Implementasi Energy Management System untuk Optimasi Distribusi Beban pada PLTS Off-Grid Berbasis IoT
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Abstract
Solar energy is one of the most promising renewable energy sources due
to its unlimited availability, environmental friendliness, and applicability in both
residential and industrial sectors. However, the performance of off-grid
photovoltaic (PV) systems is highly dependent on battery capacity and fluctuating
solar irradiation, making effective energy management essential. This study aims
to implement an Energy Management System (EMS) based on the Finite State
Machine (FSM) method to optimize load distribution in an IoT-based off-grid
photovoltaic system. The proposed EMS controls battery charging, surplus energy
utilization, battery discharging, and low battery protection through four operating
states. The system employs an ESP32 microcontroller as the main controller,
INA219 sensors for voltage and current monitoring, a BH1750 sensor for light
intensity measurement, and the MQTT protocol integrated with Node-RED for
real-time monitoring and data logging. System performance was evaluated
through FSM validation, comparative testing between EMS and non-EMS
operation, and communication performance testing. The experimental results
demonstrate that the proposed EMS successfully performs automatic energy
management according to predefined operating conditions. During the charging
process, the EMS achieved an average charging efficiency of 71.55%, allowing
the battery to reach its operating voltage faster than the non-EMS system. During
discharging, the EMS effectively prioritized load operation based on the available
battery energy while preventing over-discharge through automatic load
disconnection. Furthermore, the MQTT-based monitoring system successfully
transmitted real-time operational data to the Node-RED dashboard with a stable
communication delay of approximately 2 milisecond over testing distances
ranging from 1 to 10 meters. Overall, the proposed EMS based on the FSM
method improves energy utilization efficiency, enhances battery protection, and
provides reliable real-time monitoring for off-grid photovoltaic systems.
Description
Energi surya merupakan salah satu sumber energi terbarukan yang
berpotensi besar untuk dikembangkan melalui sistem Pembangkit Listrik Tenaga
Surya (PLTS) off-grid. Namun, keterbatasan kapasitas baterai dan fluktuasi
intensitas cahaya matahari menyebabkan pemanfaatan energi belum optimal. Oleh
karena itu, penelitian ini mengimplementasikan Energy Management System
(EMS) menggunakan metode Finite State Machine (FSM) untuk mengatur
distribusi energi dan pengoperasian beban secara otomatis berdasarkan kondisi
sistem.
Sistem dirancang menggunakan mikrokontroler ESP32 yang dipadukan
dengan sensor INA219 dan BH1750 untuk memantau parameter kelistrikan dan
intensitas cahaya. Selain itu, sistem diintegrasikan dengan protokol Message
Queuing Telemetry Transport (MQTT) menggunakan HiveMQ Broker dan Node
RED sehingga proses monitoring serta data logging dapat dilakukan secara real
time. Metode FSM diterapkan melalui empat kondisi operasi, yaitu charging,
surplus energy, discharging, dan low battery protection, untuk mengoptimalkan
pengisian baterai, pemanfaatan energi panel surya, serta perlindungan baterai dari
kondisi over-discharge.
Hasil penelitian menunjukkan bahwa implementasi EMS berbasis FSM berhasil
mengatur distribusi energi sesuai kondisi baterai dan intensitas cahaya matahari.
Dibandingkan sistem tanpa EMS, sistem yang menggunakan EMS mampu
meningkatkan efektivitas pengelolaan energi dengan rata-rata efisiensi charging
sebesar 71,55%, mempercepat pencapaian tegangan kerja baterai, serta
mengoptimalkan pengoperasian beban berdasarkan prioritas energi. Selain itu,
integrasi sistem dengan protokol MQTT berhasil mendukung monitoring dan
penyimpanan data secara real-time dengan komunikasi yang stabil, ditunjukkan
oleh rata-rata delay pengiriman data sebesar 2 ms. Secara keseluruhan, penelitian
ini membuktikan bahwa penerapan EMS berbasis FSM mampu meningkatkan
efisiensi distribusi energi, menjaga keandalan operasi baterai, serta mendukung
implementasi sistem PLTS off-grid berbasis Internet of Things (IoT).