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Full-Text Articles in Engineering

Investigation Of Variable Switching Frequency In Finite Control Set Model Predictive Control On Grid-Connected Inverters, Luocheng Wang, Tiefu Zhao, Jiangbiao He Jun 2021

Investigation Of Variable Switching Frequency In Finite Control Set Model Predictive Control On Grid-Connected Inverters, Luocheng Wang, Tiefu Zhao, Jiangbiao He

Electrical and Computer Engineering Faculty Publications

Finite control set model predictive control (FCS-MPC) has been widely studied and applied to the power converters and motor drives. It provides the power electronics system with fast dynamic response, nonlinear system formulation, and flexible objectives and constraints integration. However, its variable switching frequency feature also induces severe concerns on the power loss, the thermal profile, and the filter design. Stemming from these concerns, this article investigates the variable switching frequency characteristics of FCS-MPC on the grid-connected inverters. An intuitive relationship between the switching frequency and the magnitude of the converter output voltage is proposed through the geometry analysis, where …


A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin Jan 2021

A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

Multiple instance learning (MIL) aims to classify objects with complex structures and covers a wide range of real-world data mining applications. In MIL, objects are represented by a bag of instances instead of a single instance, and class labels are provided only for the bags. Some of the earlier MIL methods focus on solving MIL problem under the standard MIL assumption, which requires at least one positive instance in positive bags and all remaining instances are negative. This study proposes a linear programming framework to learn instance level contributions to bag label without emposing the standart assumption. Each instance of …


Optimal Coordination Of Directional Overcurrent Relay Based On Combination Ofimproved Particle Swarm Optimization And Linear Programming Consideringmultiple Characteristics Curve, Suzana Pil Ramli, Hazlie Mokhlis, Wei Ru Wong, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor, Muhamad Hatta Hussain Jan 2021

Optimal Coordination Of Directional Overcurrent Relay Based On Combination Ofimproved Particle Swarm Optimization And Linear Programming Consideringmultiple Characteristics Curve, Suzana Pil Ramli, Hazlie Mokhlis, Wei Ru Wong, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor, Muhamad Hatta Hussain

Turkish Journal of Electrical Engineering and Computer Sciences

Optimal coordination of directional over-current relays (DOCRs) is a crucial task in ensuring the security and reliability of power system network. In this paper, a hybridization of an improved particle swarm optimization and linear programming (IPSO-LP) is proposed to solve DOCRs coordination problem. The considered decision variables in the optimization are plug setting current, time multiplier setting, type of relay, and type of curve. By considering these parameters in the optimization, the best relay operating time can be determined. Furthermore, the proposed technique also considered the continuous values of pick-up current setting (PSC) and time setting multiplier (TMS). Test on …


A Random Subspace Based Conic Functions Ensemble Classifier, Emre Çi̇men Jan 2020

A Random Subspace Based Conic Functions Ensemble Classifier, Emre Çi̇men

Turkish Journal of Electrical Engineering and Computer Sciences

Classifiers overfit when the data dimensionality ratio to the number of samples is high in a dataset. This problem makes a classification model unreliable. When the overfitting problem occurs, one can achieve high accuracy in the training; however, test accuracy occurs significantly less than training accuracy. The random subspace method is a practical approach to overcome the overfitting problem. In random subspace methods, the classification algorithm selects a random subset of the features and trains a classifier function trained with the selected features. The classification algorithm repeats the process multiple times, and eventually obtains an ensemble of classifier functions. Conic …


Coordinated Charging Of Electric Vehicles Including Customer Options For Slow Orfast Charging, Swapna Ganapaneni, Srinivasa Varma Pinni Jan 2020

Coordinated Charging Of Electric Vehicles Including Customer Options For Slow Orfast Charging, Swapna Ganapaneni, Srinivasa Varma Pinni

Turkish Journal of Electrical Engineering and Computer Sciences

Transportation system electrification in the world decreases the gasoline consumption that leads to increase in usage of number of plug in electric vehicles (PEVs). PEV is a bidirectional resource which, while playing the role of a resource, poses challenges in its management. These vehicles are to be charged at a residential standard outlet or in a corporate car charging station. This paper mainly aims to maximize the benefits of a customer who comes to a charging station for charging their vehicle. An incentive-based cost mechanism is introduced to optimally schedule the vehicles; this mechanism minimizes the overall charging cost, considers …


Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla Aug 2018

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The …


Optimization Of Electricity Generation Schemes In The Java-Bali Grid System With Co2 Reduction Consideration, Farizal Farizal, Wenty Eka Septia, Amar Rachman, Nasruddin Nasruddin, Teuku Meurah Indra Mahlia Aug 2016

Optimization Of Electricity Generation Schemes In The Java-Bali Grid System With Co2 Reduction Consideration, Farizal Farizal, Wenty Eka Septia, Amar Rachman, Nasruddin Nasruddin, Teuku Meurah Indra Mahlia

Makara Journal of Technology

This research considers the problem of reducing CO2 emissions from the Java-Bali power grid system that consists of a variety of power-generating plants: coal-fired, natural gas, oil, and renewable energy (PV, geothermal, hydroelectric, wind, and landfill gas). The problem is formulated as linear programming and solved using LINGO 10. The model was developed for a nation to meet a specified CO2 emission target. Two carbon dioxide mitigation options are considered in this study, i.e. fuel balancing and fuel switching. In order to reduce the CO2 emissions by 26% in 2021, State Electric Supply Company (PLN) has to generate up to …


The Impact Of Disabling Suspicious Node Communications On Network Lifetime In Wireless Ad Hoc Sensor Networks, Zeydi̇n Pala, Ni̇hat İnanç Jan 2016

The Impact Of Disabling Suspicious Node Communications On Network Lifetime In Wireless Ad Hoc Sensor Networks, Zeydi̇n Pala, Ni̇hat İnanç

Turkish Journal of Electrical Engineering and Computer Sciences

In wireless sensor networks (WSNs), the data observed by different nodes must be relayed safely to the base station over intermediate nodes. In the network environment, some sensor nodes can act suspiciously when they enter someone else's control or due to other equipment failure. Data packets that are sent through suspicious nodes may be randomly dropped or may be not delivered as desired. In this paper, we investigate the impact of disabling suspicious nodes communications on network lifetime through a linear programming framework. We build a mathematical programming framework and perform comprehensive numerical analysis. Our results show that the decrease …


Java Computer Animation For Effective Learning Of The Cholesky Algorithm With Transportation Engineering Applications, Ivan Makohon, Duc T. Nguyen, Mecit Cetin Jan 2016

Java Computer Animation For Effective Learning Of The Cholesky Algorithm With Transportation Engineering Applications, Ivan Makohon, Duc T. Nguyen, Mecit Cetin

Civil & Environmental Engineering Faculty Publications

In this paper, the well-known Cholesky Algorithm (for solving simultaneous linear equations, or SLE) is re-visited, with the ultimate goal of developing a simple, user-friendly, attractive, and useful Java Visualization and Animation Graphical User Inter-face (GUI) software as an additional teaching tool for students to learn the Cholesky factorization in a step-by-step fashion with computer voice and animation. A demo video of the Cholesky Decomposition (or factorization) animation and result can be viewed online from the website: http://www.lions.odu.edu/~imako001/cholesky/demo/index.html. The software tool developed from this work can be used for both students and their instructors not only to master this technical …


Effects Of Mica2-Based Discrete Energy Levels On The Lifetime Of Cooperation Neighbor Sensor Networks, Zeydi̇n Pala Jan 2016

Effects Of Mica2-Based Discrete Energy Levels On The Lifetime Of Cooperation Neighbor Sensor Networks, Zeydi̇n Pala

Turkish Journal of Electrical Engineering and Computer Sciences

using Mica2 mote discrete power levels on neighbor sensor network lifetime. We built a linear programming framework to qualify the cooperation of sensor networks using a discrete energy model in comparison to noncooperating networks. Our results showed that a wireless sensor neighbor network that uses a discrete radio model can be more energy efficient than a network that uses a nondiscrete energy model.


Design Of Non-Uniform Linear Array Via Linear Programming And Particle Swarm Optimization And Studies On Phased Array Calibration, Hua Bai Nov 2014

Design Of Non-Uniform Linear Array Via Linear Programming And Particle Swarm Optimization And Studies On Phased Array Calibration, Hua Bai

Masters Theses

For a linear array, the excitation coefficients of each element and its geometry play an important role, because they will determine the radiation pattern of the given array. Side Lobe Level (SLL) is one of the key parameters to evaluate the radiation pattern of the array. Generally speaking, we desire SLL to be as low as possible. For the linear array with uniform spacing, there are some classic methods to calculate the excitation coefficients to make the radiation pattern satisfy the given requirements. For the linear array with non-uniform spacing, linear programming and particle swarm optimization are proposed to calculate …


Composite Power System Adequacy Assessment Based On Postoptimal Analysis, Amir Safdarian, Mahmood Fotuhi-Firuzabad, Farrokh Aminifar Jan 2013

Composite Power System Adequacy Assessment Based On Postoptimal Analysis, Amir Safdarian, Mahmood Fotuhi-Firuzabad, Farrokh Aminifar

Turkish Journal of Electrical Engineering and Computer Sciences

The modeling and evaluation of enormous numbers of contingencies are the most challenging impediments associated with composite power system adequacy assessment, particularly for large-scale power systems. Optimal power flow (OPF) solution, as a widely common approach, is normally employed to model and analyze each individual contingency as an independent problem. However, mathematical representations associated with diverse states are slightly different in one or a few generating units, line outages, or trivial load variations. This inherent attribute brings a promising idea to speed up the contingency evaluation procedure. In this paper, postoptimal analysis (POA), as a well-recognized technique to attack a …


Fast Thermal Generation Rescheduling, F. Eugenio Villaseca, B. Fardanesh Aug 2012

Fast Thermal Generation Rescheduling, F. Eugenio Villaseca, B. Fardanesh

F. Eugenio Villaseca

A new dynamic programming algorithm for fast rescheduling thermal generation is presented. The savings in computational times are brought about by the introduction of two new techniques: the variable truncation dynamic programming and the limitation of the solution space to be searched. Several examples on a 20 machine system are used to illustrate the application of the algorithm and to show that optimal solutions are obtained at significantly reduced computational times.


Disaggregating Time Series Data For Energy Consumption By Aggregate And Individual Customer, Steven Vitullo Oct 2011

Disaggregating Time Series Data For Energy Consumption By Aggregate And Individual Customer, Steven Vitullo

Dissertations (1934 -)

This dissertation generalizes the problem of disaggregating time series data and describes the disaggregation problem as a mathematical inverse problem that breaks up aggregated (measured) time series data that is accumulated over an interval and estimates its component parts.

We describe five different algorithms for disaggregating time series data: the Naive, Time Series Reconstruction (TSR), Piecewise Linear Optimization (PLO), Time Series Reconstruction with Resampling (RS), and Interpolation (INT). The TSR uses least squares and domain knowledge of underlying correlated variables to generate underlying estimates and handles arbitrarily aggregated time steps and non-uniformly aggregated time steps. The PLO performs an adjustment …


Minimization Of Load Shedding By Sequential Use Of Linear Programming And Particle Swarm Optimization, Mehrdad Tarafdar Hagh, Sadjad Galvani Jan 2011

Minimization Of Load Shedding By Sequential Use Of Linear Programming And Particle Swarm Optimization, Mehrdad Tarafdar Hagh, Sadjad Galvani

Turkish Journal of Electrical Engineering and Computer Sciences

Minimization of load shedding during contingency conditions is solved as an optimization problem. As a new topic, instead of local load shedding, total load shedding of a large power system is considered. Power generation rescheduling is considered to minimize the load shedding, as well. Different importance factors for buses are also considered. The linear programming method (LP) is used to solve this problem in a short period of time without considering some power system constraints. Particle swarm optimization (PSO) is also used to solve the problem by considering all power system constraints, but with a longer solving time. Finally, a …


A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith May 2009

A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith

Jennifer A. Smith

A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …


A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith Jul 2006

A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith

Electrical and Computer Engineering Faculty Publications and Presentations

A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …


Combining Quality Of Service And Topology Control In Directional Hybrid Wireless Networks, Michael C. Erwin Mar 2006

Combining Quality Of Service And Topology Control In Directional Hybrid Wireless Networks, Michael C. Erwin

Theses and Dissertations

Recent advancements in information and communications technology are changing the information environment in both quantitative and qualitative measures. The developments in directional wireless capabilities necessitate the ability to model these new capabilities, especially in dynamic environments typical of military combat operations. This thesis establishes a foundation for the definition and consideration of the unique network characteristics and requirements introduced by this novel instance of the Network Design Problem (NDP). Developed are a Mixed-Integer Linear Program (MILP) formulation and two heuristic strategies for solving the NDP. A third solution strategy using the MILP formulation with a degree-constrained Minimum Spanning Tree starting …


Fast Thermal Generation Rescheduling, F. Eugenio Villaseca, B. Fardanesh Feb 1987

Fast Thermal Generation Rescheduling, F. Eugenio Villaseca, B. Fardanesh

Electrical and Computer Engineering Faculty Publications

A new dynamic programming algorithm for fast rescheduling thermal generation is presented. The savings in computational times are brought about by the introduction of two new techniques: the variable truncation dynamic programming and the limitation of the solution space to be searched. Several examples on a 20 machine system are used to illustrate the application of the algorithm and to show that optimal solutions are obtained at significantly reduced computational times.