Enhancement of technical, economic and environment Benefits of PQ disturbances in Grid connected system using fuzzy logic based IUPQC

Maintaining peak performance in modern power systems while dealing with power quality disturbances (PQDs) is no easy feat. This study suggests a new way to improve grid-connected systems' technical, economic, and environmental benefits during PQDs by using an Interline Unified Power Quality Conditioner (IUPQC) based on fuzzy logic. The research uses state-of-the-art methods that incorporate fuzzy logic control into the IUPQC framework to reduce voltage sag, swell, flicker, harmonics, and interruptions, among other PQDs. Considering the nonlinear and ever-changing character of PQDs, fuzzy logic is an excellent choice for a control mechanism because of its resilience and adaptability in the face of uncertain and imprecise input. The IUPQC detects and responds to PQDs by analyzing system conditions and adjusting its operation with the use of fuzzy logic-based control algorithms. An advanced power conditioning device in and of itself, the IUPQC can mitigate numerous PQDs at various points in the power distribution system all at once. The IUPQC outperforms and provides more flexibility than traditional power quality mitigation devices by combining shunt active power filters with series filters. The research models the grid-connected system and simulates various PQDs situations using powerful simulation tools like MATLAB/Simulink. Furthermore, experimental validation is carried out using real-world hardware configurations to confirm the efficacy and practicability of the suggested fuzzy logic-based IUPQC in reducing PQDs in real-world operating scenarios. Field implementation and case studies, environmental effect assessment, multi-objective optimization, and comparison analysis will all be further explored in the revised and expanded edition of this project. The fuzzy logic-based IUPQC will be compared to other methods for reducing PQDs, including active power filters, passive filters, and traditional IUPQC, to show how much better it is and how much less expensive it is. In addition, we will evaluate fuzzy logic-based control parameters of the IUPQC using multi-objective optimization approaches. These techniques consider conflicting objectives such minimizing system losses, maximizing power quality improvement, and decreasing operational expenses. Reducing emissions of greenhouse gases, conserving energy, and improving sustainability are just a few of the environmental benefits that an extensive environmental impact assessment will identify. Lastly, case studies and real-world implementation will show how the fuzzy logic-based IUPQC works in various real-world settings, shedding light on its advantages like lower downtime, better power quality, and cost savings for both power utilities and end users.