A Review on Hybrid AI-Based Control Strategies for Harmonic Reduction in Voltage Source Inverters Using CSA–RLS and Neural Network Techniques

2026-06-24T11:26:43+00:00

A major concern within electric power systems is the deterioration in power quality that arises from non-linear loads, as well as renewable energy. Harmonic distortions on electrical networks play a significant role in this process. Voltage Source Inverters (VSIs), largely used in modern power systems, need control strategies that should easily stabilise their highly efficient power outputs. This review paper is aimed at providing an in-depth examination of advanced techniques for harmonic elimination. The focus is on hybrid AI-based control. Traditional approaches such as the use of proportional-integral (PI) controllers and instantaneous p-q theory are still quite good but very poor in tracking a design to perform adaptively under uncertain and extreme dynamic scenarios. This article depicts an evolutionary narrative in intelligent control design with prominence given to the concept of incorporating optimisation and adaptive learning algorithms. Few of these include the Crow Search Algorithm (CSA) and Recursive Least Squares (RLS). It allows real-time parameter tuning so that the converging process can be accelerated, and the extraction of harmonics is robustened to aptitude by given methodologies. The hybrid control researchers have embedded the involvement of neural networks (NN) in it, as they memorise the behaviour of the system that is learnt in that way and thus approximate the optimised demand-switching strategies with VSI. Simulations are carried out in MATLAB/Simulink to gauge the efficacy of the new techniques for some key performance measures, such as THD, response time, and stability, in the given specific simulation based logical context. The study is fairly conclusive in showing that hybrid approaches are far superior to conventional approaches since the hybrid CSA–RLS–NN models have had a dramatic reduction in THD and overall improvement in power quality. Present trends, challenges, and future research directions relevant to intelligent harmonic control for the development of smart power systems—three very conducive areas for the next-generation smart power systems that can be taken care of using hybrid AI-based solutions.

How to cite this article:
Zia F, Kumar A, Gupta C. A Review on Hybrid AI-Based Control Strategies for Harmonic Reduction in Voltage Source Inverters Using CSA–RLS and Neural Network Techniques. J Adv Res Instru Control Engi 2026; 13(3&4): 1-10.

A Review on Battery Energy Storage Systems for Power Quality Improvement in LV and HV Electrical Grids

2026-06-24T11:44:58+00:00

The steady delivery of power quality is a brewing, exerting challenge to electrical grids, owing to increased doses of distributed generation, volatile loads, and renewables. A Battery Energy Storage System (BESS) is thus considered maturely as a soft Mexican wave to please voltage and power consumption, stabilise postings, and jazz up the overall performance of the grid. The paper-practical BESS is aimed at conventional considerations of topology, location, control strategies and voltage as well as high-voltage networks. The outcome of this paper will show that a discrete implementation of converter controls to end studies on methods for reducing pollution by harmonics is well contemplated. With the upper steering wheel of artificial intelligence, the application is described in the section on AI-based optimisation of BESS control; analysis is quantified related to grounds on how to result in better active and reactive, skilful work responses. There is a review of various configurations and integration approaches of BESS into their electrical application networks, and the influence of these on power quality, the efficiency of systems and reliability is described. The review identifies some practical difficulties, including optimal placement, posture factors, and instant monitoring. Further on in the present narrative, some future directions in research are laid out, presenting emphasis on AI-supported predictive control, grid-friendly storage solutions, and total evaluation descriptions of methodologies given over LV and HV grids. As a result of counting numerous very recent papers, it gives a well-detailed image of the state of the art of BESS applications dedicated to improving power quality and thus will provide inspiration to outnumber the lavish audience which is made of researchers, engineers, and dynamic operators of grids to upgrade some for system stability and performance.

How to cite this article:
Aalam T, Jain S, Kumar A. A Review on Battery Energy Storage Systems for Power Quality Improvement in LV and HV Electrical Grids. J Adv Res Instru Control Engi 2026; 13(1): 11-19.

Journal of Advanced Research in Instrumentation and Control Engineering

A Review on Hybrid AI-Based Control Strategies for Harmonic Reduction in Voltage Source Inverters Using CSA–RLS and Neural Network Techniques

A Review on Battery Energy Storage Systems for Power Quality Improvement in LV and HV Electrical Grids