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Adaptive Control Optimization for Solar Energy Storage Systems Using Fuzzy Logic, Genetic Algorithms, and State of Charge Estimation Andicho Haryus Wirasapta; Tiara Deta Pamungkas
JMECS (Journal of Measurements, Electronics, Communications, and Systems) In Press Papers
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v12i2.10090

Abstract

The intermittent nature of solar energy results in a generation versus load curve, thus becoming a significant challenge for reliable utilization. The use of a battery energy storage system, on the other hand, plays a vital role in uninterrupted power supply; however, it requires advanced control techniques for smooth functionality. The use of conventional techniques, such as a classical Maximum Power Point Tracking scheme based on Constant Current/Constant Voltage, becomes inefficient for dealing with nonlinear dynamics associated with system functionality, thereby reducing battery life. The proposed composite approach incorporates fuzzy logic decision-making, Genetic Algorithm optimization, and adaptive Extended Kalman Filter estimation for quantifying real-time battery state. A comprehensive PV-BESS model has been developed in the environment of a MATLAB/Simulink toolbox, using actual load as well as actual solar irradiance. The results based on the proposed approach indicate improvement in energy efficiency of 20% along with 5% accuracy in battery state estimation while extending battery life to 18-25% compared to conventional battery energy storage systems. The proposed approach provides a robust, optimizing, as well as a viable solution set for the PV-BESS system, thereby paving the way for future micro-grid development.
Simulasi Keputusan Handover Cerdas berbasis Support Vector Machine pada Jaringan Nirkabel Menggunakan Matlab Andicho Haryus Wirasapta; Tiara Deta Pamungkas
Jurnal Litek : Jurnal Listrik Telekomunikasi Elektronika Vol. 23 No. 1 (2026): Jurnal Litek, Maret 2026
Publisher : Jurusan Teknik Elektro Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/litek.v23i1.104

Abstract

Manajemen mobilitas merupakan tantangan utama dalam jaringan seluler nirkabel akibat dinamika kanal dan mobilitas pengguna, di mana skema handover konvensional berbasis ambang RSS atau SINR sering memicu handover tidak perlu dan efek ping-pong. Penelitian ini mengusulkan mekanisme keputusan handover cerdas berbasis kecerdasan buatan menggunakan Support Vector Machine (SVM) dengan integrasi fitur RSS, SINR, kecepatan pengguna, dan beban base station. Evaluasi melalui simulasi MATLAB pada kondisi kanal dan mobilitas yang realistis menunjukkan bahwa pendekatan yang diusulkan mampu mengurangi jumlah handover dan kejadian ping-pong lebih dari 50%, menurunkan probabilitas packet loss sekitar 6%, serta meningkatkan effective throughput sekitar 6% dibandingkan dengan skema berbasis threshold konvensional. Hasil ini menegaskan kontribusi ilmiah utama penelitian dalam merumuskan dan mengevaluasi mekanisme keputusan handover berbasis SVM yang mengintegrasikan parameter kanal dan mobilitas secara simultan, serta secara kuantitatif menunjukkan peningkatan kinerja jaringan dibandingkan dengan skema handover berbasis threshold konvensional.