Technologies

The global shift toward decarbonized power systems is driving unprecedented penetration of variable renewable energy sources, especially wind and solar PV. Legacy grid architectures, built around centralized, dispatchable synchronous generation, are ill-suited to manage the bidirectional power flows, reduced inertia, and new stability constraints introduced by inverter-based resources. Existing research offers deep but fragmented insights into individual elements of this transition, such as advanced power electronics, microgrids, or market design, but rarely integrates them into a coherent architectural vision for resilient, high-renewable grids. This review closes that gap by synthesizing technical, architectural, and institutional perspectives into a unified framework for resilient grid design toward 2030 and beyond. First, it traces the evolution from traditional hierarchical grids to smart, prosumer-centric, and modular multi-layer architectures, highlighting the implications for reliability and resilience. Second, it critically examines the core technical challenges of high VRES penetration, including stability, power quality, protection, and operational planning in converter-dominated systems. Third, it reviews the enabling roles of advanced power electronics, hierarchical control and wide-area monitoring, microgrids, and hybrid AC/DC networks. Case studies from Germany, China, and Egypt are used to distil context-dependent pathways and common design principles. Building on these insights, the paper proposes a scalable multi-layer framework spanning physical, data, control, and regulatory/market layers. The framework is intended to guide researchers, planners, and policymakers in designing resilient, converter-dominated grids that are not only technically robust but also economically viable and socially sustainable.

With the rapid growth of global social media users, platforms have become crucial venues for shaping public opinions. However, most existing multimodal topic models focus on large-scale content analysis and often fail to capture nuanced patterns in individual user content. To address this gap, we propose Social Media Account Topic Modeling (SMATM), a novel account-level multimodal topic modeling framework designed to enhance the analysis of individual users’ multimodal data and extract fine-grained personalized themes. SMATM innovatively enhances the ability of topic models to capture social media account data characteristics by introducing a label weighting module, employs a flexible parameter learning module to improve the model’s adaptability to users’ sparse content, and proposes novel evaluation metrics that leverage large language models’ (LLMs) understanding of complex contexts to enhance model interpretability. Experiments conducted on a multimodal account-level dataset collected from social media marketing scenarios validated the effectiveness of the SMATM model in account-level topic extraction. Compared with existing baseline models and ablation models, SMATM achieved significant leads in both topic consistency and diversity evaluation metrics. Particularly in terms of interpretability, the SMATM framework elevated theme accuracy from a baseline of 0.1864 to 0.6059. This 3.25-fold enhancement underscores the model’s superior capability for analyzing individual user behavior and multimodal data. Visualization of cross-industry account themes further confirms that SMATM produces semantically consistent and relevant topics by effectively integrating textual and visual information. Overall, the SMATM model represents a substantial advance in social media content analysis, user profiling, and personalized recommendations.

This paper presents a novel design technique using beam-forming networks based on CORPS (coherently radiating periodic structures) technology to achieve the simplification of the feed network of Fermat spiral antenna arrays. The use of one-layer CORPS structures generates the values of co-phasal excitation required for the feeding network system based on subarrays. The setting of subarrays has been achieved through the study of the behavior of phases of each antenna element in scanning. In this way, elements that exhibit linear behavior in scanning can be grouped. Furthermore, the geometry of the antenna array system using a Fermat spiral configuration applies methods for side lobe level (SLL) reduction such as: a raised cosine amplitude excitation and optimization of the amplitude excitations through the method of genetic algorithms (GA), CORPS amplitude distribution and uniform distribution. The contribution of this paper is to provide a design of a phased antenna system for a Fermat spiral array geometry considering the analysis and study in the performance of SLL, scanning range, and the phase shifters reduction. Full-wave electromagnetic results are provided for the full phased antenna system by using circular patch antenna elements at a frequency of 6 GHz. If our system using CORPS is compared with the use of a conventional feeding network where every antenna in the spiral array is fed with a phase shifter, the benefits of using this phased spiral array system are: a phase shifters reduction capability of 33%, steering ranges of ±22° in the elevation plane, low SLL using the proposed distribution techniques. Furthermore, the choice of CORPS 2×3 networks would allow the integration of the antenna system where one layer is proposed for the feeding network and another layer for the antenna array with the aim of avoiding crossings and unwanted radiation.