Re: Computer Analysis Of Power Systems Rar
Hullen Vilius
This course is designed to introduce computational methods used for power grid operation and planning. The course will help students understand the various computational methods that form the basis of major commercial software packages used by grid analysts and operators. Students are expected to have some basic understanding of principles of power system analysis including power system models, power flow calculation, economic dispatch, reliable and stability analysis. The course covers the following computational methods commonly used in power grid operation and planning: Locational Marginal Pricing Schemes, Game Theory, Unconstrained Optimization, Linear Programming, Non-linear Constrained Optimization, and Forecasting Methods.
Students want to pursue a career as a power grid planner or operator or PhD students who are interested in research in the following areas: renewable integration, demand response, energy storage, energy management systems, power system economics, should think of taking the course.
Energy systems research focuses on the generation and management of power in both traditional electrical systems as well as modern applications of renewable energy. Examples include electric vehicles, energy storage, microgrids, power systems automation and optimization, and smart grids. Design problems span everything from individual electric machines to vast interconnected power generation and distribution systems. Students of this area are recruited in all industries related to energy including electrical, nuclear, wind, solar, and hydroelectric power.
E E 200 Undergraduate Research Exploration Seminar (1)
Weekly seminar featuring research primarily from within the Department of Electrical and Computer Engineering. Speakers include senior PhD students and postdocs as well as faculty from within the department. Provides students with an opportunity to connect with the broader research community in electrical and computer engineering. Credit/no-credit only.
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E E 233 Circuit Theory (5)
Electric circuit theory. Analysis of circuits with sinusoidal signals. Phasors, system functions, and complex frequency. Frequency response. Computer analysis of electrical circuits. Power and energy. Two port network theory. Laboratory in basic electrical engineering topics. Prerequisite: E E 215.
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E E 280 Exploring Devices (4)
Overview of modern electronic and photonic devices underlying modern electronic products including smartphones, traffic lights, lasers, solar cells, personal computers, and chargers. Introduction to modeling and principles of physics relevant to the analysis of electrical and optical/photonic devices. Prerequisite: either PHYS 122 or PHYS 142; recommended: either Python programming or Matlab; and Linux. Offered: AWSp.
View course details in MyPlan: E E 280
E E 331 Devices and Circuits I (5)
Physics, characteristics, applications, analysis, and design of circuits using semiconductor diodes and field-effect transistors with an emphasis on large-signal behavior and digital logic circuits. Classroom concepts are reinforced through laboratory experiments and design exercises. Prerequisite: 1.0 in E E 233.
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E E 332 Devices and Circuits II (5)
Characteristics of bipolar transistors, large- and small- signal models for bipolar and field effect transistors, linear circuit applications, including low and high frequency analysis of differential amplifiers, current sources, gain stages and output stages, internal circuitry of op-amps, op-amp configurations, op-amp stability and compensation. Weekly laboratory. Prerequisite: 1.0 in E E 331.
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E E 342 Signals, Systems, and Data II (4)
Review of basic signal processing concepts. Two-sided Laplace and z -transforms and connection to Fourier transforms. Modulation, sampling and the fast Fourier transform. Short-time Fourier transform. Multi-rate signal processing. Applications including inference and machine learning. Computer laboratory. Prerequisite: E E 242.
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E E 351 Energy Systems (5)
Develops understanding of modern energy systems through theory and analysis of the system and its components. Discussions of generation, transmission, and utilization are complemented by environmental and energy resources topics as well as electromechanical conversion, power electronics, electric safety, renewable energy, and electricity blackouts. Prerequisite: a minimum grade of 1.0 in E E 215.
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E E 391 Probability for Information and Communication Engineering (4)
Introduces probabilistic concepts for Electrical and Computer Engineering majors with applications to information/data science, signal processing, and communication systems. Includes accompanying Python labs that apply probabilistic concepts to these application domains. Prerequisite: E E 235 or E E 241; and MATH 126 or MATH 136.
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E E 393 Advanced Technical Communication (4)
Practical skills for day-to-day engineering communication as well as an advanced exploration of how to prepare persuasive documents and presentations for technical and non-technical audiences.
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E E 398 Introduction to Professional Issues (1)
Covers topics of interest to students planning their educational and professional path, including salaries, the value of advanced degrees, societal expectations of engineering professionals, the corporate enterprise, ethical dilemmas, patents and trade secrets, outsourcing, and the global market.
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E E 400 Advanced Topics in Electrical Engineering (1-5, max. 10)
Contemporary topics at the advanced undergraduate elective level. Faculty presents advanced elective topics not included in the established curriculum.
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E E 406 Teaching Engineering (3) DIV
Explores effective and inclusive teaching techniques in engineering and related STEM fields. Includes active and problem-based learning with attention to how racial, ethnicity, gender, and socioeconomic differences affect how students learn and interact with teachers (including faculty and teaching assistants).
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E E 414 Engineering Innovation in Health (3)
Introduces the role of Innovation and engineering in the design of medical devices and healthcare technologies, applicable both to medical practice and healthcare-focused engineering. May serve as the first course in a medically related senior design project sequence. Discusses medical practice, clinical needs finding, FDA regulation, insurance reimbursement, intellectual property, and the medical device design process. Recommended: M E 123 and M E 354. Offered: jointly with M E 414; A.
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E E 417 Modern Wireless Communications (4)
Introduction to wireless networks as an application of basic communication theorems. Examines modulation techniques for digital communications, signal space, optimum receiver design, error performance, error control coding for high reliability, mulitpath fading and its effects, RF link budget analysis, WiFi and Wimax systems. Prerequisite: E E 416
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E E 436 Medical Instrumentation (4)
Introductory course in the application of instrumentation to medicine. Topics include transducers, signal-conditioning amplifiers, electrodes and electrochemistry, ultrasound systems, electrical safety, and the design of clinical electronics. Laboratory included. For upper-division and first-year graduate students preparing for careers in bioengineering - both research and industrial. Prerequisite: E E 332.
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E E 437 Integrated Systems Capstone (5)
Team-based design experience to develop integrated electronic systems by constructing and validating, prototype integrated circuits (IC) and sensors using modern Computer Aided Design (CAD) tools. Systems are simulated using modern semiconductor, MEMs and nanophotonic technologies. Teams define requirements; investigate tradeoffs in performance, cost, power and size; design for both reliability and testability. Prerequisite: E E 331 and E E 473.
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E E 438 Instrumentation Design Project Capstone (5)
Team-based design for developing an electronic instrumentation system and constructing and validating a prototype using modern printed circuit board technology. Teams develop design requirements; investigate tradeoffs for miniaturization, integration, performance, and cost; and consider use cases, failure modes, manufacturability, and testability. Includes extensive laboratory. Prerequisite: either E E 433 or E E 436.
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E E 442 Digital Signals and Filtering (3)
Methods and techniques for digital signal processing. Review of sampling theorems, A/D and D/A converters. Demodulation by quadrature sampling. Z-transform methods, system functions, linear shift-invariant systems, difference equations. Signal flow graphs for digital networks, canonical forms. Design of digital filters, practical considerations, IIR and FIR filters. Digital Fourier transforms and FFT techniques. Prerequisite: a minimum grade of 1.0 in either E E 341 or E E 342.
View course details in MyPlan: E E 442