594 research outputs found
Graph based Platform for Electricity Market Study, Education and Training
With the further development of deregulated electricity market in many other
countries around the world, a lot of challenges have been identified for market
data management, network topology processing and fast market-clearance
mechanism design. In this paper, a graph computing framework based on
TigerGraph database is proposed to solve a security constrained unit commitment
(SCUC) and security constrained economic dispatch (SCED) problem, with
parallelized graph power flow (PGPF) and innovative LU decomposition
techniques, for electricity market-clearance. It also provides a comprehensive
visualization platform to demonstrate the market clearing results vividly, such
as locational marginal price (LMP), and is able to be utilized for electricity
market operators' education and training purpose.Comment: To be published (Accepted) in: Proceedings of the Power and Energy
Society General Meeting (PESGM), Portland, OR, 201
Power Flow Analysis Using Graph based Combination of Iterative Methods and Vertex Contraction Approach
Compared with relational database (RDB), graph database (GDB) is a more
intuitive expression of the real world. Each node in the GDB is a both storage
and logic unit. Since it is connected to its neighboring nodes through edges,
and its neighboring information could be easily obtained in one-step graph
traversal. It is able to conduct local computation independently and all nodes
can do their local work in parallel. Then the whole system can be maximally
analyzed and assessed in parallel to largely improve the computation
performance without sacrificing the precision of final results. This paper
firstly introduces graph database, power system graph modeling and potential
graph computing applications in power systems. Two iterative methods based on
graph database and PageRank are presented and their convergence are discussed.
Vertex contraction is proposed to improve the performance by eliminating
zero-impedance branch. A combination of the two iterative methods is proposed
to make use of their advantages. Testing results based on a provincial 1425-bus
system demonstrate that the proposed comprehensive approach is a good candidate
for power flow analysis.Comment: 8 pages, 8 figures, 2018 International Conference on Power System
Technology (POWERCON 2018
Full-Duplex Cellular Networks: It Works!
Full-duplex (FD) communications with bidirectional transmitting and receiving
at the same time and frequency radio resource have long been deemed a promising
way to boost spectrum efficiency, but hindered by the techniques for
self-interference cancellation (SIC). Recent breakthroughs in analog and
digital signal processing yield the feasibility of beyond dB SIC
capability and make it possible for FD communications to demonstrate nearly
doubled spectrum efficiency for point-to-point links. Now it is time to shift
at least partial of our focus to full duplex networking, such as in cellular
networks, since it is not straightforward but demanding novel and more
complicated interference management techniques. Before putting FD networking
into practice, we need to understand that what scenarios FD communications
should be applied in under the current technology maturity, how bad the
performance will be if we do nothing to deal with the newly introduced
interference, and most importantly, how much improvement could be achieved
after applying advanced solutions. This article will shed light on these
questions
Induced radioactivity analysis for the NSRL Linac in China using Monte Carlo simulations and gamma-spectroscopy
The 200-MeV electron linac of the National Synchrotron Radiation Laboratory
(NSRL) located in Hefei is one of the earliest high-energy electron linear
accelerators in China. The electrons are accelerated to 200 MeV by five
acceleration tubes and are collimated by scrapers. The scraper aperture is
smaller than the acceleration tube one, so some electrons hit the materials
when passing through them. These lost electrons cause induced radioactivity
mainly due to bremsstrahlung and photonuclear reaction. This paper describes a
study of induced radioactivity for the NSRL Linac using FLUKA simulations and
gamma-spectroscopy. The measurements showed that electrons were lost mainly at
the scraper. So the induced radioactivity of the NSRL Linac is mainly produced
here. The radionuclide types were simulated using the FLUKA Monte Carlo code
and the results were compared against measurements made with a High Purity
Germanium (HPGe) gamma spectrometer. The NSRL linac had been retired because of
upgrading last year. The removed components were used to study induced
radioactivity. The radionuclides confirmed by the measurement are: Ni,
Mn, Cr, Co, Co, Co, Mn, Co and
Na, the first eight nuclides of which are predicted by FLUKA simulation.
The research will provide the theoretical basis for the similar accelerator
decommissioning plan, and is significant for accelerator structure design,
material selection and radiation protection design.Comment: 6 pages, 5 figures, Submitted to the Chinese Physics
A High-Performance Energy Management System based on Evolving Graph
As the fast growth and large integration of distributed generation, renewable
energy resource, energy storage system and load response, the modern power
system operation becomes much more complicated with increasing uncertainties
and frequent changes. Increased operation risks are introduced to the existing
commercial Energy Management System (EMS), due to its limited computational
capability. In this paper, a high-performance EMS analysis framework based on
the evolving graph is developed. A power grid is first modeled as an evolving
graph and then the power system dynamic analysis applications, like network
topology processing (NTP), state estimation (SE), power flow (PF), and
contingency analysis (CA), are efficiently implemented on the system evolving
graph to build a high-performance EMS analysis framework. Its computation
performance is field tested using a 2749-bus power system in Sichuan, China.
The results illustrate that the proposed EMS remarkably speeds up the
computation performance and reaches the goal of real-time power system
analysis.Comment: 5 pages, 6 figures, 4 tables, accepted by IEEE Transactions on
Circuits and Systems II: Express Brief
No-Reference Color Image Quality Assessment: From Entropy to Perceptual Quality
This paper presents a high-performance general-purpose no-reference (NR)
image quality assessment (IQA) method based on image entropy. The image
features are extracted from two domains. In the spatial domain, the mutual
information between the color channels and the two-dimensional entropy are
calculated. In the frequency domain, the two-dimensional entropy and the mutual
information of the filtered sub-band images are computed as the feature set of
the input color image. Then, with all the extracted features, the support
vector classifier (SVC) for distortion classification and support vector
regression (SVR) are utilized for the quality prediction, to obtain the final
quality assessment score. The proposed method, which we call entropy-based
no-reference image quality assessment (ENIQA), can assess the quality of
different categories of distorted images, and has a low complexity. The
proposed ENIQA method was assessed on the LIVE and TID2013 databases and showed
a superior performance. The experimental results confirmed that the proposed
ENIQA method has a high consistency of objective and subjective assessment on
color images, which indicates the good overall performance and generalization
ability of ENIQA. The source code is available on github
https://github.com/jacob6/ENIQA.Comment: 12 pages, 8 figure
Exploration of Graph Computing in Power System State Estimation
With the increased complexity of power systems due to the integration of
smart grid technologies and renewable energy resources, more frequent changes
have been introduced to system status, and the traditional serial mode of state
estimation algorithm cannot well meet the restrict time-constrained requirement
for the future dynamic power grid, even with advanced computer hardware. To
guarantee the grid reliability and minimize the impacts caused by system status
fluctuations, a fast, even SCADA-rate, state estimator is urgently needed. In
this paper, a graph based power system modeling is firstly explored and a graph
computing based state estimation is proposed to speed up its performance. The
power system is represented by a graph, which is a collection of vertices and
edges, and the measurements are attributes of vertices and edges. Each vertex
can independently implement local computation, like formulations of the
node-based H matrix, gain matrix and righthand-side (RHS) vector, only with the
information on its connected edges and neighboring vertices. Then, by taking
advantages of graph database, these node-based data are conveniently collected
and stored in the compressed sparse row (CSR) format avoiding the complexity
and heaviness introduced by the sparse matrices. With communications and
synchronization, centralized computation of solving the weighted least square
(WLS) state estimation is completed with hierarchical parallel computing. The
proposed strategy is implemented on a graph database platform. The testing
results of IEEE 14-bus, IEEE 118-bus systems and a provincial system in China
verify the accuracy and high-performance of the proposed methodology.Comment: 5 pages, 2 figures, Proc. of 2018 IEEE Power and Energy Society
General Meetin
Graph Computing based Fast Screening in Contingency Analysis
During last decades, contingency analysis has been facing challenges from
significant load demand increase and high penetrations of intermittent
renewable energy, fluctuant responsive loads and non-linear power electronic
interfaces. It requires an advanced approach for high-performance contingency
analysis as a safeguard of the power system operation. In this paper, a
graph-based method is employed for N-1 contingency analysis (CA) fast
screening. At first, bi-directional breadth-first search (BFS) is proposed and
adopted on graph model to detect the potential shedding component in
contingency analysis. It implements hierarchical parallelism of the graph
traverse and speedup its process. Then, the idea of evolving graph is
introduced in this paper to improve computation performance. For each
contingency scenario, N-1 contingency graph quickly derives from system graph
in basic status, and parallelly analyzes each contingency scenario using graph
computing. The efficiency and effectiveness of the proposed approach have been
tested and verified by IEEE 118-bus system and a practical case SC 2645-bus
system.Comment: 6 pages, 9 figures, 6 tables, accepted by IEEE PES ISGT ASIA 201
Simplify Power Flow Calculation Using Terminal Circuit and PMU Measurements
Power flow calculation methods have been developed in decades using power
injections and Newton-Raphson method. The nonlinear characteristics of the
power flow to the bus voltage require Jacobian matrix reformation and
refactorization in each iteration. Power network is composed by resistors,
reactors, and capacitors which is a linear circuit when investigating the node
voltages with the node current injections. To take the advantage of the
linearity, this paper proposed to use terminal circuit model and PMU voltage
phase angle measurements to simplify power flow calculation. When updating
current injections at the righthand side of power flow equations and using PMU
voltage phase angle measurements representing PV buses voltage phase angle, the
Jacobian matrix is constant during the iteration. The simplification reduces
the computational efforts and improves the computation efficiency. The proposed
method is tested on the IEEE 14-bus and IEEE 118-bus standard systems. The
results are validated by traditional power flow solution and the computation
efficiency is demonstrated.Comment: 5 pages, 5 figures, 4 tables, 2019 IEEE Power & Energy Society
General Meetin
Graph Based Power Flow Calculation for Energy Management System
Power flow calculation in EMS is required to accommodate a large and complex
power system. To achieve a faster than real-time calculation, a graph based
power flow calculation is proposed in this paper. Graph database and graph
computing advantages in power system calculations are presented. A linear
solver for power flow application is formulated and decomposed in nodal
parallelism and hierarchical parallelism to fully utilize graph parallel
computing capability. Comparison of the algorithm with traditional sequential
programs shows significant benefits on computation efficiency. Case studies on
practical large-scale systems provide supporting evidence that the new
algorithm is promising for online computing for EMS.Comment: 5 pages, 4 figures, 3 tables, Proc. of 2018 IEEE Power and Energy
Society General Meetin
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