Uniaxial trackers are widely employed as the frame for solar photovoltaic (PV) panel installation. However, when used in sloping terrain scenarios such as mountain and hill regions, it is essential to apply a solar-tracking strategy with the sloping factors considered, to eliminate the shading effects between arrays and reduce the electricity production loss due to terrain changes. Based on a uniaxial tracker on the sloping terrain of a PV farm located in Ningxia, this study established a uniaxial solar-tracking strategy for sloping terrain by integrating a spatial projection model with a dynamic shadow assessment method. In the proposed strategy, the optimal tilt angle of the PV array and related desirable adjustment are identified taking into consideration major parameters such as the shadow area ratio S and the average solar irradiance intensity G. A tool underpinned by Matlab Simulink has also been developed to realize the proposed solar-tracking strategy. With the input of a simulated ramp signal β and the dynamically changed time parameters, the tracking angle of PV arrays over the simulated duration is accurately predicted, followed by a series of experimental validations conducted on the winter solstice and a typical sunny day (15 September). Moreover, the study also explored the terrain impacts on solar tracking by comparing the sloping terrain and flat terrain applications. The analytic and experimental results indicate that (a) the maximum value of the G(β) function could serve as the input to identify the optimal tracking angle; (b) the application of the flat terrain tracking (FTT) strategy in sloping terrain would result in a reduction of average solar irradiance intensity harvested by the PV arrays with varying degrees; (c) in the context of an east–west −7° sloping terrain, compared with the FTT strategy, the sloping terrain tracking (STT) strategy enabled anti-shading tracking, and then increased the daily PV electricity yield by 0.094 kWh/kWp, which is around 1.48% of the daily energy production; (d) given a measurement with annual scale, the STT strategy could cause a 1.26% increase in the energy harvesting with a flat uniaxial PV array on a −7° slope terrain, achieving an annual increase of 25.16 kWh/kWp. The experimental comparative analysis validated the precision of the proposed solar-tracking model, which has far-reaching significance for achieving automatic solar-tracking of PV modules, as well as improving the capacity and efficiency of PV systems.

The incorporation of graphene oxide (GO) into composite materials can modulate their overall performance. To enhance the performance of acoustic emission (AE) signals, 3% GO was incorporated into glass fiber-reinforced polymer (GFRP) composites, resulting in the creation of GO-GFRP composite materials. The sentry function was first used to investigate the damage evolution of the material. Then, the AE signals were analyzed using multivariate mode decomposition (MVMD) and the generalized S transform to identify the damage mechanisms. Finally, scanning electron microscopy (SEM) was used to observe the fracture surfaces of the samples to confirm the material failure. The experiments identified four damage mechanisms: matrix cracking, fiber debonding, delamination failure, and fiber breakage. It was also found that GO-GFRP composites are more prone to fiber debonding compared to GFRP composites without added GO.

Decarbonising the urban built environment for reaching carbon neutrality is high on the agenda for many cities undergoing rapid expansion and densification. As an important urban form, precincts have been increasingly focused on as the context for urban redevelopment planning and at the forefront for trialling carbon reduction measures. However, due to interplays between the built forms and the occupancy, the carbon performance of a precinct is significantly affected by morphological variations, demographical changes, and renewable energy system deployment. Despite much research on the development of low-carbon precincts, there is limited analysis on aggregated effects of population growth, building energy efficiency, renewable energy penetration, and carbon reduction targets in relation to precinct carbon signature and carbon neutral potential for precinct redevelopment and decarbonisation planning. In this paper, an integrated carbon assessment model, including overall precinct carbon emissions and carbon offset contributed by precinct-scale renewable energy harvesting, is developed and applied to examine the lifecycle carbon signature of urban precincts. Using a case study on a residential precinct redevelopment, scenario analysis is employed to explore opportunities for decarbonising densification development and the carbon neutral potential. Results from scenario analysis indicate that redevelopment of buildings with higher-rated energy efficiency and increase of renewable energy penetration can have a long term positive impact on the carbon performance of urban precincts. Meanwhile, demographical factors in precinct evolution also have a strong influence on a precinct’s carbon neutral potential. Whilst population size exerts upward pressure on total carbon emissions, changes in family types and associated consumption behaviour, such as travelling, can make positive contributions to carbon reduction. The analysis also highlights the significance of embodied carbon to the total carbon signature and the carbon reduction potential of a precinct during densification, reinforcing the notion that “develop with less” is as important as carbon offsetting measures for decarbonising the precinct toward carbon neutrality.

Many efforts have recently been dedicated to developing smart sockets that seek to provide insights into the reduction of standby energy waste coupled to electric appliances. However, not all technical solutions consider the techno-economic benefits in the development. This research presents a hardware solution based on STM32F103 (STM32F103 devices use the Cortex-M3 core, with a maximum CPU speed of 72 MHz) for the development of an energy-efficient smart socket to address the standby energy waste of household electric appliances and associated economic losses. Input-output analysis on monitored voltage and current was employed to assess the performance and examine the precision of the developed system. As it was targeted at facilitating easier operation, the smart socket was developed to be compatible with other remote controllers of household electric appliances. Experimental results indicated that the developed system could measure voltage values accurately to avoid overvoltage for security protection. The measuring unit could monitor current values with high precision to support the energy-saving control. A functional testing was conducted on the prototypes with a lifecycle assessment employed to validate the economic attractiveness of the developed system. Results indicated that the system is user friendly and cost-effective as no extra wiring required and network environment independent. Indeed, indirect fruits, such as lifespan extension and safety enhancement, could also be achieved for appliances.

Given the prejudicial environmental effects of fossil-fuel based energy production, renewable energy sources can contribute significantly to the sustainability of human society. As a clean, cost effective and inexhaustible renewable energy source, wind energy harvesting has found a wide application to replace conventional energy productions. However, concerns have been raised over the noise generated by turbine operating, which is helpful in fault diagnose but primarily identified for its adverse effects on the local ecosystems. Therefore, noise monitoring and separation is essential in wind turbine deployment. Recent developments in condition monitoring provide a solution for turbine noise and vibration analysis. However, the major component, aerodynamic noise is often distorted in modulation, which consequently affects the condition monitoring. This study is conducted to explore a novel approach to extract low-frequency elements from the aerodynamic noise background, and to improve the efficiency of online monitoring. A framework built on the spline envelope method and improved local mean decomposition has been developed for low-frequency noise extraction, and a case study with real near-field noises generated by a mountain-located wind turbine was employed to validate the proposed approach. Results indicate successful extractions with high resolution and efficiency. Findings of this research are also expected to further support the fault diagnosis and the improvement in condition monitoring of turbine systems.

As essential load-bearing equipment to support the nacelle and blades, the tower is subjected to the whole wind turbine loading. This study proposes a new method of combining acoustic emission and normalized accumulation parameters to characterize wind turbine towers Q345 steel damage. First of all, tendency analysis of the acoustic emission signal parameter was conducted to determine damage degree during the damage stage. Secondly, we normalized the accumulation of amplitude and other parameters to compare the proportion of each accumulation parameter at different stages, while studying the spectra of common acoustic emission signals. Finally, comparing the differences and similarities of the normalized accumulation parameters between three different rates, we analyze the effect of rate on the normalized accumulation parameters. These results indicate that the normalized cumulative duration parameter is suitable for characterizing the yield damage occurrence, the normalized cumulative energy parameter is very sensitive to the fracture stage, the normalized cumulative energy parameter is least influenced by the loading rate, and the energy parameter is a sensitivity factor for normalized expression, which to realizes the stage of damage judgment.