Hira Tahir

Although it is a fundamental technique for autonomous navigation in GNSS-denied environments, tightly-coupled multi-sensor fusion has advanced faster than conventional narrative assessments. Using a PRISMA-guided review, bibliometrics, and Latent Dirichlet Allocation (LDA) topic modeling ($K=8, C_v=0.62$), we analyze a corpus of \Nincluded{} included publications (2015–2026) to give a data-driven synthesis of the domain. Resilience appears as an increasingly explicit topic across the corpus: more recent publications highlight degeneracy, outliers, and event-driven sensing inside state-estimation pipelines, in contrast to previous work that concentrated on nominal robustness. The literature from 2024 to 2025 particularly shows four trends (2026 is a half year in our export).:(i) measurement-domain integration of 5G, WiFi Round-Trip Time (WiFi-RTT), and ultra-wideband (UWB) signals; (ii) event-based and neuromorphic vision for high-dynamic-range scenarios; (iii) decentralized swarm cooperative localization; and (iv) semantic-cognitive map integration for managing geometric degeneracy. We also find a reporting gap: a lot of studies don't include computational performance data, which makes real-world validation more difficult. The analysis scripts and machine-readable corpus metadata are available upon request. Lastly, using three synthesis tools—a conceptual degradation--response framework for navigation resilience, an empirically supported taxonomy of degeneracy-mitigation mechanisms, and an engineering decision matrix for choosing sensor--estimator topologies under computational and environmental constraints—we convert the review findings into useful recommendations.

This paper proposes an adaptive hierarchical control strategy for a hybrid energy storage system (HESS) integrated within a hub station, aimed at mitigating output power fluctuations and enhancing grid stability under high renewable energy penetration. The proposed framework incorporates hierarchical structure based four control levels, combining optimal power control, adaptive power decomposition via a low-pass filter, adaptive ramp rate regulation, and SOC-based selective control. This structure enables effective coordinated management of HESS power output, SOC, and ramp rate in response to varying operating conditions. Simulation results demonstrate that the proposed strategy significantly reduces SOC variation and ramp rate violations compared to conventional methods. Furthermore, the proposed strategy achieves a substantial improvement in renewable energy hosting capacity, with the maximum allowable renewable generation increased by approximately 35% compared to the conventional method. System-level validation using the IEEE 14-bus test system further confirms that the hub station enhances grid voltage stability and increases the permissible RES penetration level by approximately 25%. These results verify the effectiveness and scalability of the proposed control strategy for stable renewable energy integration into power grids.

The new millennium witnessed an unanticipated escalation in the installation of rooftop solar panels, particularly due to the development of highly efficient power electronic converters (PECs). The ‘battle of currents’ between AC and DC, which settled in the favor of AC in the nineteenth century, reignited as DC is striking back due to this technological augmentation. The shifting trend towards DC is more pronounced in the residential sector, which necessitates a comparative analysis of AC and DC at distribution scale on realistic grounds. Modern home data extracted from the energy information administration (EIA) has been utilized to devise a mathematical model based on bottom-up approach. The comparative analysis has been performed encompassing scenarios of varying PEC efficiencies as a result of daily load variation. Moreover, the scenarios of multiple PEC efficiencies and rooftop solar capacities are also considered. The comparative analysis revealed efficiency advantage of 1.966%, 1.41% and 1.17% in favor of DC as compared to AC for the scenarios considered. In the end future recommendations are presented to further enhance the efficiency of DC, thereby providing a concrete standing for power industry decision of adopting DC at distribution scale.

This paper is an attempt to present a simple yet innovative planning method for determining the type of common bus in a hub station (HS), devised on efficiency and reliability grounds. The efficiency is evaluated by modeling the efficiency curves of the converters under part-load and full-load conditions, hence enabling a realistic estimate of the efficiency. Reliability evaluation is executed by modeling the failure and repair rate distributions of the HS components. The optimal common bus type selection is based on both the efficiency and reliability metrics of the HS. The deterministic factor in the type of common bus selection is proved to be the number of components in the HS. The results indicate that DC and AC systems have comparable efficiencies with a meagre difference of 1.26%. The failure rate of AC common bus architecture is 22% greater than DC common bus architecture resulting in a 1.788 times reliability advantage of the DC system. Moreover, the greater number of components in the case of a AC common bus adds to the economic advantage of DC with a lower number of components leading DC to be an optimal design.