In this research paper, an inductively coupled distributed static compensator (IC-DSTATCOM) for three phase three wire (3P3W) electric power distribution system (EPDS) is proposed. The contraction of power quality (PQ) was marked as a perilous droop mode bump into direct coupled distributed static compensator (DC-DSTATCOM). To regain the PQ, inductive coupling transformer is assisted in conjunction with DC-DSTATCOM. The system equivalent circuit of IC-DSTATCOM is accomplished by take into account of impedance of both transformer and DC-DSTATCOM to reveal the filtering technique. The filtering icos∅ mechanism is performed by following the generalized mathematical approach using MATLAB/Simulink. A case education is reviewed in detail to illustrate the performance of both DC-DSTATCOM and IC-DSTATCOM. The IC-DSTATCOM is amplified healthier as compared to other in terms of harmonics shortening, good power factor, load balancing, and potential regulation. To examine the effectiveness, simulation outputs of the IC-DSTATCOM with different PQ parameter indices are presented by following the benchmark measure of IEEE-2030-7-2017 and IEC-61000-1 system code.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Electric bicycles (e-bikes) have rapidly emerged as a sustainable alternative to conventional modes of transportation. This study reviews the evolution, technological advancements, and environmental benefits of e-bikes through comparative data analysis, survey results, and case studies. The findings demonstrate that the developments in lithium-ion batteries, lightweight materials, and smart motor systems have significantly improved e-bike performance, efficiency, and affordability. From an environmental perspective, e-bikes can cut greenhouse gas emissions by more than 90% compared to cars, while simultaneously improving urban air quality and reducing overall pollution levels. Survey responses indicate that e-bike users often substitute short car trips, promoting sustainable commuting behaviors and supporting public health. Despite these benefits, challenges persist regarding insufficient infrastructure, inconsistent policy support, and limited battery recycling programs. In summary, e-bikes constitute a transformative element in sustainable urban mobility and climate change mitigation. Beyond policy reforms, future work should prioritize renewable-powered charging systems and circular battery utilization models to ensure e-bikes contribute to a more resilient and environmentally friendly transportation ecosystem.

This article presents the dual operation of distributed energy resources (DER) integrated impedance source inverter (DI-ZSI). The distribution grid, DER and variable nonlinear load are operating on two modes. In mode-1, power generated by the DER is zero or less then the load requirement and the inverter act as a voltage source inverter (VSI) for shunt compensation only. But, in mode-2, power generated by the DER greater than the load requirement and operates as a DI-ZSI based distributed static compensator (DSTATCOM). In this scenario, it not only acts as a shunt compensator but also inject active power to the distribution grid. An accurately tuned proportional integral with adaptive least mean square (ALMS) controller is used to generate the switching signals of inverter switches. The DI-ZSI performs stable operation in the distribution grid over a variable non-linear loading. A field programmable gate array (FPGA) SPARTAN-6 controller is used to develop the proposed system. Experimental results from DI-ZSI and VSI under variable loading highlighted the superiority of the DI-ZSI as per guidelines imposed by IEEE-2030-7-2017.