohanty, S., Pati, S. & Kar, S.K. Persistent Voltage Profiling of a Wind Energy-Driven Islanded Microgrid with Novel Neuro-fuzzy Controlled Electric Spring. J Control Autom Electr Syst 34, 609–623 (2023). https://doi.org/10.1007/s40313-023-00984-9

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