Journal of Advanced Research in Instrumentation and Control Engineering

A Comprehensive Review on Power Loss Reduction and THD Mitigation in Low and High Voltage Distribution Systems

Pushpendra Patel — 2026-02-23

The growing need for reliable and efficient power distribution has once again brought forth issues regarding power quality and technical losses in electrical networks. Because of their long lowtension lines and unbalanced nonlinear loads, conventional Low Voltage Distribution Systems (LVDSs) are mostly subjected to high I²R losses, voltage drops, and high Total Harmonic Distortion (THD). On the contrary, High Voltage Distribution Systems (HVDSs) place the 11 kV network closer to consumer clusters, keeping smaller transformers nearby. Hence, there are fewer line losses, good voltage regulation, and power theft mitigation. This review paper presents a detailed assessment of existing work in the literature on comparisons between LVDSs and HVDSs with respect to efficiency, voltage stability, reliability, and THD performances. Recent developments in MATLAB/SIMULINK-based modelling and field implementations are critically studied so as to emphasise the basic parameters influencing system performance. The paper discusses network design, conductor sizing, load segregation, and harmonic filtering towards optimised power delivery. It also underscores the interfacing of renewable energy sources such as solar and wind into distribution systems while looking into the implications on power losses and harmonic behaviour. Various case studies have revealed that HVDSs can reduce technical losses by 30–50% and attain improved THD levels as compared to LVDSs, thereby playing a vital role in the evolution of smart grids. However, a fair share of issues regarding the enormous initial capital investment, logistics of maintenance, and harmonics from distributed generation still remain to be resolved. The review finally draws attention to the synergy of modelling, real-time monitoring, and adaptive control strategies needed for sustainable and high-quality power distribution in ever-evolving LVDS and HVDS networks.

A Comprehensive Review on Buck–Boost Integrated Control Strategies for Cascaded PV Inverter Systems under Variable Irradiation and Unbalanced Grid Conditions

Mohamed Emadeldin Mohamed Awadalkarem — 2026-02-09

With the rapid integration of photovoltaic (PV) systems into modern power networks, the need has increased for power converters whose efficiency is high enough that they can remain stable with fluctuating irradiance. and temperature variations as well as unbalanced loading conditions. Their standard single-stage evidences a lack of voltage regulation which, in turn, results in imperfect power extraction and unnecessary elevated harmonic distortion. It further discomfort scales grid stability. The paper reviews the progress of the technology, challenges faced, and innovations of PV inverter control with an accentuated exploration aiming at buck-boost control integrated by cascaded and per-phase distributed inverter structures. Research from 2021 to 2025 has shown a change of focus toward the development of intelligent converter designs, algorithm projects for adaptiveness, coordinating DC-DC/DC-AC operations for system performance enhancement. The review amalgamates with the results from studies regarding dual-iteration-based modeling, hybrid metaheuristic optimization (HJAYADE, POA, ITSA), dynamic fractional order modeling, AI-based irradiance forecasting, and advanced MPPT techniques (fuzzy logic, MSSA-optimized controllers, MPC, and deep learning). Further improvements manifested include significantly reduced RMSE in PV parameter estimation, an MPPT tracking efficiency of more than 99%, a THD rate below 1% for currents and voltages, and perhaps noticeable active power increases in grid-interconnected cases.

A Review of Multi-Objective Optimization: Methods and Algorithms in Mechanical Engineering Problems

Gaurav Tripathi — 2026-03-02

Modern mechanical engineering problems often involve multiple conflicting objectives such as minimizing cost while maximizing performance, strength, and efficiency. Traditional optimization approaches, which focus on a single objective, are no longer sufficient to address such complex design challenges. Multi-objective optimization (MOO) provides a systematic framework to handle trade-offs among competing objectives and identify optimal design solutions. This review paper presents a comprehensive overview of various multi-objective optimization methods and algorithms widely used in mechanical engineering applications. Classical techniques, evolutionary algorithms, swarm intelligence approaches, and hybrid optimization strategies are discussed in detail. The paper also highlights practical applications in design optimization, thermal systems, manufacturing, and structural engineering. Finally, current challenges and future research directions in the field are outlined.

Design and Performance Analysis of Microcontroller-Based Automated Control Systems

Maneeka Arora — 2026-03-24

Automation has become a fundamental component of modern engineering systems, significantly improving efficiency, accuracy, and reliability across various industrial and domestic applications. Microcontroller-based control systems offer a cost-effective and flexible solution for implementing automation due to their compact size, programmability, and integration capabilities. This paper presents the design, development, and performance analysis of a microcontroller-based automated control system. The system incorporates sensors, actuators, and a central processing unit to perform real-time monitoring and control operations. A structured methodology is followed, including hardware design, software development, and system integration. Performance evaluation is conducted based on parameters such as response time, accuracy, reliability, and power consumption. The results demonstrate that the proposed system provides efficient real-time control with minimal latency and high precision. The study highlights the advantages of microcontroller-based automation systems and suggests potential improvements for future applications in industrial and smart environments.

Development of a Fuzzy Logic-Based Control System for Process Optimization

Lavi Tanwar — 2026-03-29

In modern industrial environments, achieving optimal control of complex and nonlinear processes remains a significant challenge. Conventional control techniques such as proportional–integral–derivative (PID) controllers often struggle to maintain performance in systems with uncertainties, nonlinearities, and time-varying dynamics. This paper presents the development and performance evaluation of a fuzzy logic- based control system for process optimization. The proposed system utilizes fuzzy inference mechanisms to mimic human decision-making and improve control accuracy and adaptability. A microcontroller-based implementation is designed to integrate sensors, fuzzy logic algorithms, and actuators in a closed-loop configuration. The system is evaluated under various operating conditions, and performance metrics such as response time, stability, and error minimization are analyzed. The results demonstrate that the fuzzy logic-based controller outperforms conventional control methods in terms of robustness, flexibility, and efficiency, making it suitable for real-time industrial applications.