To explore single-phase micro inverter with boosting ability, simple structure, low cost and high power density, a new structure of multilevel inverter (MLI) is proposed in this paper. With this structure, two half-bridge modular switched-capacitor circuits are arranged on both left- and right-sides of a dc source. Circuit configuration of this MLI can be bilaterally symmetrical and this benefits to modular design and voltage stress reduction of inverting bridges. Additionally, in order to reduce voltage ripple of capacitors and total harmonic distortion of output voltage simultaneously, a hybrid pulse width modulation strategy is developed to improve the performance of this MLI. As a result, capacitors of this MLI can be replenished repeatedly when they are taken as voltage sources to generate different voltage levels. Circuit configuration, operation principle, modulation, power loss and voltage ripple are analyzed in detail. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed MLI and modulation strategy.

Constructing comprehensive multimodal feature representations from RGB images (RGB) and point clouds (PT) in 2D–3D multimodal anomaly detection (MAD) methods is very important to reveal various types of industrial anomalies. For multimodal representations, most of the existing MAD methods often consider the explicit spatial correspondence between the modality-specific features extracted from RGB and PT through space-aligned fusion, while overlook the implicit interaction relationships between them. In this study, we propose a uni-modal and cross-modal fusion (UCF) method, which comprehensively incorporates the implicit relationships within and between modalities in multimodal representations. Specifically, UCF first establishes uni-modal and cross-modal embeddings to capture intramodal and intermodal relationships through uni-modal reconstruction and cross-modal mapping. Then, an adaptive nonequal fusion method is proposed to develop fusion embeddings, with the aim of preserving the primary features and reducing interference of the uni-modal and cross-modal embeddings. Finally, uni-modal, cross-modal, and fusion embeddings are all collaborated to reveal anomalies existing in different modalities. Experiments conducted on the MVTec 3D-AD benchmark and the real-world surface mount inspection demonstrate that the proposed UCF outperforms existing approaches, particularly in precise anomaly localization.

Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.

Due to the complex configuration and control framework, the conventional microgrid is not cost-effective for engineering applications with small or medium capacity. A stand-alone modular microgrid with separated AC bus and decentralized control strategy is proposed in this paper. Each module is a self-powered system, which consists of wind and solar power, a storage battery, load and three-port converter. The modules are interconnected by three-port converters to form the microgrid. Characteristics, operation principle, control of the modular microgrid and the three-port converter are analyzed in detail. Distributed storage batteries enable power exchanges among modules to enhance economic returns. Economic dispatch of the stand-alone modular microgrid is a mixed-integer programming problem. A day-ahead operation optimization model including fuel cost, battery operation cost, and power transmission cost is established. Because there are so many constraints, it is difficult to produce a feasible solution and even more difficult to have an improved solution. An improved simplified swarm optimization (iSSO) method is therefore proposed. The iSSO scheme designs the new update mechanism and survival of the fittest policy. The experimental results from the demonstration project on DongAo Island reflect the effectiveness of the stand-alone modular microgrid and the economic dispatch strategy based on the iSSO method.

Conventional microgrids have a specific system configuration and a complex hierarchical control structure, which has resulted in difficulties in their economic development. A modular microgrid based on distributed battery storage has been proposed to realize the rapid economic development of small-to-medium microgrids. Control of modular microgrids is simplified to voltage control within modules and exchange power control among modules. Battery power has great influence on battery performance. Space-time complementary power characteristics among modules help to alleviate power fluctuations, prolong the service life and realize the unified maintenance of distributed batteries. Leader-following consensus theory of multi-agent systems is adopted to realize the power and capacity consensus tracking of distributed battery storage in a modular microgrid. Sufficient and necessary conditions for continuous-time and sampled-data bounded power and capacity consensus tracking of distributed battery storages are deduced by a matrix analytical method. Steady regions of sampling period and sampling delay for sampled-data bounded power and capacity consensus tracking are determined by analytical or numerical solutions. Simulations and experiments on a modular microgrid demonstration project located on DongAo Island (China) show the effectiveness and robustness of the proposed power and capacity consensus tracking strategy for distributed storage systems. The power and capacity consensus tracking strategy determines the exchange power among modules and improves the control technology of modular microgrids.

Aerogel is widely recognized as a superinsulating material with great potential for enhancing the thermal insulation performance of building walls. It can be applied in various forms such as aerogel plasters (AP), aerogel fibrous composites (AFC), and aerogel concrete (AC) in practical engineering applications. This study aims to investigate the most efficient application form for maximizing building insulation performance while minimizing the amount of aerogel used. To predict the thermal insulation performance of aerogel-insulated walls, a resistance–capacitance network model integrating the aerogels’ effective thermal conductivity model was developed and was validated by comparing it with Fluent simulation software results in terms of surface temperature. Using the validated models, the thermophysical parameters, transient thermal properties, and transmission load were predicted and compared among AP, AFC, and AC walls. The results indicate that using AFC can result in approximately 50% cost savings to achieve the same thermal resistance. After adding a 20 mm thickness of aerogel to the reference wall without aerogel, the AFC wall exhibited the highest improvement in thermal insulation performance, reaching 46.0–53.5%, followed by the AP wall, and then the AC wall, aligning with considerations of microstructural perspectives, thermal resistance distributions, and thermal non-uniformity factors. Therefore, giving priority to AFC use could reduce the required amount of silica aerogel and enhance economic efficiency. These results provide valuable insights for theoretical models and the application of aerogel-insulated walls in building engineering insulation.