108,045 research outputs found
Modeling and Control of Power Electronics Interfaced Load for Transmission Power Network Analysis
The penetration level of power electronics (PE) interfaced loads has been gradually increasing in recent years. It is beneficial to equip the electric load with a PE interface since it allows for more advanced control of the load performance. Furthermore, the increasing penetration of PE interfaced loads will bring both challenges and opportunities to power network resilience and reliability.
However, the lack of modeling and control design for PE interfaced load units in the transmission-level power network analysis, especially for these high-penetrated high-power-rating load applications, limits the accuracy of evaluating the dynamic performance and stability status of the power network. Additionally, the complex configuration and high bandwidth dynamic performance of the PE interfaced load computationally prohibit the model development in transient stability (TS) simulation programs.
Therefore, the dynamic PE interfaced load model can be characterized considering the following aspects: 1) Utilize the real-time experimental platform to represent the PE load dynamic performance since the power testbed can reflect the power grid operation with more robustness. 2) Adapt the simplified PE-based model to TS simulation tools, which focus on grid electromechanical transients and oscillations between 0.1 and 3 Hz.
Research of the PE interfaced load towards its modeling and control design in different simulation environments and the flexible contribution to the grid operation has been conducted. First, the variable speed drive (VSD) based motor load is studied as a typical PE interfaced load, which can actively interact with power grid operation. The model of VSD load is introduced and applied to the power emulator for the multi-converter-based hardware testbed (HTB) in the Center of Ultra-wide-area Resilient Electric Energy Transmission Network (CURENT). Second, the aggregated performance of multiple VSD load units with grid frequency support function is characterized. Third, the fast electric vehicle (EV) charging unit is studied as a typical PE interfaced load with high power consumption. The generic model of EV charger load is developed based on the detailed switching model. The accuracy of the proposed EV charger load TS model has been verified by comparing it to simulation results of the equivalent electromagnetic (EMT) model
PaPaS: A Portable, Lightweight, and Generic Framework for Parallel Parameter Studies
The current landscape of scientific research is widely based on modeling and
simulation, typically with complexity in the simulation's flow of execution and
parameterization properties. Execution flows are not necessarily
straightforward since they may need multiple processing tasks and iterations.
Furthermore, parameter and performance studies are common approaches used to
characterize a simulation, often requiring traversal of a large parameter
space. High-performance computers offer practical resources at the expense of
users handling the setup, submission, and management of jobs. This work
presents the design of PaPaS, a portable, lightweight, and generic workflow
framework for conducting parallel parameter and performance studies. Workflows
are defined using parameter files based on keyword-value pairs syntax, thus
removing from the user the overhead of creating complex scripts to manage the
workflow. A parameter set consists of any combination of environment variables,
files, partial file contents, and command line arguments. PaPaS is being
developed in Python 3 with support for distributed parallelization using SSH,
batch systems, and C++ MPI. The PaPaS framework will run as user processes, and
can be used in single/multi-node and multi-tenant computing systems. An example
simulation using the BehaviorSpace tool from NetLogo and a matrix multiply
using OpenMP are presented as parameter and performance studies, respectively.
The results demonstrate that the PaPaS framework offers a simple method for
defining and managing parameter studies, while increasing resource utilization.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced
Research Computing, July 22--26, 2018, Pittsburgh, PA, US
Using fast and accurate simulation to explore hardware/software trade-offs in the multi-core era
Writing well-performing parallel programs is challenging in the multi-core processor era. In addition to achieving good per-thread performance, which in itself is a balancing act between instruction-level parallelism, pipeline effects and good memory performance, multi-threaded programs complicate matters even further. These programs require synchronization, and are affected by the interactions between threads through sharing of both processor resources and the cache hierarchy.
At the Intel Exascience Lab, we are developing an architectural simulator called Sniper for simulating future exascale-era multi-core processors. Its goal is twofold: Sniper should assist hardware designers to make design decisions, while simultaneously providing software designers with a tool to gain insight into the behavior of their algorithms and allow for optimization. By taking architectural features into account, our simulator can provide more insight into parallel programs than what can be obtained from existing performance analysis tools. This unique combination of hardware simulator and software performance analysis tool makes Sniper a useful tool for a simultaneous exploration of the hardware and software design space for future high-performance multi-core systems
Development of the adjoint of GEOS-Chem
We present the adjoint of the global chemical transport model GEOS-Chem, focusing on the chemical and thermodynamic relationships between sulfate β ammonium β nitrate aerosols and their gas-phase precursors. The adjoint model is constructed from a combination of manually and automatically derived discrete adjoint algorithms and numerical solutions to continuous adjoint equations. Explicit inclusion of the processes that govern secondary formation of inorganic aerosol is shown to afford efficient calculation of model sensitivities such as the dependence of sulfate and nitrate aerosol concentrations on emissions of SOx, NOx, and NH3. The adjoint model is extensively validated by comparing adjoint to finite difference sensitivities, which are shown to agree within acceptable tolerances; most sets of comparisons have a nearly 1:1 correlation and R2>0.9. We explore the robustness of these results, noting how insufficient observations or nonlinearities in the advection routine can degrade the adjoint model performance. The potential for inverse modeling using the adjoint of GEOS-Chem is assessed in a data assimilation framework through a series of tests using simulated observations, demonstrating the feasibility of exploiting gas- and aerosol-phase measurements for optimizing emission inventories of aerosol precursors
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of Californiaβs California Institute for Energy and the Environment, from 2003-2014
Building an Expert System for Evaluation of Commercial Cloud Services
Commercial Cloud services have been increasingly supplied to customers in
industry. To facilitate customers' decision makings like cost-benefit analysis
or Cloud provider selection, evaluation of those Cloud services are becoming
more and more crucial. However, compared with evaluation of traditional
computing systems, more challenges will inevitably appear when evaluating
rapidly-changing and user-uncontrollable commercial Cloud services. This paper
proposes an expert system for Cloud evaluation that addresses emerging
evaluation challenges in the context of Cloud Computing. Based on the knowledge
and data accumulated by exploring the existing evaluation work, this expert
system has been conceptually validated to be able to give suggestions and
guidelines for implementing new evaluation experiments. As such, users can
conveniently obtain evaluation experiences by using this expert system, which
is essentially able to make existing efforts in Cloud services evaluation
reusable and sustainable.Comment: 8 page, Proceedings of the 2012 International Conference on Cloud and
Service Computing (CSC 2012), pp. 168-175, Shanghai, China, November 22-24,
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