Search Results (6)

To enhance the accuracy and efficiency of controlled fault current interruption (CFI) in short-circuit current processing within power systems, a half-cycle elimination prediction algorithm and a double-sampling CFI sequence method are proposed in this study. By analyzing the non-periodic and periodic components of short-circuit currents, the half-cycle elimination method and fast Fourier transform are utilized to compute these two components, respectively. The double-sampling CFI sequence approach is designed to fully utilize the response and waiting times of relay protection. Following the first sampling to estimate the target zero-crossing point, the remaining response and waiting times are allocated for a second sampling and recalculation to enhance the precision of zero-crossing prediction. MATLAB R2023a is employed to conduct multi-scenario simulations, and the algorithm’s performance is evaluated using actual recorded waveform data. The results demonstrate that the proposed algorithm accurately predicts the target zero-crossing point after a short circuit, with a computational error of less than 0.2 ms. Furthermore, the double-sampling sequence method is shown to improve the accuracy of open-circuit zero-crossing point calculations by an order of magnitude. This work provides a novel technical approach for the fast and precise handling of short-circuit faults in power systems. Full article

Yunnan is rich in renewable energy resources. An understanding of its energy structure and developmental trajectories would assist in enabling the design of suitable decarbonizing pathways and how to fit into the national 30–60 agenda. Drawing from endogenous growth theory and time series analysis, our study employs comparative functions and scenario assessments to predict the changes in the key economic indicators, such as GDP, industrial structure shifts, population, and urbanization rates, during the low-carbon transition. We further show energy structure patterns and intensity trends using regression-modeling and data-fitting methods. Based on our analyses, we project that by 2035, Yunnan’s GDP will grow to CNY 5.4761 trillion, with secondary and tertiary industries contributing 88.8%. The population is estimated to grow to 52.08 million with an urbanization rate of 70%. Moreover, fossil fuel energy consumption is forecasted to diminish to 38.7%, and energy consumption intensity is projected to be reduced to 0.38 tons of standard coal per CNY 10,000. If these metrics follow the inherent endogenous growth trend, Yunnan’s emissions are forecasted to peak at around 220 million tons of CO₂ by 2030. These findings not only provide a data foundation for Yunnan’s low-carbon development goals but also illuminate pathways for regions rich in renewable resources to transition towards sustainable growth, emphasizing the harmony between advancement and environmental stewardship. Full article

Rural tourism plays an increasing role in maintaining sustainable rural development. Integrating culture into rural tourism is multifaceted. Local communities have often been regarded as homogeneous, and different voices within them are selectively presented or re-interpreted by those in power. A better understanding of how and why cultures are integrated into rural tourism is urgently needed. This paper aims to investigate (1) the aims and motives of tourism managers to integrate cultural concepts into rural tourism; (2) who has participated in the cultural integration process; and (3) how cultures have been integrated into rural tourism. Based on a scoping literature review, we found that cultures could add more attractions, such as historical heritage, artwork, cultural landscape, customs, food, and language, to the natural landscape and bring more tourists to rural areas. However, integrating cultures into rural tourism is not always successful. Conflicts of interest among different stakeholders are also often found. Some of the worst cases of cultural integration have even destroyed the original natural landscape and local cultures. While cultural integration is complicated, injustice and perverse effects do not have to be a consequence of integrating cultures into rural tourism. Multi-way communication among tourism providers, managers, and consumers can mitigate disruptive outcomes and unlock positive social outcomes. Full article

The adverse effects of rapid urbanization are of global concern. Careful planning for and accommodation of accelerating urbanization and citizenization (i.e., migrants gaining official urban residency) may be the best approach to limit some of the worst impacts. However, we find that another trajectory may be possible: one linked to the rural development plan adopted in the latest Chinese national development strategy. This plan aims to build rural areas as attractive areas for settlement by 2050 rather than to further urbanize with more people in cities. We assess the political motivations and challenges behind this choice to develop rural areas based on a literature review and empirical case analysis. After assessing the rural and urban policy subsystem, we find five socio-political drivers behind China’s rural development strategy, namely ensuring food security, promoting culture and heritage, addressing overcapacity, emphasizing environmental protection and eradicating poverty. To develop rural areas, China needs to effectively resolve three dilemmas: (1) implementing decentralized policies under central supervision; (2) deploying limited resources efficiently to achieve targets; and (3) addressing competing narratives in current policies. Involving more rural community voices, adopting multiple forms of local governance, and identifying and mitigating negative project impacts can be the starting points to manage these dilemmas. Full article

Building landscape resilience inspires the cultivation of the landscape’s capacity to recover from disruption and live with changes and uncertainties. However, integrating ecosystem and society within such a unified lens—that is, socio–ecological system (SES) resilience—clashes with many cornerstone concepts in social science, such as power, democracy, rights, and culture. In short, a landscape cannot provide the same values to everyone. However, can building landscape resilience be an effective and just environmental management strategy? Research on this question is limited. A scoping literature review was conducted first to synthesise and map landscape management change based on 111,653 records. Then, we used the Nuozhadu (NZD) catchment as a case study to validate our findings from the literature. We summarised current critiques and created a framework including seven normative categories, or common difficulties, namely resilience for “whom”, “what”, “when”, “where”, “why”, as well as “can” and “how” we apply resilience normatively. We found that these difficulties are overlooked and avoided despite their instructive roles to achieve just landscape management more transparently. Without clear targets and boundaries in building resilience, we found that some groups consume resources and services at the expense of others. The NZD case demonstrates that a strategy of building the NZD’s resilience has improved the conservation of the NZD’s forest ecosystems but overlooked trade-offs between sustaining people and the environment, and between sustainable development for people at different scales. Future researchers, managers, and decision-makers are thereby needed to think resilience more normatively and address the questions in the “seven difficulties” framework before intervening to build landscape resilience. Full article

Soil moisture is a key component of the water cycle budget. Sensing soil moisture using microwave sensors onboard satellites is an effective way to retrieve surface soil moisture (SSM) at a global scale, but the retrieval accuracy in some regions is inadequate due to the complicated factors influencing the general retrieval process. On the other hand, monitoring soil moisture directly through in-situ devices is capable of providing high-accuracy SSM measurements, but the distribution of such stations is sparse. Recently, the Global Navigation Satellite System interferometric Reflectometry (GNSS-R) method was used to derive field-scale SSM, which can serve as a supplement to contemporary sparse in-situ soil moisture networks. On this basis, it is of great research significance to explore the fusion of these different kinds of SSM data, so as to improve the present satellite SSM products with regard to their data accuracy. In this paper, a multi-source point-surface fusion method based on the generalized regression neural network (GRNN) model is applied to fuse the Soil Moisture Active Passive (SMAP) Level 3 radiometer SSM daily product with in-situ measured and GNSS-R estimated SSM data from five soil moisture networks in the western continental U.S. The results show that the GRNN model obtains a fairly good performance, with a cross-validation R value of approximately 0.9 and a ubRMSE of 0.044 cm³ cm⁻³. Furthermore, the fused SSM product agrees well with the site-specific SSM data in terms of time and space, which demonstrates that the proposed GRNN model is able to construct the non-linear relationship between the point- and surface-scale SSM. Full article