Dual-tree wavelet transform based advanced adaptive control for seamless transition in PV-battery hybrid microgrid system

This study introduces an advanced adaptive control (AAC) technique featuring a synchronizing controller capable of identifying different operational modes—grid-following and grid-forming—while ensuring enhanced energy management in hybrid microgrid systems (HMGs) through seamless transition operations. In grid-following mode, a dual-tree wavelet transform (DTWT)-based current control strategy is implemented to facilitate parallel inverter operation and significantly enhance power quality (PQ) by isolating fundamental active currents from non-linear loads. In grid-forming mode, the synchronizing controller enables a smooth transition from current control to voltage control, thereby ensuring stable and coordinated inverter functionality. To address power shortages and fluctuations in photovoltaic (PV) generation, an innovative battery control strategy is employed, utilizing the PV maximum power point tracking (MPPT) voltage output, and governed by the proposed AAC scheme. The effectiveness of the proposed approach is validated through both simulation and real-time testing using the Typhoon HIL-402 platform under various scenarios, including inverter failure, sudden generation variations, and operational mode transitions. In software-based validation, the proposed DTWT-AAC achieves significant PQ enhancement, with total harmonic distortion (THD) reductions resulting in PQ improvements of 99.54% during inverter-1 failure, 99.82% under variable generation, and 99.59% during grid-following to grid-forming transition. Moreover, the average synchronization times under these respective conditions are notably low—0.03 s, 0.032 s, and 0.02 s. In real-time validation, when compared to the conventional discrete wavelet transform-based adaptive control (DWT-AC), the proposed DTWT-AAC delivers marked improvements: THD is reduced from 35.2% (uncontrolled) and 5.3% (DWT-AC) to 1.9%, while synchronization response time is improved from 0.9 s (DWT-AC) to 0.2 s (DTWT-AAC). These findings confirm the proposed method’s superiority in terms of PQ, dynamic stability, and robustness, making it highly suitable for real-time applications and scalable future grid-integrated microgrid deployments.