Smart Charging For Storage Batteries In A Smart Grid System

Abstract

Smart charging merupakan solusi adaptif untuk mengatasi tantangan impor energi dalam sistem smart grid. Sistem ini dirancang dengan fitur IoT untuk mempermudah pengawasan dan pengendalian impor daya secara real-time. Sistem juga dilengkapi dengan kontrol Fuzzy Lookup yang bertugas mengatur impor daya sesuai set point yang ditentukan pengguna, memastikan efisiensi dan stabilitas sistem. Komponen utama yang digunakan meliputi Huawei R4850G5, ESP32, SMPS 5V 2A, MCP2515, ANT BMS, dan baterai LiFePO4. Melalui komunikasi MQTT, set point daya diinput oleh pengguna menggunakan Node-RED. Nilai ini diolah oleh ESP32 dengan algoritma Fuzzy Lookup, yang menyesuaikan tegangan output Huawei R4850G5 berdasarkan pembacaan arus baterai. Dari eksperimen dengan 11 variasi set point, ditemukan bahwa nilai daya aktual memiliki error sebesar 0,09%, sementara error pembacaan arus adalah 0,13%. Respon sistem menunjukkan waktu rise time sekitar 3 detik, namun terjadi fenomena osilasi pada set point 190 watt akibat delay sinkronisasi antara tegangan keluaran dan arus baterai. Nilai settling time tercatat sekitar 3 detik. Sebagai perbandingan, metode counting dengan set point 250 watt menunjukkan waktu rise time 15 detik dan mencapai steady state setelah 28 detik. Hasil penelitian menunjukkan bahwa sistem ini efektif dalam memantau dan mengontrol impor daya pada smart grid. Dengan integrasi fitur IoT dan kontrol Fuzzy Lookup, sistem ini terbukti menjadi solusi yang handal dan adaptif untuk mendukung efisiensi energi pada smart grid. ================================================================================================================================== Smart charging is an adaptive solution to address the challenges of energy import in smart grid systems. This system is designed with IoT (Internet of Things) features to facilitate realtime monitoring and control of power imports. It is also equipped with a Fuzzy Lookup control mechanism, which regulates power imports according to user-defined set points, ensuring system efficiency and stability. The main components used include the Huawei R4850G5, ESP32, SMPS 5V 2A, MCP2515, ANT BMS, and LiFePO4 batteries. Through MQTT communication, the power set point is input by users via Node-RED. This value is processed by the ESP32 using a Fuzzy Lookup algorithm, which adjusts the output voltage of the Huawei R4850G5 based on battery current readings. From experiments with 11 variations of set points, the actual power value showed an error of 0.09%, while the current reading error was 0.13%. The system response exhibited a rise time of approximately 3 seconds; however, oscillations occurred at the 190-watt set point due to synchronization delays between output voltage and battery current. The settling time was recorded at around 3 seconds. For comparison, a counting method with a 250-watt set point showed a rise time of 15 seconds and reached a steady state after 28 seconds. The study's results demonstrate that this system effectively monitors and controls power imports in smart grids. With the integration of IoT features and Fuzzy Lookup control, the system has proven to be a reliable and adaptive solution for supporting energy efficiency in smart grids