Due to the lack of data caused by limited and uncertain observations, how to classify Resident Space Object (RSO) remains to be a difficult problem. Previous RSO classifications mainly focus on the problem when the "hard data" which are obtained by physical sensors are missing. They make use of features extracted from observation data which center on RSOs themselves only and are still very limited. This paper proposes to use an RSO Ontology named OntoStar to represent hard data and soft data. This representation not only describes RSOs themselves, but also links related objects to RSOs, establishing a more comprehensive and accurate RSO description to support more accurate and robust classifications. OntoStar not only contains mined feature deducting rules to refine the RSO feature information, but also includes a variety of mined RSO recognition rules to classify RSOs based on different sets of features. Experimental results show that RSO classification based on OntoStar can effectively solve the RSO classification problem under limited or uncertain observation conditions.
The effects of different bridging fluorene units on the two-photon absorption (TPA) properties and ultrafast response of organic conjugated oligomers were investigated for three star-shaped oligomers named TFT-1, TFT-2 and TFT-3. These three oligomers are composed of the same central core 1,3,5-triazine, with three arms that consist of specific numbers of bridging fluorene groups and with triphenylamine as electron-donating group at the terminal end of each arm. The studies on these oligomers were carried out by using two-photon excited fluorescence (TPF), degenerate pump–probe techniques, transient absorption spectroscopy and time-resolved photoluminescence (TRPL) methods. The TPA cross-sections were determined to be 1509 GM, 1260 GM and 789 GM for TFT-1, TFT-2 and TFT-3, respectively, decreasing with the increase of bridging fluorene number. Ultrafast dynamics results show that there is a fast intramolecular charge transfer (ICT) formation time of about several ps and a relatively long decay process of the ICT state. The formation time of ICT was found to increase from TFT-1 (1.9 ps), to TFT-2 (3.0 ps) and TFT-3 (6.3 ps), with the increased number of the fluorene bridge, which may explain the action of fluorene bridge on the electron transmission properties, the ICT properties and the TPA behavior.
Multi-terminal VSC-HVDC (MTDC) is considered to be a attractive option for integrating wind energy from large-scale offshore wind farms. This paper proposes a distributionally robust economic dispatch model with considering the operation of MTDC. The power output of a wind farm is a random variable and assumed to follow an unknown probability distribution. The proposed model aims to seek the optimal economic dispatch decision under the worst-case probability distribution. Although the power equations for MTDC are nonlinear, we obtain a linear approximation by linearizing them around the nominal voltage. We propose a method to transform the proposed model to a linear model and it can be solved efficiently.
Big data refers to a collection of data that can not be captured, managed, and processed with conventional software tools within an affordable timeframe.Dissemination and application of big data has led to a series of changes of consumer behavior, which also put forward new requirements for the enterprise's marketing model enterprises.Enterprises should take advantage of the big data, tap the value of data, change marketing concepts and improve business efficiency.
The market clearing tool is critical for the day-ahead electric energy market. In this paper, we propose a chance-constrained market clearing model for the day-ahead electric energy markets in China. To accommodate large-scale renewable energy, we employ chance-constraints to manage risk and set affine policy as the units' control strategy reacting to uncertainties from variable renewable energy plants. A modified 118-bus system is utilized to test the performance of the proposed approach.
Our country has carried out the pilot work of electricity spot market construction since 2017. The electricity spot markets allows short-term trading and generally involves two trading arrangements, the day-ahead market and the balancing market In this paper, we revisit the mechanism of integrated electricity market. With carrying out numerical examples, we make a detailed discussion on bridging day-ahead market and balancing market. Furthermore, under two imbalance settlements, we compare the revenue for producers and payments for consumers from aspects of energy and ancillary services.
The reliable ignition of air mixture is one of the main difficulties in lean combustion. It is generally believed that the improvement on the ignition system lies in enhancing the ignition energy; this paper, on the other hand, reveals, by conducting comparative tests of ignition energy and ionic state when the ignition system works under normal combustion and when the system works under lean combustion, that the energy emitted in such three stages as puncture, electric arc and emitting light of the same ignition system does not show obvious fluctuation under different air mixture conditions. In other words, different air-fuel ratios do not exert great impact on the performance of the ignition system; the increase of ignition energy alone cannot guarantee the rise in ignition reliability in lean combustion. Further analysis demonstrates that in the three stages of electrode ignition, the puncture stage, which accounts for only a small portion of the total energy, has the highest energy conversion rate. Extending the puncture time or accomplishing repeated punctures proves to be an effective way to boost ignition reliability in lean combustion.
The requirement for energy sustainability drives the development of renewable energy technologies and gas-fired power generation. The increasing installation of gas-fired units significantly intensifies the interdependency between the electricity system and natural gas system. The joint scheduling of electricity and natural gas systems has become an attractive option for improving energy efficiency. This paper proposes a robust day-ahead scheduling model for electricity and natural gas system, which minimizes the total cost including fuel cost, spinning reserve cost and cost of operational risk while ensuring the feasibility for all scenarios within the uncertainty set. Different from the conventional robust optimization with predefined uncertainty set, a new approach with risk-averse adjustable uncertainty set is proposed in this paper to mitigate the conservatism. Furthermore, the Wasserstein–Moment metric is applied to construct ambiguity sets for computing operational risk. The proposed scheduling model is solved by the column-and-constraint generation method. The effectiveness of the proposed approach is tested on a 6-bus test system and a 118-bus system.
To reveal the evolution of shear banding flows, one-dimensional nanostructure metallic glass composites have been studied with molecular dynamics. The inherent size determines the initial thickness of shear bands, and the subsequent broadening can be restricted to some extent. The vortex-like flows evoke the atomic motion perpendicular to the shear plane, which accelerates the interatomic diffusion. The reduction of local strain rate causes the flow softening for monolithic Cu-Zr glass, but the participation of Cu-atoms in the shear banding flow gradually leads to the shear hardening for the composites.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)