A study conducted by Researcher Aydın Başkaya, who serves as Deputy Director of Energy Technologies at the TÜBİTAK Marmara Research Center (MAM), and Gazi University Faculty Member Prof. Dr. Bünyamin Tamyürek, presenting an artificial intelligence-based approach to hybrid energy storage systems, has been published.

The research conducted in collaboration between TÜBİTAK MAM and Gazi University, titled "Self-Tuning Current Control via ANN for Enhanced Harmonic Mitigation in Hybrid PV–Battery Storage Systems Utilizing the 3L-HANPC Inverter," has been published in the journal Electronics and made available to the scientific community. The study developed an artificial neural network (ANN)-based, self-tuning current control method for 1500 V DC Three-Level Hybrid Active Neutral Point Coupled (3L-HANPC) inverters used in Hybrid Photovoltaic–Battery Energy Storage Systems (PV-BSS). The artificial neural network, designed with a Multi-Layer Perceptron (MLP) architecture, was optimized by jointly evaluating the Total Harmonic Distortion (THD) and training efficiency criteria.Simulation results showed that the proposed controller provided lower harmonic distortion and faster dynamic response compared to classical PI methods. It was also determined that the system exhibited stable and reliable performance under both trained and previously unencountered operating conditions. Published in the special issue of Electronics magazine titled "Energy Saving Management Systems: Challenges and Applications," the study highlights the contribution of artificial intelligence-based control methods to energy efficiency and system reliability in high-power hybrid PV-battery systems. The research serves as an important example of TÜBİTAK MAM's scientific work in the field of energy technologies and university-research center collaborations.

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