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This letter presents an active and reactive power coordinated damping controller for doubly fed induction generator (DFIG) using second-order sliding mode technique. Through simultaneously modulating active and reactive power of DFIG, the proposed controller has an enhanced damping performance. Its advantages include faster damping speed and robustness to modeling uncertainties and parameter variations. Simulation results have verified its superior performance over existing schemes.

A deep-learning-based hybrid strategy for short-term load forecasting is presented. The strategy proposes a novel tree-based ensemble method warm-start gradient tree boosting (WGTB). Current strategies either ensemble submodels of a single type, which fail to take advantage of the statistical strengths of different inference models, or simply sum the outputs from completely different inference models, which does not maximize the potential of the ensemble. Inspired by the bias-variance trade-off, WGTB is proposed and tailored to the great disparity among different inference models on accuracy, volatility, and linearity. The complete strategy integrates four different inference models of different capacities. WGTB, then, ensembles their outputs by a warm-start and a hybrid of bagging and boosting, which lowers bias and variance concurrently. It is validated on two real datasets from the State Grid Corporation of China of hourly resolution. The result demonstrates the effectiveness of the proposed strategy that hybridizes the statistical strengths of both low-bias and low-variance inference models.

In the context of carbon peak and carbon neutral policies, low-carbon construction has been the focus of most countries worldwide. As one of the most effective ways to achieve green construction, many countries have launched low-carbon policies to promote the development of prefabrication. However, the effectiveness and influencing factors of low-carbon policies on prefabrication need to be further verified under the dynamic game between the government and the construction enterprise. Therefore, this study considered subsidy and carbon tax policies and developed an evolutionary game model to promote the development of the prefabricated construction market. The evolutionary stable strategy of the government and construction enterprise under different scenarios was obtained. Subsequently, a numerical analysis was conducted to further investigate the impact of the key factors on the stable strategy. The results showed that an appropriate hybrid policy of subsidies and taxes could positively promote the prefabrication implementation of the construction enterprise. The government should adopt an appropriate policy intensity according to the maturity of the market. This study can provide effective guidance and practical enlightenment for the government to achieve low-carbon, green, and sustainable construction.

A self-assembly approach is used to fabricate a hierarchical nanostructure using functionalized carbon spheres as nano-spacers to separate graphene nanosheets. The nanostructure significantly enhances capacitance of a graphene supercapacitor by more than 70%, while providing a universal method to self-assembling various carbons into hierarchical structures for energy conversion/storage systems.

The effectiveness of porous pavement (PP) and bio-retention cells (BCs) under the influence of potential climate change was investigated based on representative concentration pathways (RCPs). A case study of a test catchment in Guangzhou illustrated changes of peak runoff under various climate scenarios. There were distinct increases in runoff volume and peak discharge in response to RCP8.5 but only marginal increases in response to RCP2.6 (compared with present conditions). The performance of PP and BCs in terms of percentage reduction of runoff volume and peak discharge was examined for 1-, 10-, and 100-year return period and 1- and 6-h-duration storms under various climate scenarios. The effectiveness of PP and BCs varied non-linearly with the extent of PP and BCs adopted. In general, the fluctuation of hydrological performance of PP is greater than that of BCs in RCP2.6 and RCP8.5 (e.g., peak flow reductions range from -60% to 69% and from -22% to 9%, for 5% area of PP and BCs, respectively). And PP is more cost-effective for frequent storms using life cycle costing analysis. We find that PP and BCs could significantly reduce runoff volume and peak discharge in response to rainfall events with short return period, but not for heavy storms with longer return period.

AbstractOld landfills require pre‐aeration before excavation to reduce the emissions of volatile organic compounds and methane. Variation and distribution of gas species during landfill aeration is important in designing an aeration system and evaluating aeration progress. Limited research is conducted on the variation of gas concentration in aerobic landfills considering methane oxidation and aerobic waste degradation. In this study, a numerical model is developed considering reactions to simulate the changes in methane, oxygen, and carbon dioxide concentrations in landfills during air injection and extraction. Parameter sensitivity analyses are conducted to evaluate the effects of permeability, dispersion coefficient, maximum methane oxidation rate, and oxygen consumption rate on simulation results. Results show that the model is sensitive to oxygen consumption rate. Overall, the application of this model in aerobic landfills provides a practical method to predict gas concentration variation. This model can be used in the optimal design of in situ aeration system.