考虑虚拟电厂可信容量的新能源电力系统容量市场出清模型

随着风电和光伏发电装机规模快速增长,系统出现了发电容量充裕度不足的问题。为确保电力系统中的充足发电容量,需要引入容量市场机制。相比于大型火电机组的长建设周期和高投资成本,分布式可调节资源聚合的虚拟电厂（virtual powerplant,VPP）建设周期短、投资小、见效快,是为系统提供发电容量的有效资源。因此,构建了虚拟电厂可信容量（unforcedcapacity,UCAP）计算方法并提出一种考虑虚拟电厂可信容量的新能源电力系统容量市场出清模型。虚拟电厂可信容量计算模型考虑了其功率、能量以及运行特性。容量市场出清模型在考虑发电侧风电、光伏、传统机组的基础上,增加用电侧虚拟电厂参与市场。容量市场出清模型中考虑了高峰容量需求、基本容量需求、电能需求、谷荷需求、爬坡功率需求等系统约束。最后通过算例分析了虚拟电厂可信容量、市场容量总需求量以及新能源装机容量对市场出清结果的影响,验证了本文虚拟电厂可信容量计算方法以及容量市场出清模型的有效性。     

计及用电行为模式的区域商业建筑负荷预测方法

为充分利用智能电表采集的细粒负荷数据并提高区域商业建筑负荷预测的精确度,提出一种基于用电行为模式的区域商业建筑负荷预测方法。首先,基于均值方差归一化方法对采集到的负荷数据进行标准化处理,通过肘方法确定聚类数目后进行k-Shape聚类,实现区域商业建筑负荷不同用电行为模式的提取;其次,针对大规模商业建筑负荷预测问题,考虑区域内大量商业建筑负荷预测时耗费大量内存资源却难以实现较准确预测问题,提出一种改进的Informer模型,该模型通过聚类算法识别具有相似用电行为模式的商业建筑,并充分考虑智能电表采集的异常负荷数据对模型训练结果的影响,能够良好的解决大规模商业建筑负荷预测精度不高问题;最后,采用加利福尼亚州商业建筑负荷进行实验,实验结果表明所提方法能够有效提高区域商业建筑负荷预测精度。     

Research on wind turbine blade damage based on pre-stressed FBG strain sensors

One of the essential parts of a wind power generator that captures wind energy is the wind turbine blade. The safety of the blades rapidly declines as a wind turbine''s operating period grows. For real-time monitoring, a chip-type pre-stressed fiber Bragg grating (FBG) strain sensor was fabricated. The sensor''s structure was improved using simulation analysis along with optimization. It was discovered through calibration trials that the pre-stressing method expanded the sensor''s range of measurement, guaranteed overall linearity, and prevented the potential hysteresis phenomena during compression. The sensor''s final sensitivity was calculated to be 1.970 pm/με, and its linear fitting coefficient was 0.999. Finally, the sensor was used to monitor the wind turbine blades and the strain change curve of the root of a normally functioning blade is found to be a sine curve, which provides a certain reference value for judging whether the blade is damaged in the future.     

Proximity-Induced Fully Ferromagnetic Order with Eightfold Magnetic Anisotropy in Heavy Transition Metal Oxide CaRuO3

Ferromagnetic materials with a strong spin-orbit coupling (SOC) have attracted much attention in recent years because of their exotic properties and potential applications in energy-efficient spintronics. However, such materials are scarce in nature. Here, a proximity-induced paramagnetic to ferromagnetic transition for the heavy transition metal oxide CaRuO₃ in (001)-(LaMnO₃/CaRuO₃) superlattices is reported. Anomalous Hall effect is observed in the temperature range up to 180 K. Maximal anomalous Hall conductivity and anomalous Hall angle are as large as ∼15 Ω⁻¹ cm⁻¹ and ∼0.93%, respectively, by one to two orders of magnitude larger than those of the typical 3d ferromagnetic oxides such as La_0.67Sr_0.33MnO₃. Density functional theory calculations indicate the existence of avoid band crossings in the electronic band structure of the ferromagnetic CRO layer, which enhances Berry curvature thus strong anomalous Hall effects. Further evidences from polarized neutron reflectometry show that the CaRuO₃ layers are in a fully ferromagnetic state (∼0.8 μ_B/Ru), in sharp contrast to the proximity-induced canted antiferromagnetic state in 5d oxides SrIrO₃ and CaIrO₃ (∼0.1 μ_B/Ir). More than that, the magnetic anisotropy of the (001)-(LaMnO₃/CaRuO₃) superlattices is eightfold symmetric, showing potential applications in the technology of multistate data storage.     

Stubborn state estimation for complex-valued neural networks with mixed time delays: the discrete time case

Neural Computing and Applications - In this paper, the state estimation problem is investigated for a class of discrete-time complex-valued neural networks (CVNNs) with mixed time delays. We...     

An improved Henry gas solubility optimization for optimization tasks

Applied Intelligence - The henry gas solubility optimization (HGSO) is a new nature-inspired algorithm that mimics Henry Gas Solubility to solve global optimization problems. The main changes of...     

Enhanced semantic representation learning for implicit discourse relation classification

Applied Intelligence - Implicit discourse relation classification is one of the most challenging tasks in discourse parsing. Without connectives as linguistic clues, classifying discourse relations...     

Hollow Pd/MOF Nanosphere with Double Shells as Multifunctional Catalyst for Hydrogenation Reaction

A new type of hollow nanostructure featured double metal‐organic frameworks shells with metal nanoparticles (MNPs) is designed and fabricated by the methods of ship in a bottle and bottle around the ship. The nanostructure material, hereinafter denoted as Void@HKUST‐1/Pd@ZIF‐8, is confirmed by the analyses of photograph, transmission electron microscopy, scanning electron microscopy, powder X‐ray diffraction, inductively coupled plasma, and N₂ sorption. It possesses various multifunctionally structural characteristics such as hollow cavity which can improve mass transfer, the adjacent of the inner HKUST‐1 shell to the void which enables the matrix of the shell to host and well disperse MNPs, and an outer ZIF‐8 shell which acts as protective layer against the leaching of MNPs and a sieve to guarantee molecular‐size selectivity. This makes the material eligible candidates for the heterogeneous catalyst. As a proof of concept, the liquid‐phase hydrogenation of olefins with different molecular sizes as a model reaction is employed. It demonstrates the efficient catalytic activity and size‐selectivity of Void@HKUST‐1/Pd@ZIF‐8.