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All Journal JMECS (Journal of Measurements, Electronics, Communications, and Systems) Jurnal Litek : Jurnal Listrik Telekomunikasi Elektronika
Tiara Deta Pamungkas
Poltekkes Kemenkes Jambi
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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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.v13i1.10090

Abstract

The intermittent nature of solar energy results in a generation–load mismatch, posing a significant challenge to reliable power utilization. Battery Energy Storage Systems (BESS) play a crucial role in mitigating this issue. However, effective operation requires advanced control strategies. Conventional techniques, such as classical Maximum Power Point Tracking based on Constant Current/Constant Voltage, often struggle to cope with the nonlinear dynamics of PV–BESS systems, leading to reduced efficiency and accelerated battery degradation. This paper proposes a hybrid adaptive control strategy integrating fuzzy logic decision-making, Genetic Algorithm (GA) optimization, and Extended Kalman Filter (EKF)-based State of Charge (SoC) estimation. A comprehensive PV–BESS model is developed in the MATLAB/Simulink environment using real solar irradiance and realistic load profiles. Simulation results demonstrate an absolute improvement in energy efficiency of approximately 14.3%, a SoC estimation accuracy within ±5%, and an extension of battery lifetime by 18–25% compared to conventional control methods. The proposed approach offers a robust and computationally efficient solution for PV–BESS operation, making it suitable for future microgrid and renewable energy storage applications.
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.
Co-Authors Wirasapta , Andicho Haryus