Power Factor Correction on 500W Inverter Microcontroller-Base Using Particle Swarm Optimization Method - Dimas Pristovani Riananda; Ryan yudha Adhitya; Zindhu Maulana Ahmad Putra; Aulia Rahma Annisa; Arya Adiansyah Saputra (Telkom University, 2025)
This research explores the design and evaluation of an inverter system incorporating the Particle Swarm Optimization (PSO) method to enhance power factor efficiency. The study investigates the inverter’s performance across resistive loads (40W and 100W lamps), inductive loads (40W fan and 200W blenders), and a combination of resistive-inductive loads, both with and without PSO-based Power Factor Correction (PFC). By optimizing the phase difference between voltage and current, the PSO algorithm aims to maintain a power factor close to the industry standard of 0.85 or higher. The findings indicate that resistive loads consistently sustain a power factor of 1.00, while inductive loads benefit significantly from PSO implementation. The 40W inductive fan, initially operating at 0.55, improved to 0.57 – 0.60, whereas the 200W inductive blender increased from 0.90 to 0.98. Similarly, mixed resistive-inductive loads showed an enhancement from 0.89 to 0.99, emphasizing PSO’s role in improving power efficiency. The study recorded a total power factor improvement of 0.36, with an average increase of 0.0144 per test case, confirming PSO’s effectiveness in reducing reactive power losses and optimizing energy conversion. These results highlight the potential of PSO-based control strategies in enhancing power quality, stabilizing inverter performance, and improving energy efficiency, particularly in applications where inductive loads are predominant. The research contributes to the development of intelligent inverter systems that offer greater reliability, cost-effectiveness, and energy savings for residential and industrial power applications.