Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 15 of 15

Full-Text Articles in Engineering

Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick Jan 2023

Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Publications and Presentations

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …


Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick Dec 2022

Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Datasets

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …


Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa Dec 2021

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …


Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena Jan 2021

Area-Delay Efficient Radix-4 8×8 Booth Multiplier For Dsp Applications, Subodh Singhal, Sujit Patel, Anurag Mahajan, Gaurav Saxena

Turkish Journal of Electrical Engineering and Computer Sciences

Booth multiplier is the key component in portable very large-scale integration (VSLI) systems enabled with signal and image processing applications. The area, delay, and energy are the major constraints in these systems. Therefore, in this paper, a detailed analysis of the state-of-the-art Booth multiplier architecture and its various internal units are presented to find the scope of optimization. Based on the finding of analysis, optimized new binary to 2's complement (B2C), Booth encoder-cum-selector type-1 and type-2, and partial product addition units are proposed. Furthermore, using these optimized units, an efficient parallel radix-4 8×8 Booth multiplier architecture is proposed. The simulation …


Neural Network Model Of Information Fusion For Coal Storage And Kinetic Energy Of Ball Mill, Bai Yan, He Fang Aug 2020

Neural Network Model Of Information Fusion For Coal Storage And Kinetic Energy Of Ball Mill, Bai Yan, He Fang

Journal of System Simulation

Abstract: A dynamic mathematical model of coal pulverizing system was analyzed. Simulation experiments on mill operation process were conducted by PFC3D software platform based on discrete element method. The associated data between different coal quality, coal storage and balls' motion were obtained under certain quantitative optimized operating parameters configuration. Neural network model of information fusion for coal storage and kinetic energy of ball mill was established by using an adaptive combination learning algorithm. Coal storage in mill cylinder was predicted from the energy point of view. The results indicate that there is a close relationship between coal storage, pulverizing efficiency …


Data Management Of Data Processing Framework In Green Data Center, Zhang Xiao, Gao Yuan, Xiaoliang Wang, Yiyong Ge, Haixiang Yang, Shupeng Wan Jul 2020

Data Management Of Data Processing Framework In Green Data Center, Zhang Xiao, Gao Yuan, Xiaoliang Wang, Yiyong Ge, Haixiang Yang, Shupeng Wan

Journal of System Simulation

Abstract: Using renewable energy in data center is an environment-friendly way to solve the problem of high energy consumption of data center. Since renewable energy is variable, delaying the jobs which has no strict deadline i a widely used strategy to maximize the usage of renewable energy. Meanwhile, turning the idle servers off can further reduce energy consumption. If the data required by the jobs to be processed are unavailable, some servers in sleep state need to be reactivated to guarantee that the data required by the jobs are available. Such operation may lead to energy waste due to the …


Multi-Objective Dynamic Programming Algorithm Of Energy-Efficient Scheduling For Tow-Train, Xinyan Zhang, Yuqing Zhou Apr 2020

Multi-Objective Dynamic Programming Algorithm Of Energy-Efficient Scheduling For Tow-Train, Xinyan Zhang, Yuqing Zhou

Journal of System Simulation

Abstract: To balance the performance and energy consumption of the mixed-model assembly lines effectively, a multi-objective energy-saving scheduling method for the tow-train is proposed. The energy-saving objective is introduced into the traditional material handling scheduling model for the tow-train and a multi-objective mixed integer programming model is constructed with two objective functions of minimizing the maximum line-side inventory and the total energy consumption. A forwards multi-objective dynamic programming based on the time window and dominance rules is presented to obtain the Pareto solutions: the definition for new states is given to obtain the Markov property, the time window and dominance …


Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee Oct 2019

Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee

Doctoral Dissertations

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT …


Visualization And 3d Printing Of A 3d Solar Tracker Model Using Mayavi And Pov-Ray, Aditya Mehra Aug 2017

Visualization And 3d Printing Of A 3d Solar Tracker Model Using Mayavi And Pov-Ray, Aditya Mehra

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

In this work, we have created a realistic model of a solar tracker using Mayavi: 3D scientific data visualization and plotting in Python, Enthought Canopy:a comprehensive Python analysis environment and Persistence of Vision Ray Tracer, or POV-Ray, a ray tracing program which generates photo-realistic images from a text-based scene description, a model of the solar tracker was also 3D printed.


Design, Application, And Power Performance Analyses Of A Micro Wind Turbine, Hayati̇ Mamur Jan 2015

Design, Application, And Power Performance Analyses Of A Micro Wind Turbine, Hayati̇ Mamur

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, design, implementation, and power performance analyses of a micro wind turbine (MWT) system are presented. An original permanent magnet synchronous generator (PMSG) that reduced cogging torque was employed as a generator in the MWT. A novel blade form offering better performance at low wind speeds was also utilized for the MWT blades. Power performance analyses of the MWT were carried out for different wind regimes by truck testing. Performance coefficient, cut-in, and cut-out of the MWT were determined as 27.7{\%}, 2.7 m/s, and 20 m/s at the end of the truck testing, respectively. Moreover, a new supervisory …


Mechatronics In Electrical Efficiency And Environmental Impact, Sherif Hyseni Nov 2014

Mechatronics In Electrical Efficiency And Environmental Impact, Sherif Hyseni

UBT International Conference

This paper focuses on the mechatronic technology development, and its influent on electrical efficiency with a direct result in cost and environment. Considering the well-known European Union standard “20-20-20” and the possibility and responsibility of Kosovo in this field, the role of energy efficiency has great impact for future directions. This paper refers to a new technology solution for heating that is available on the local market, called “DAIKIN” by analyzing the functionality of this device and its promise to save up to 40% of the heating costs. Implementation of “DAIKIN” technology in state institutions in Prishtina, and also the …


Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber Jul 2013

Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber

Research Collection School Of Computing and Information Systems

This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real …


Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe May 2013

Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe

Research Collection School Of Computing and Information Systems

This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …


Odnawialne Źródła Energii W., Wojciech M. Budzianowski Jan 2010

Odnawialne Źródła Energii W., Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.


Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani Sep 2008

Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the Trust Level Routing (TLR) pro- tocol, an extension of the optimized energy-delay rout- ing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network. TLR is similar to OEDR in that they both are link state routing proto- cols that run in a proactive mode and adopt the concept of multi-point relay (MPR) nodes. However, TLR aims at incorporating trust levels into routing by frequently changing the MPR nodes as well as authenticating the source node and contents of control packets. TLR calcu- lates the link costs based on a composite metric (delay …