Description: Distributed generation is a flexible and effective way to utilize renewable energy. The dispersed generators are quite close to the load, and pose some power quality problems such as harmonic current emissions. This paper focuses on the harmonic propagation and interaction between a small-scale wind farm and nonlinear loads in the distribution grid. Firstly, by setting the wind turbines as P – Q(V) nodes, the paper discusses the expanding Newton-Raphson power flow method for the wind farm. Then the generalized gamma mixture models are proposed to study the non-characteristic harmonic propagation of the wind farm, which are based on Gaussian mixture models, improved phasor clustering and generalized Gamma models. After the integration of the small-scale wind farm, harmonic emissions of nonlinear loads will become random and fluctuating due to the non-stationary wind power. Furthermore, in this paper the harmonic coupled admittance matrix model of nonlinear loads combined with a wind farm is deduced by rigorous formulas. Then the harmonic propagation and interaction between a real wind farm and nonlinear loads are analyzed by the harmonic coupled admittance matrix and generalized gamma mixture models. Finally, the proposed models and methods are verified through the corresponding simulation models in MATLAB/SIMULINK and PSCAD/EMTDC.

Description: Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO) to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well.

Description: As a critical subsystem in electric vehicles and smart grids, a battery energy storage system plays an essential role in enhancement of reliable operation and system performance. In such applications, a battery energy storage system is required to provide high energy utilization efficiency, as well as reliability. However, capacity inconsistency of batteries affects energy utilization efficiency dramatically; and the situation becomes more severe after hundreds of cycles because battery capacities change randomly due to non-uniform aging. Capacity mismatch can be solved by decomposing a cluster of batteries in series into several low voltage battery packs. This paper introduces a new analysis method to optimize energy utilization efficiency by finding the best number of batteries in a pack, based on capacity distribution, order statistics, central limit theorem, and converter efficiency. Considering both battery energy utilization and power electronics efficiency, it establishes that there is a maximum energy utilization efficiency under a given capacity distribution among a certain number of batteries, which provides a basic analysis for system-level optimization of a battery system throughout its life cycle. Quantitative analysis results based on aging data are illustrated, and a prototype of flexible energy storage systems is built to verify this analysis.

Description: In order to improve the effects of denoising, this paper introduces the basic principles of wavelet threshold denoising and traditional structures threshold functions. Meanwhile, it proposes wavelet threshold function and fixed threshold formula which are both improved here. First, this paper studies the problems existing in the traditional wavelet threshold functions and introduces the adjustment factors to construct the new threshold function basis on soft threshold function. Then, it studies the fixed threshold and introduces the logarithmic function of layer number of wavelet decomposition to design the new fixed threshold formula. Finally, this paper uses hard threshold, soft threshold, Garrote threshold, and improved threshold function to denoise different signals. And the paper also calculates signal-to-noise (SNR) and mean square errors (MSE) of the hard threshold functions, soft thresholding functions, Garrote threshold functions, and the improved threshold function after denoising. Theoretical analysis and experimental results showed that the proposed approach could improve soft threshold functions with constant deviation and hard threshold with discontinuous function problems. The proposed approach could improve the different decomposition scales that adopt the same threshold value to deal with the noise problems, also effectively filter the noise in the signals, and improve the SNR and reduce the MSE of output signals.

Description: Considering the influence of group piles, a prediction model for three-dimensional ground surface settlement induced by circular metro tunnels excavation in incompressible rock masses is proposed based on the stochastic medium theory and the shear displacement method. The surface settlement caused by the metro tunnel opening is divided into two parts. One part is soil mass settlement caused by the metro tunnel opening and calculated by the stochastic medium theory. The other part is the settlement induced by the friction force between the group piles and the soil mass around the metro tunnel cross section and calculated by the shear displacement method. The three-dimensional prediction of the ground surface settlement is obtained by the linear superposition of the two parts. The validation of the proposed prediction approach is proved by comparing with the measured data and the numerical model of the double tunnels under the Puyuan overpass where metro tunnels undercrossed group piles. The effects of buried depth, radial convergences, center distance of double tunnels, position and size of piles, and group piles are analyzed and discussed. The improved prediction approach can be applied to calculate the three-dimensional ground settlement, especially for the metro tunnels crossing through group piles.

Description: In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the birth targets, the measurements are adaptively partitioned into two parts, persistent and birth measurement sets, for updating the persistent and birth target Probability Hypothesis Density, respectively. Furthermore, the collaboration mechanism of multiple probability hypothesis density (PHDs) is established, where tracks can be automatically extracted. Simulation results reveal that the proposed filter yields considerable computational savings in processing requirements and significant improvement in tracking accuracy.

Description: The Open Geospatial Consortium (OGC) Geography Markup Language (GML) standard provides basic types and a framework for defining geo-informational data models such as CityGML and IndoorGML, which provide standard information models for 3D city modelling and lightweight indoor network navigation. Location information, which is the semantic engine that fuses big geo-information data, is however, discarded in these standards. The Chinese national standard of Indoor Multi-Dimensional Location GML (IndoorLocationGML) presented in this study can be used in ubiquitous indoor location intelligent applications for people and robots. IndoorLocationGML is intended as an indoor multi-dimensional location information model and exchange data format standard, mainly for indoor positioning and navigation. This paper introduces the standard’s main features: (1) terminology; (2) indoor location information model using a Unified Modeling Language (UML) class diagram; (3) indoor location information markup language based on GML; and (4) use cases. A typical application of the standard is then discussed. This standard is applicable to the expression, storage, and distribution of indoor multi-dimensional location information, and to the seamless integration of indoor–outdoor location information. The reference and basis are therefore relevant to publishers, managers, users, and developers of indoor navigation and location-based services (LBS).

Description: To investigate the dynamics and relative drivers of cellulose degradation during litter decomposition, a field experiment was conducted in three individual ecosystems (i.e., forest floor, stream, and riparian zone) of an alpine forest meta-ecosystem on the eastern Tibetan Plateau. Four litter species (i.e., willow: Salix paraplesia, azalea: Rhododendron lapponicum, cypress: Sabina saltuaria, and larch: Larix mastersiana) that had varying initial litter chemical traits were placed separately in litterbags and then incubated on the soil surface of forest floor plots or in the water of the stream and riparian zone plots. Litterbags were retrieved five times each year during the two-year experiment, with nine replicates each time for each treatment. The results suggested that foliar litter lost 32.2%–89.2% of the initial dry mass depending on litter species and ecosystem type after two-year’s incubation. The cellulose lost 60.1%–96.8% of the initial mass with degradation rate in the order of stream > riparian zone > forest floor. Substantial cellulose degradation occurred at the very beginning (i.e., in the first pre-freezing period) of litter decomposition. Litter initial concentrations of phosphorus (P) and lignin were found to be the dominant chemical traits controlling cellulose degradation regardless of ecosystems type. The local-scale environmental factors such as temperature, pH, and nutrient availability were important moderators of cellulose degradation rate. Although the effects of common litter chemical traits (e.g., P and lignin concentrations) on cellulose degradation across different individual ecosystems were identified, local-scale environmental factors such as temperature and nutrient availability were found to be of great importance for cellulose degradation. These results indicated that local-scale environmental factors should be considered apart from litter quality for generating a reliable predictive framework for the drivers of cellulose degradation and further on litter decomposition at a global scale.

Description: Phenolic acid profiles and antioxidant activities of outer bran, coarse bran, and shorts from blue, black, and purple wheat were analyzed. Phenolic acids were mainly in the bound form in pigmented wheat bran fractions. Phenolic acid content decreased in the order of outer bran, coarse bran, and shorts for the three pigmented wheat varieties. HPLC analysis of phenolic extracts demonstrated that the bound form of phenolic acids contained more ferulic, isoferulic, and p-coumaric acids compared to their free counterparts. Among the three pigmented wheat varieties, the bran fractions from blue wheat contained higher bound phenolic acids than the other two pigmented wheat bran fractions, except for purple coarse bran. The blue wheat outer bran had the highest total bound phenolic acid of 3458.71 μg/g while the purple wheat shorts had the lowest of 1730.71 μg/g. The contribution of bound phenolic acids to the total phenolic content and antioxidant activity was significantly higher than that of free phenolic acids. Blue wheat bran fractions had the highest radical scavenging activity against DPPH∙ while those of purple wheat gained the highest ABTS∙+ scavenging activity. High correlations were observed between TPC and radical scavenging capacities for DPPH and ABTS (, ).

Description: Sustainability, Vol. 10, Pages 1748: The Evolution of Renewable Energy Price Policies Based on Improved Bass Model: A System Dynamics (SD) Analysis Sustainability doi: 10.3390/su10061748 Authors: Xin-gang Zhao Yu-zhuo Zhang Yan-bin Li Many countries in the world have implemented many price support policies to promote the development of renewable energy, and there are evolutionary processes between different policies at different stages of national development. Existing literature has less research on the internal mechanism and alternative process of renewable energy price policies’ evolution process. In view of this, this paper innovatively introduces the classic model of innovation diffusion theory, the Bass model, into the renewable energy price mechanism, and improves it on the basis of the traditional Bass model, and then proposes a system dynamics (SD) simulation based on the improved Bass model to study the evolution process of the renewable energy price policies. This paper mainly studies the evolution process of the policies from feed-in tariff (FIT) to renewable portfolio standard (RPS), and takes China’s wind power industry as an example to simulate the model. The results show that FIT can effectively and quickly evolve to RPS based on the internal influence of the interaction among power generation enterprises and the external influence of government behaviors. All the power generation enterprises will implement RPS, and the amount of green power enterprises eventually grows steadily and slowly. In addition, increasing the decline rate of FIT subsidy and RPS unit fine can effectively promote the evolution of RPS policy, and also improve the amount of green power enterprises and the activity of the tradable green certificates (TGC) trading market.