221 research outputs found
Measurement-Based Monitoring and Control in Power Systems with High Renewable Penetrations
Power systems are experiencing rapid changes in their generation mixes because of the increasing integration of inverter-based resources (IBRs) and the retirement of traditional generations. This opens opportunities for a cleaner energy outlook but also poses challenges to the safe operation of the power networks. Enhanced monitoring and control based on the increasingly available measurements are essential in assisting stable operation and effective planning for these evolving systems.
First, awareness of the evolving dynamic characteristics is quintessential for secure operation and corrective planning. A quantified monitoring study that keeps track of the inertial response and primary frequency response is conducted on the Eastern Interconnection (EI) for the past decade with field data. Whereas the inertia declined by at least 10%, the primary frequency response experienced an unexpected increase. The findings unveiled in the trending analysis also led to an improved event MW size estimation method, as well as discussions about regional dynamics.
Experiencing a faster and deeper renewable integration, the Continental Europe Synchronous Area (CESA) system has been threatened by more frequent occurrences of inter-area oscillations during light-load high-renewable periods. A measurement-based oscillation damping control scheme is proposed for CESA with reduced reliance on system models. The design, implementation, and hardware-in-the-loop (HIL) testing of the controller are discussed in detail.
Despite the challenges, the increasing presence of IBRs also brings opportunities for fast and efficient controls. Together with synchronized measurement, IBRs have the potential to flexibly complement traditional frequency and voltage control schemes for improved frequency and voltage recovery. The design, implementation, and HIL testing of the measurement-based frequency and voltage control for the New York State Grid are presented.
In addition to the transmission level development, IBRs deployed in distribution networks can also be valuable assets in emergency islanding situations if controlled properly. A power management module is proposed to take advantage of measurements and automatically control the electric boundaries of islanded microgrids for maximized power utilization and improved frequency regulation. The module is designed to be adaptive to arbitrary non-meshed topologies with multiple source locations for increased flexibility, expedited deployment, and reduced cost
QoS-Aware Mobile Service Selection Algorithm
For the problem of mobile service selection, this paper gives a context-aware service selection algorithm based on Genetic Algorithm. In this algorithm, a tree encoding method, a fitness function, and a fitness-better strategy were proposed. The tree encoding mode made Genetic Algorithm support selection of various types of service combinations, for example, sequence composition, concurrence composition, probability composition, and loop composition. According to the encoding method, a fitness function was designed specially. The fitness-better strategy gives the direction of population evolution and avoids the degradation of population fitness. Some experiments analyses show that the provided service selection algorithm can get better service composition
High-order gas-kinetic scheme with TENO class reconstruction for the Euler and Navier-Stokes equations
The high-order gas-kinetic scheme(HGKS) with WENO spatial reconstruction
method has been extensively validated through many numerical experiments,
demonstrating its superior accuracy efficiency, and robustness. Compared with
WENO class schemes, TENO class schemes exhibit significantly improved
robustness, low numerical dissipation and sharp discontinuity capturing. In
this paper, two kinds of fifth-order HGKS with TENO class schemes are designed.
One involves replacing WENO5 scheme with the TENO5 scheme in the conventional
WENO5-GKS. WENO and TENO schemes only provide the non-equilibrium state values
at the cell interface. The slopes of the non-equilibrium state along with the
equilibrium values and slopes, are obtained by additional linear
reconstruction. Another kind of TENO5-D GKS is similar to WENO5-AO GKS.
Following a strong scale-separation procedure, a tailored novel ENO-like
stencil selection strategy is proposed such that the high-order accuracy is
restored in smooth regions by selecting the candidate reconstruction on the
large stencil while the ENO property is enforced near discontinuities by
adopting the candidate reconstruction from smooth small stencils. The such TENO
schemes are TENO-AA and TENO-D scheme. The HGKS scheme based on WENO-AO or
TENO-D reconstruction take advantage of the large stencil to provide point
values and slopes of the non-equilibrium state. By dynamically merging the
reconstructed non-equilibrium slopes, extra reconstruction of the equilibrium
state at the beginning of each time step can be avoided. The simplified schemes
have better robustness and efficiency than the conventional WENO5-GKS or
TENO5-GKS. TENO-D GKS is also as easy to develop as WENO-AO GKS to high-order
finite volume method for unstructured mesh.Comment: arXiv admin note: text overlap with arXiv:2304.05572; text overlap
with arXiv:1905.08489 by other author
A global adaptive velocity space for general discrete velocity framework in predictions of rarefied and multi-scale flows
The rarefied flow and multi-scale flow are crucial for the aerodynamic design
of spacecraft, ultra-low orbital vehicles and plumes. By introducing a discrete
velocity space, the Boltzmann method, such as the discrete velocity method and
unified methods, can capture complex and non-equilibrium velocity distribution
functions (VDFs) and describe flow behaviors exactly. However, the extremely
steep slope and high concentration of the gas VDFs in a local particle velocity
space make it very difficult for the Boltzmann method with structured velocity
space to describe high speed flow. Therefore, the adaptive velocity space (AVS)
is required for the Boltzmann solvers to be practical in complex rarefied flow
and multi-scale flow. This paper makes two improvements to the AVS approach,
which is then incorporated into a general discrete velocity framework, such as
the unified gas-kinetic scheme. Firstly, a global velocity mesh is used to
prevent the interpolation of the VDFs at the physical interface during the
calculation of the microscopic fluxes, maintaining the program's high level of
parallelism. Secondly, rather than utilizing costly interpolation, the VDFs on
a new velocity space were reconstruction using the ``consanguinity"
relationship. In other words, a split child node's VDF is the same as its
parent's VDF, and a merged parent's VDF is the average of its children's VDFs.
Additionally, the discrete deviation of the equilibrium distribution functions
is employed to maintain the proposed method's conservation. Moreover, an
appropriate set of adaptive parameters is established to enhance the automation
of the proposed method. Finally, a number of numerical tests are carried out to
validate the proposed method
Tracking differentiator based back-stepping control for valve-controlled hydraulic actuator system
Back-stepping design method is widely used in high-performance tracking control tasks As is known to all, the controller based on back-stepping design will become complex as the model order increases, which is the so called “explosion of terms” problem. In this paper, a tracking differentiator (TD) based back-stepping controller is proposed to handle the “explosion of terms” problem. Instead of calculating the derivatives of intermediate control variables through tedious analytical expressions, for the proposed method, the tracking differentiator is embedded into each recursive procedure to generate the substitute derivative signal for every intermediate control variable. As a result, the complexity of implementation procedure of back-stepping controller is significantly reduced. The discrepancies between the derivative substitutes and the real derivatives are considered. And the effects on control performances caused by the discrepancies are analyzed. In addition to giving the theoretical results and the stability proofs with Lyapunov methods, the developed controller design method is evaluated through a series of experiments with a hydraulic robot arm position serve system. The control performance of the proposed controller is verified by the experiments results.</p
LEO Satellite-Enabled Grant-Free Random Access with MIMO-OTFS
This paper investigates joint channel estimation and device activity
detection in the LEO satellite-enabled grant-free random access systems with
large differential delay and Doppler shift. In addition, the multiple-input
multiple-output (MIMO) with orthogonal time-frequency space modulation (OTFS)
is utilized to combat the dynamics of the terrestrial-satellite link. To
simplify the computation process, we estimate the channel tensor in parallel
along the delay dimension. Then, the deep learning and expectation-maximization
approach are integrated into the generalized approximate message passing with
cross-correlation--based Gaussian prior to capture the channel sparsity in the
delay-Doppler-angle domain and learn the hyperparameters. Finally, active
devices are detected by computing energy of the estimated channel. Simulation
results demonstrate that the proposed algorithms outperform conventional
methods.Comment: This paper has been accepted for presentation at the IEEE GLOBECOM
2022. arXiv admin note: text overlap with arXiv:2202.1305
Hypersonic wave wall flow based on gas kinetic method
The transition of hypersonic boundary layer can lead to a several-fold
increase in surface heat flux and skin friction for the aircraft, significantly
impacting its flight performance. The corrugated wall, as a passive control
method for boundary layer flow, also serves as a type of wall microstructure,
making its study on the local rarefaction effect of considerable engineering
significance. In this study, we employed the conservative discrete unified gas
dynamic scheme and utilized a domain-wide numerical simulation method.
Initially, we simulated the hypersonic flat plate flow with different depths of
corrugated walls under the conditions of incoming flow Mach number of 6 and
Reynolds number of . Subsequently, we investigated the effects of
corrugated walls, including flat plate corrugated walls and wedge corrugated
walls, under varying Reynolds numbers for an incoming flow Mach number of 6,
and discussed the impact of local rarefaction effect of corrugated walls under
different Reynolds numbers. By using the local Knudsen number as the criterion,
we found that under these conditions, the occurrence of local rarefaction
effect near the corrugated wall due to consecutive failures does not take place
when the incoming Reynolds number reaches or .
However, when the incoming Reynolds number drops to , the local
rarefaction effect near the corrugated wall becomes evident, with the
appearance of non-equilibrium effects in translational and rotational
temperatures of molecules. This phenomenon becomes more pronounced as the
Reynolds number decreases further
P-CSREC: A New Approach for Personalized Cloud Service Recommendation
It is becoming a challenging issue for users to choose a satisfied service to fit their need due to the rapid growing number of cloud services and the vast amount of service type varieties. This paper proposes an effective cloud service recommendation approach, named personalized cloud service recommendation (P-CSREC), based on the characterization of heterogeneous information network, the use of association rule mining, and the modeling and clustering of user interests. First, a similarity measure is defined to improve the average similarity (AvgSim) measure by the inclusion of the subjective evaluation of users’ interests. Based on the improved AvgSim, a new model for measuring the user interest is established. Second, the traditional K-Harmonic Means (KHM) clustering algorithm is improved by means of involving multi meta-paths to avoid the convergence of local optimum. Then, a frequent pattern growth (FP-Growth) association rules algorithm is proposed to address the issue and the limitation of traditional association rule algorithms to offer personalization in recommendation. A new method to define a support value of nodes is developed using the weight of user’s score. In addition, a multi-level FP-Tree is defined based on the multi-level association rules theory to extract the relationship in higher level. Finally, a combined user interest with the improved KHM clustering algorithm and the improved FP-Growth algorithm is provided to improve accuracy of cloud services recommendation to target users. The experimental results demonstrated the effectiveness of the proposed approach in improving the computational efficiency and recommendation accuracy
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