Super capacitor-enhanced neural control (SENCO) for power quality optimization in wind turbine-integrated microgrids

Rutuja S. Hiware, P. M. Daigavane

Abstract


Wind-integrated microgrids face significant challenges in power flow management, voltage control, and stability due to fluctuating nature of wind energy. To address these issues, the proposed Super Capacitor-Enhanced Neural Control (SENCO) system integrates supercapacitors directly into Unified Power Quality Conditioners (UPQCs). This innovative approach compensates for power variations caused by wind intermittencies and grid failures. SENCO system leverages an Artificial Neural Network (ANN)-based Pulse Width Modulation (PWM) control approach to boost power management efficiency and enhance network stability. By incorporating an energy storage component and a dynamic control mechanism, the system adapts to varying conditions, ensuring stable operation and consistent energy quality. Furthermore, optimization techniques are applied to improve system efficiency and responsiveness, offering a robust solution for managing energy generation and distribution variations. The proposed SENCO model demonstrates significant advancements by maintaining grid voltage stability at 400 V with minimal fluctuations and balancing load voltage at 200 V. It effectively mitigates disturbances with compensation currents reaching ±500 A. Moreover, the grid current Total Harmonic Distortion (THD) is significantly reduced from 28.46% without UPQC to much lower levels, while the load current and voltage THDs are maintained at 4.82% and 4.77%, respectively. These outcomes underscore the model’s ability to substantially enhance power quality and ensure reliable energy delivery in wind-integrated microgrids. By addressing critical challenges associated with wind energy intermittency and grid reliability, SENCO provides a comprehensive and efficient solution for advancing renewable energy integration into microgrids.

 

Received: 27 March 2025

Accepted: 25 July 2025

Published: 31 August 2025


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References


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DOI: https://dx.doi.org/10.21622/resd.2025.11.2.1279

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Copyright (c) 2025 Rutuja S Hiware, P.M. Daigavane

Renewable Energy and Sustainable Development

E-ISSN: 2356-8569

P-ISSN: 2356-8518

 

Published by:

Academy Publishing Center (APC)

Arab Academy for Science, Technology and Maritime Transport (AASTMT)

Alexandria, Egypt

resd@aast.edu