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Renewable Energy Resources (RER), especially wind and solar energy resources, have been growing steadily, and supplying all electric power needs from renewable resources appears more achievable than ever. Solar energy has had the greatest growth rate among renewable energy resources in recent years. The main challenge of employing Photovoltaic (PV) systems is the intermittent nature of solar energy...
Hadoop Map-Reduce has been attracting attention for large-scale image data parallel processing environment for searching and analyzing large-sized images. Hadoop Map-Reduce is a platform for processing large amounts of data, allowing Map-Reduce operations to be processed in parallel to speed up complex tasks. It takes a lot of development time to integrate Hadoop Map-Reduce with various image analysis...
In the past decade, the number of reported security attacks exploiting unchecked input firmware values has been on the rise. To address this concerning trend, this work proposes a novel detection framework, called DOVE, capable of identifying unlikely firmware execution flows, specifically those that may reveal a security vulnerability. The DOVE framework operates by leveraging a symbolic simulation...
CO2 Capture and Storage (CCS) is a way to limit the impact of the power plants on the environment. Using the numerical modeling, the paper analyzes the impact of the post-combustion CCS on the coal-fired Thermal Power Plants (TPP) internal consumptions. The steam turbine power is decreased by the steam flow rate requested by the CO2 capture process. The power consumed by the cooling pumps decreases...
Wide deployment of sensing and actuation capabilities in the electric power grid, along with changing dynamical characteristics, are necessitating analysis of power-system swing dynamics from an input-output perspective. In this article, the input-output properties of the swing dynamics, including the finite and infinite zeros, are characterized from a dynamical-networks perspective. Specifically,...
We propose the use of cloud-computing platforms and virtual network laboratories such as GENI (Global Environment for Network Innovations), together with high-speed software defined networks such as Internet2 to combat various cyber-physical implementation challenges for wide-area control of large power systems using Synchrophasors. Experimental results from a cloud-in-the-loop testbed environment...
Deep learning-based models have recently been widely successful at outperforming traditional approaches in several computer vision applications such as image classification, object recognition and action recognition. However, those models are not naturally designed to learn structural information that can be important to tasks such as human pose estimation and structured semantic interpretation of...
Random graph generation techniques provide an invaluable tool for studying graph related concepts. Unfortunately, traditional random graph models tend to produce artificial representations of real-world phenomenon. Manually developing customized random graph models for every application would require an unreasonable amount of time and effort. In this work, a platform is developed to automate the production...
Growing interest in modeling large, complexnetworks has spurred significant research into generative graphmodels. Kronecker-style models (e.g. SKG and R-MAT) are oftenused due to their scalability and ability to mimic key propertiesof real-world networks. Although a few papers theoreticallyestablish these models' behavior for specific parameters, manyclaims used to justify their use are supported...
This paper introduces a unified constraint-based test case generator for white-box method-level unit testing. The derivation of a suite of test cases can be defined as a constraint satisfaction problem. Each test case consists of a test input and an expected output. The program is automatically transformed into a constraint model called constraint logic graph. The constraint logic graph is a succinct...
The increasing adoption of Big Data analytics has led to a high demand for efficient technologies in order to manage and process large datasets. Popular MapReduce frameworks such as Hadoop are being replaced by emerging ones like Spark or Flink, which improve both the programming APIs and performance. However, few works have focused on comparing these frameworks. This paper addresses this issue by...
Queuing systems of any domain oftentimes exhibit correlated arrivals that considerably influence system behavior. Unfortunately, the vast majority of simulation modeling applications and programming languages do not provide the means to properly model the corresponding input processes. In order to obtain valid models, there is a substantial need for tools capable of modeling autocorrelated input processes...
DNA computing is based on biochemical reactions of DNA molecules. It may give incorrect computations. So, to make the biochemical reactions more accurate good DNA Sequences are needed. DNA Sequence design involves with a number of conflicting design criteria. We formulate the DNA Sequence design as a multi-objective optimization problem and solve it by implementing an algorithm without using any existing...
Hybrid dynamical models are a powerful tool for describing the behaviour of many industrial processes and physical phenomena in which logical (discrete) and analog (continuous) dynamics exist and interact. Black-box identification of hybrid models from input/output observations and no information on the operating mode of the system is a challenging problem, as both the logical and the continuous dynamics...
Irradiance transitions caused by overpassing cloud shadows can cause significant fluctuations in the output power of photovoltaic (PV) systems. With fast growth of PV power production, there is a growing potential of PV output power variability having a negative effect on the power quality and reliability in the grid. This issue is of special importance locally and in small grids with high PV penetration...
This paper proposes a Quasi-Monte Carlo (QMC) simulation based multi-objective economic dispatch, which aims to reduce the fuel cost and emission of the grid simultaneously. During the simulation, QMC models the stochastic behaviours of wind speed and distributed loads with low-discrepancy sequences. In comparison with conventional Monte Carlo (MC) simulation, the computational complexity of QMC is...
The inclusion and modeling of uncertainty in conventional load flow is required with the enhancement in the penetration of intermittent generation. As a result, the multi-modality is there in output distribution functions. In this paper, a probabilistic load flow method is used with two wind generator models with multimodal loadings and a spline based reconstruction technique is introduced for the...
More electric aircraft (MEA) include higher power ratings and more power electronics than conventional aircraft. With electrification comes increased multi-physical interaction between power systems, especially in electrical and thermal domains. It is desirable to develop an accurate and fast systemlevel model that captures the dynamics of multiple energy domains over the course of candidate mission...
The high voltage DC (HVDC) parallel electric power system (EPS) is one of the most promising structures for the More Electric Air-craft (MEA), providing higher performance with less weight and less energy loss. The structure of a typical HVDC parallel EPS is illustrated in this paper. The method to share the load current among the generators in EPS is the key to optimize the performance. An “average...
In this paper, we propose a computation technique to compute the power generation performance of a hub dynamo, which is installed in a bicycle. The output power of the hub dynamo is small and it is difficult to accurately predict the power generation performance using 3-D finite element analysis. First, the output voltage of the hub dynamo is computed and is compared with the measured one. Then, the...
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