141 research outputs found
An explicit formula based estimation method for distribution network reliability
An improved explicit estimation algorithm is proposed for reliability estimation of distribution network. Firstly, hierarchical clustering is used to identify and cluster typical feeders based on topology structure. Secondly, the explicit formula of reliability indices under each typical feeder topology is derived by regression analysis, to establish the model for network reliability estimation. Numerical simulations show the suitability of the proposed method in obtaining accurate reliability index for diversified network topology
Consensus disturbance rejection for Lipschitz nonlinear multi-agent systems with input delay: a DOBC approach
In this paper, a new predictor-based consensus disturbance rejection method is proposed for high-order multi agent systems with Lipschitz nonlinearity and input delay. First, a distributed disturbance observer for consensus control is developed for each agent to estimate the disturbance under the delay constraint. Based on the conventional predictor feedback approach, a non-ideal predictor based control scheme is constructed for each agent by utilizing the estimate of the disturbance and the prediction of the relative state information. Then, rigorous analysis is carried out to ensure that the extra terms associated with disturbances and nonlinear functions are properly considered. Sufficient conditions for the consensus of the multi-agent systems with disturbance rejection are derived based on the analysis in the framework of Lyapunov-Krasovskii functionals. A simulation example is included to demonstrate the performance of the proposed control scheme. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.National Natural Science Foundation of China [61673034]SCI(E)ARTICLE1,SI298-31535
Nonlinear magnetotransport shaped by Fermi surface topology and convexity in WTe2
The nature of Fermi surface defines the physical properties of conductors and
many physical phenomena can be traced to its shape. Although the recent
discovery of a current-dependent nonlinear magnetoresistance in spin-polarized
non-magnetic materials has attracted considerable attention in spintronics,
correlations between this phenomenon and the underlying fermiology remain
unexplored. Here, we report the observation of nonlinear magnetoresistance at
room temperature in a semimetal WTe2, with an interesting temperature-driven
inversion. Theoretical calculations reproduce the nonlinear transport
measurements and allow us to attribute the inversion to temperature-induced
changes in Fermi surface convexity. We also report a large anisotropy of
nonlinear magnetoresistance in WTe2, due to its low symmetry of Fermi surfaces.
The good agreement between experiments and theoretical modeling reveals the
critical role of Fermi surface topology and convexity on the nonlinear
magneto-response. These results lay a new path to explore ramifications of
distinct fermiology for nonlinear transport in condensed-matter
Towards a "Swiss Army Knife" for Scalable User-Defined Temporal -Core Analysis
Querying cohesive subgraphs on temporal graphs (e.g., social network, finance
network, etc.) with various conditions has attracted intensive research
interests recently. In this paper, we study a novel Temporal
-Core Query (TXCQ) that extends a fundamental Temporal
-Core Query (TCQ) proposed in our conference paper by optimizing or
constraining an arbitrary metric of -core, such as size,
engagement, interaction frequency, time span, burstiness, periodicity, etc. Our
objective is to address specific TXCQ instances with conditions on different
in a unified algorithm framework that guarantees scalability. For
that, this journal paper proposes a taxonomy of measurement
and achieve our objective using a two-phase framework
while is time-insensitive or time-monotonic. Specifically,
Phase 1 still leverages the query processing algorithm of TCQ to induce all
distinct -cores during a given time range, and meanwhile locates the "time
zones" in which the cores emerge. Then, Phase 2 conducts fast local search and
evaluation in each time zone with respect to the time
insensitivity or monotonicity of . By revealing two
insightful concepts named tightest time interval and loosest time interval that
bound time zones, the redundant core induction and unnecessary
evaluation in a zone can be reduced dramatically. Our experimental results
demonstrate that TXCQ can be addressed as efficiently as TCQ, which achieves
the latest state-of-the-art performance, by using a general algorithm framework
that leaves as a user-defined function
Agent-Based Modeling for Scale Evolution of Plug-In Electric Vehicles and Charging Demand
Scale evolution pattern recognition of plug-in electric vehicles (PEVs) and charging demand modeling are essential for various involved sectors to promote PEV proliferation and integration into power systems. Considering that the market penetration development of PEVs will drive the evolution of charging demand, an integrated dynamic method based on an agent-based modeling technology is proposed in this paper by combining scale evolution model with charging demand model to jointly detect the possible PEVs evolution patterns and long-term charging demand profiles. Heterogeneous consumers presenting different preferences in making vehicle purchase decisions and the interactions with other consumers via social dynamics are taken into consideration in the scale evolution model. After obtain the scale of PEVs by aggregating individual consumer agents purchase behavior, the driving patterns, charging behavior habits, and charging strategies are systematically incorporated into the charging demand model. Case studies demonstrate the feasibility and effectiveness of the proposed methodology by taking an urban area as an example. Furthermore, the factors that affect the market evolution of PEVs and the charging demand are also simulated and analyzed.</p
Two stage Robust Nash Bargaining based Benefit Sharing between Electric and HCNG Distribution Networks Bridged with SOFC
Hydrogen-enriched compressed natural gas (HCNG) networks have potentized
sustainability and efficiency of integrated electricity and natural gas
systems. However, paucity of benefit sharing risks the IENGS's development in
multiple entities and bottlenecks its efficacy. To fill the gap, a robust Nash
bargaining-based benefit sharing mechanism for HCNG-enabled IENGS is proposed
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