An Approximated Linear Optimal Power Flow Framework for Power System Operation and Planning. WP 2.2: Markets
|
|
|
- Myrtle Malone
- 5 years ago
- Views:
Transcription
1 An Approximated Linear Optimal Power Flow Framework for Power System Operation and Planning WP 2.2: Markets Philipp Fortenbacher
2 Outline Project Overview Linear/ Quadratic Programming Based Optimal Power Flow (LIN-OPF) Conclusion and Outlook Philipp Fortenbacher
3 Outline Project Overview Linear/ Quadratic Programming Based Optimal Power Flow (LIN-OPF) Conclusion and Outlook Philipp Fortenbacher
4 Project Topic Combination of markets From: ENTSOE Project Goals: Secure cooptimization of energy, reserve procurement, capacities Analyse the economic benefit compared to current market structures Philipp Fortenbacher
5 Milestones MS1: Assessment of a centralized and co-optimized Swiss and European market structure MS2: Quantification of the economic potential for benchmark scenarios MS3: Quantitative economic evaluation of the implementation roadmap Philipp Fortenbacher
6 Current Project Status Co-optimization of energy and reserve procurement Nonlinear AC-Optimal Power Flow (OPF) Ramprates introduce intertemporal constraints (multi-period OPF problem) Next MS1 Goals Milestone goal on larger networks Incorporation of storage Extension to Unit Commitment Problem (e.g. generator startup costs) Philipp Fortenbacher
7 Outline Project Overview Linear/ Quadratic Programming Based Optimal Power Flow (LIN-OPF) Conclusion and Outlook Philipp Fortenbacher
8 Optimal Power Flow (OPF) for Power System Operation and Planning OPF can be used to find optimal generator setpoints taking grid constraints into account optimal planning schemes (generation, network, storage, ) Nonlinear multi-period OPF introduces high complexity and cannot consider binary decisions (e.g. startup costs) This requires a tractable OPF formulation considering voltage, and reactive power Semidefinite or second order cone relaxations might still be too complex Need for a linear approximation of the OPF problem in an LP/QP framework Philipp Fortenbacher
9 LIN-OPF Related Work and Contribution Existing work Iterative approaches (Kirschen, Alsac, Olofsson, ) No consideration of network losses (e.g. DC-OPF) Power flow approximation only (Coffrin et al.) Not in the full decision variable domain (e.g. DC-OPF) Contribution Development of Linear/ Quadratic Programming based OPF (LIN- OPF) in the full decision variable domain and losses included Power flow approximation over entire operating area using linear power flow and absolute loss approximations No iterations needed P. Fortenbacher T. Demiray Linear /Quadratic Programming Based Optimal Power Flow using Linear Power Flow and Absolute Loss Approximations To be submitted Philipp Fortenbacher
10 Recasting AC-OPF to LIN-OPF Standard AC-OPF Recast to LIN-OPF in x && f p ( p gen )+ f q ( q gen )@& s.t.&&h(x) 0@&&&g(x)=0. & min x && f p con ( p gen )+ f q con ( q AC power flow equations Linear Power Flow approximation Absolute loss approximation Philipp Fortenbacher
11 Absolute Loss Approximation 2 bus example θ 1 p q v y=g+jb Loss Approximation θ 2 p q v Philipp Fortenbacher
12 LIN-OPF Voltage Magnitude and Angle Errors IEEE118 Testcase Root Mean Square (RMS) Errors Philipp Fortenbacher
13 Optimality and Characteristics Objective value deviation against AC-OPF Approximation not Relaxation No guaruantee for feasible solution in original problem space, but improved (DC-OPF) If solution is not tight, MIP has to be solved Negative LMPs (Negative prices, highly congested systems) Philipp Fortenbacher
14 Outlook Complexity Computation Time for a storage siting problem 800sec 6sec 18 storage devices AC-OPF matpower IP solver LIN-OPF gurobi solver investment horizon (hours) Philipp Fortenbacher
15 Outline Project Overview Linear/ Quadratic Programming Based Optimal Power Flow (LIN-OPF) Conclusion and Outlook Philipp Fortenbacher
16 Conclusion Tractable LP/QP based OPF problem (LIN-OPF) for planning and operation Meshed networks e.g. distribution, transmission and LV grids Optimality, voltage and angle errors are reasonable Complexity reduction with LIN-OPF for multi-period OPF problems Philipp Fortenbacher
17 Next steps within MS1 Journal paper publication Working paper Include LIN-OPF into our reserve allocation framework Extension for tap changing transformers Include storage Unit Commitment problem with generator startup costs (MIP) Extend method to reflect security constraints 2nd year Use framework for larger networks (Swiss and European Grid) Philipp Fortenbacher
18 Thank you for your attention FEN Research Center for Energy Networks Philipp Fortenbacher PhD Postdoctoral Researcher ETH Zürich SOI C1 Sonneggstrasse Zürich Switzerland Phone Fax
Optimal Proxy-Limited Lines for Representing Voltage Constraints in a DC Optimal Powerflow
Optimal Proxy-Limited Lines for Representing Voltage Constraints in a DC Optimal Powerflow by Michael Schlindwein A thesis submitted in fulfillment of the requirements for the degree of Master of Science
Aggregation of Buses for a Network Reduction HyungSeon Oh, Member, IEEE
IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 27, NO. 2, MAY 2012 705 Aggregation of Buses a Network Reduction HyungSeon Oh, Member, IEEE Abstract A simple but precise model would improve the computation efficiency
Study of the Paper Efficient AC Optimal Power Flow and Global Optimizer Solutions. Yuyang Chen
Study of the Paper Efficient AC Optimal Power Flow and Global Optimizer Solutions Yuyang Chen Presentation Agenda Theoretical background Study 0. Background Introduction 1. SDP relaxation 2. D&C method
Javad Lavaei. Department of Electrical Engineering Columbia University
Graph Theoretic Algorithm for Nonlinear Power Optimization Problems Javad Lavaei Department of Electrical Engineering Columbia University Joint work with: Ramtin Madani, Ghazal Fazelnia and Abdulrahman
ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 7, Issue 1, July 2017
Congestion Management in Deregulated Power System Using Market Splitting Based Approach Manish Harchand 1, KanwardeepSingh 2 M.Tech student 1, Associate professor 2 Department of Electrical Engineering,
Multi-Area Power System Security using Polyhedral Transfer Capacities. Dr. Alexander Fuchs (ETH Zürich, Research Center for Energy Networks)
Multi-Area Power System Security using Polyhedral Transfer Capacities Dr. Alexander Fuchs (ETH Zürich, Research Center for Energy Networks) Goals of this presentation How does flexible generation affect
Javad Lavaei. Graph-theoretic Algorithm for Nonlinear Power Optimization Problems. Department of Electrical Engineering Columbia University
Graph-theoretic Algorithm for Nonlinear Power Optimization Problems Javad Lavaei Department of Electrical Engineering Columbia University Joint work with Ramtin Madani, Somayeh Sojoudi, Ghazal Fazelnia
Multi-area Nonlinear State Estimation using Distributed Semidefinite Programming
October 15, 2012 Multi-area Nonlinear State Estimation using Distributed Semidefinite Programming Hao Zhu haozhu@illinois.edu Acknowledgements: Prof. G. B. Giannakis, U of MN Doctoral Dissertation Fellowship
DC Optimal Power Flow Proxy Limits
DC Optimal Power Flow Proxy Limits Bernard C. Lesieutre Univ. of Wisconsin-Madison lesieutre@wisc.edu Michael Schlindwein Univ. of Wisconsin-Madison schlindwein@wisc.edu Edward E. Beglin Navigant Consulting
PowerWorld Tutorial. Yen-Yu Lee The University of Texas at Austin Jan 18, Updated December 26, 2012, by Ross Baldick
PowerWorld Tutorial Yen-Yu Lee The University of Texas at Austin Jan 18, 2010 Updated December 26, 2012, by Ross Baldick 1 Introduction PowerWorld is one of the most popular power system simulation tools.
Smart Grid Application of Optimal Transmission Switching
Smart Grid Application of Optimal Transmission Switching By, Kory W. Hedman, et al.* University of California, Berkeley INFORMS Annual Meeting Washington, DC October 15, 2008 *Dr. Richard P. O Neill (Chief
MIGRATION PROCESS FROM UCTE DEF TO CGMES SECOND EDITION
MIGRATION PROCESS FROM UCTE DEF TO CGMES SECOND EDITION 24 OCTOBER 2016 PT CGM Page 1 of 18 ENTSO-E AISBL Avenue Cortenbergh 100 1000 Brussels Belgium Tel +32 2 741 09 50 Fax +32 2 741 09 51 info@entsoe.eu
Load Conformance Limiter Enhancement
TECHNICAL BULLETIN December 28, 2016 www.caiso.com 250 Outcropping Way, Folsom, CA 95630 916.351.4400 TECHNICAL BULLETIN Revision History Date Version Description Author December 28, 2016 1.0 Draft Proposal
Functions and Families
Unit 3 Functions and Families Name: Date: Hour: Function Transformations Notes PART 1 By the end of this lesson, you will be able to Describe horizontal translations and vertical stretches/shrinks of functions
Performance analysis of FACTS devices in steady state power flow
Performance analysis of FACTS devices in steady state power flow VELAMURI SURESH 1, SREEJITH.S 2 1 Research Scholar, 2 Associate Professor School of Electrical engineering, VIT University Vellore, INDIA
International Journal of Scientific & Engineering Research Volume 4, Issue 2, February ISSN
International Journal of Scientific & Engineering Research Volume 4, Issue, February-1 1 Voltage Stability Enhancement through Static Var Compensator A.S. Siddiqui 1, Tanmoy Deb Jamia Millia Islamia, New
Optimal transmission switching: economic efficiency and market implications
J Regul Econ (2011) 40:111 140 DOI 10.1007/s11149-011-9158-z ORIGINAL ARTICLE Optimal transmission switching: economic efficiency and market implications Kory W. Hedman Shmuel S. Oren Richard P. O Neill
Cyber Security Analysis of State Estimators in Electric Power Systems
Cyber Security Analysis of State Estimators in Electric Power Systems H. Sandberg, G. Dán, A. Teixeira, K. C. Sou, O. Vukovic, K. H. Johansson ACCESS Linnaeus Center KTH Royal Institute of Technology,
Load Flow Analysis. I Objectives
EE342 Electrical Power Lab Experiment PS3 Load Flow Analysis I Objectives To demonstrate load flow concepts. To study system performance under different operating conditions. To experience the real feel
Convex Optimization and Machine Learning
Convex Optimization and Machine Learning Mengliu Zhao Machine Learning Reading Group School of Computing Science Simon Fraser University March 12, 2014 Mengliu Zhao SFU-MLRG March 12, 2014 1 / 25 Introduction
Bilinear Programming
Bilinear Programming Artyom G. Nahapetyan Center for Applied Optimization Industrial and Systems Engineering Department University of Florida Gainesville, Florida 32611-6595 Email address: artyom@ufl.edu
Voltage control in MV and LV grid Distributed automation solution. Sami Repo Tampere University of Technology, Finland Coordinator of IDE4L project
1 Voltage control in MV and LV grid Distributed automation solution Sami Repo Tampere University of Technology, Finland Coordinator of IDE4L project 2 Content IDE4L project Problem of voltage control in
Advanced Use of GAMS Solver Links
Advanced Use of GAMS Solver Links Michael Bussieck, Steven Dirkse, Stefan Vigerske GAMS Development 8th January 2013, ICS Conference, Santa Fe Standard GAMS solve Solve william minimizing cost using mip;
Flexible Transmission in the Smart Grid: Optimal Transmission Switching
Flexible Transmission in the Smart Grid: Optimal Transmission Switching Kory W. Hedman, Shmuel S. Oren, and Richard P. O Neill Abstract There is currently a national push to create a smarter, more flexible
Network Codes, Governance and Regulatory issues for the Transition towards up to 100% RES
6/27/2018 Slide No. 2 Network Codes, Governance and Regulatory issues for the Transition towards up to 100% RES 28th June 2018 Bucharest, Romania Dr. Mihai PAUN Vice-President Romanian Energy Center RESERVE:
Optimal Location and Size of Distributed Energy Resources Using Sensitivity Analysis-Based Approaches
Optimal Location and Size of Distributed Energy Resources Using Sensitivity Analysis-Based Approaches Mohammed Benidris Electrical & Biomedical Engineering University of Nevada, Reno Reno, NV 89557, USA
Agenda. Understanding advanced modeling techniques takes some time and experience No exercises today Ask questions!
Modeling 2 Agenda Understanding advanced modeling techniques takes some time and experience No exercises today Ask questions! Part 1: Overview of selected modeling techniques Background Range constraints
Recursive column generation for the Tactical Berth Allocation Problem
Recursive column generation for the Tactical Berth Allocation Problem Ilaria Vacca 1 Matteo Salani 2 Michel Bierlaire 1 1 Transport and Mobility Laboratory, EPFL, Lausanne, Switzerland 2 IDSIA, Lugano,
Quadratic Equations. Learning Objectives. Quadratic Function 2. where a, b, and c are real numbers and a 0
Quadratic Equations Learning Objectives 1. Graph a quadratic function using transformations. Identify the vertex and axis of symmetry of a quadratic function 3. Graph a quadratic function using its vertex,
MODULAR HUB AND SPOKE 17 NOVEMBER 2017
MODULAR HUB AND SPOKE 17 NOVEMBER 2017 Executive Summary Future North Sea offshore wind farms will increasingly be located further from shore. The longer distances to shore and generally deeper waters
Graph-Theoretic Convexification of Polynomial Optimization Problems: Theory and Applications Javad Lavaei
Graph-Theoretic Convexification of Polynomial Optimization Problems: Theory and Applications Javad Lavaei Department of Electrical Engineering Columbia University 1 Polynomial Optimization Polynomial Optimization:
Lecture 25 Nonlinear Programming. November 9, 2009
Nonlinear Programming November 9, 2009 Outline Nonlinear Programming Another example of NLP problem What makes these problems complex Scalar Function Unconstrained Problem Local and global optima: definition,
SYNCHRONIZED PHASOR MEASUREMENTS FOR STATE ESTIMATION
Électrotechnique et électroénergétique SYNCHRONIZED PHASOR MEASUREMENTS FOR STATE ESTIMATION MIHAI GAVRILAŞ, 1 IONUŢ RUSU, 1 GILDA GAVRILAŞ, 1 OVIDIU IVANOV 1 Key words: State estimation, Phasor measurements,
Microgrids: Building Blocks of the Smart Grid Adaptive Protection Schemes for Microgrids
Enrico Ragaini (ABB Low Voltage Products), Alexandre Oudalov (ABB Corporate Research), ISGT Europe 2012, Berlin Microgrids: Building Blocks of the Smart Grid Adaptive Protection Schemes for Microgrids
Graph each function. State the domain, the vertex (min/max point), the range, the x intercepts, and the axis of symmetry.
HW Worksheet Name: Graph each function. State the domain, the vertex (min/max point), the range, the x intercepts, and the axis of smmetr..) f(x)= x + - - - - x - - - - Vertex: Max or min? Axis of smmetr:.)
Postprint.
http://www.diva-portal.org Postprint This is the accepted version of a paper presented at IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), JUN 10-13, 2015, Rome, ITALY.
Achieving Smarter Grid Operation With On-Line DSA Technology
Achieving Smarter Grid Operation With On-Line DSA Technology Powercon 2014 October 20-22, 2014, Chengdu, China Lei Wang Powertech Labs Inc. 12388 88 th Avenue Surrey, BC, Canada A very simple version of
SystempaK (Digital/File Type) Dual Input Arithmetic Relay Module Model J-SCM 92/97
No.SS2-2320-0950 (Rev. 1) SystempaK (Digital/File Type) Dual Input Arithmetic Relay Module Model J-SCM 92/97 Introduction The Dual Input Arithmetic Relay Module is an advanced arithmetic module that can
Smart Gas Grids. Manuel Sánchez, Ph.D. Team Leader Smart Grids Directorate General for Energy European Commission
Smart Gas Grids Manuel Sánchez, Ph.D. Team Leader Smart Grids Directorate General for Energy European Commission Smart Gas Grids in practice Brussels 1st December 2015 Energy Low carbon economy requires
MATPOWER. A MATLAB Power System Simulation Package. Version 2.0 December 24, User s Manual
MATPOWER A MATLAB Power System Simulation Package Version 2.0 December 24, 1997 User s Manual Ray D. Zimmerman rz10@cornell.edu Deqiang (David) Gan deqiang@ee.cornell.edu 1997 Power Systems Engineering
EU Technology Platform SmartGrids WG2 Network Operations
EU Technology Platform SmartGrids WG2 Network Operations Tahir Kapetanovic Director Electricity, E-Control Member of the SmartGrids AC Chairman of the WG2 tahir.kapetanovic@e-control.at Overview SmartGrids
Logic Synthesis for Energy-Efficient Photonic Integrated Circuits
リレーションシップ ID rid4 のイメージパーツがファイルにありませんでした Logic Synthesis for Energy-Efficient Photonic Integrated Circuits Zheng Zhao, Zheng Wang, Zhoufeng Ying, Shounak Dhar, Ray T. Chen, and David Z. Pan Dept. of Electrical
Cyber Security for Smart Grid Devices
Cyber Security for Smart Grid Devices Annarita Giani Electrical Engineering & Computer Sciences University of California at Berkeley agiani@eecs.berkeley.edu Trustworthy Cyber Infrastructure for the Power
Introduction to Optimization
Introduction to Optimization Second Order Optimization Methods Marc Toussaint U Stuttgart Planned Outline Gradient-based optimization (1st order methods) plain grad., steepest descent, conjugate grad.,
Benders in a nutshell Matteo Fischetti, University of Padova
Benders in a nutshell Matteo Fischetti, University of Padova ODS 2017, Sorrento, September 2017 1 Benders decomposition The original Benders decomposition from the 1960s uses two distinct ingredients for
The Gurobi Optimizer. Bob Bixby
The Gurobi Optimizer Bob Bixby Outline Gurobi Introduction Company Products Benchmarks Gurobi Technology Rethinking MIP MIP as a bag of tricks 8-Jul-11 2010 Gurobi Optimization 2 Gurobi Optimization Incorporated
ACTIVE MAGNETIC BEARINGS AND MOTOR DRIVE TOWARDS INTEGRATION
ACTIVE MAGNETIC BEARINGS AND MOTOR DRIVE TOWARDS INTEGRATION René Larsonneur R&D Mechanics, MECOS Traxler AG, 8404 Winterthur, Switzerland rene.larsonneur@mecos.com Philipp Bühler R&D Electronics, MECOS
Methods to improve computing times in linear energy system optimization models
Methods to improve computing times in linear energy system optimization models Hans Christian Gils, Karl-Kiên Cao, Manuel Wetzel, Felix Cebulla, Kai von Krbek, Benjamin Fuchs, Frieder Borggrefe DLR German
ENTSO-E working to fulfill the 3 rd Package
ENTSO-E working to fulfill the 3 rd Package Regulators Role in Developing Infrastructure, Florence February 7 2012 Geoffrey Feasey, ENTSO-E Corporate Affairs Manager ENTSOE s role in implementing European
Math Models of OR: The Simplex Algorithm: Practical Considerations
Math Models of OR: The Simplex Algorithm: Practical Considerations John E. Mitchell Department of Mathematical Sciences RPI, Troy, NY 12180 USA September 2018 Mitchell Simplex Algorithm: Practical Considerations
Electric Power Systems Research
Electric Power Systems Research 110 (2014) 45 54 Contents lists available at ScienceDirect Electric Power Systems Research j o ur na l ho mepage: www.elsevier.com/locate/epsr Multi-agent control of community
[Telchy, 4(11): November, 2015] ISSN: (I2OR), Publication Impact Factor: 3.785
![[Telchy, 4(11): November, 2015] ISSN: (I2OR), Publication Impact Factor: 3.785](/thumbs/93/113791517.jpg "[Telchy, 4(11): November, 2015] ISSN: (I2OR), Publication Impact Factor: 3.785")
[Telchy, 4(): November, 5] ISSN: 77-9655 (IOR), Publication Impact Factor:.785 IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY INTELLIGENT OPTIMIZATION AND SCHEDULING OF NETWORKED
Optimal Reactive Power Dispatch Using Hybrid Loop-Genetic Based Algorithm
Optimal Reactive Power Dispatch Using Hybrid Loop-Genetic Based Algorithm Md Sajjad Alam Student Department of Electrical Engineering National Institute of Technology, Patna Patna-800005, Bihar, India
ONLINE CLOSED-LOOP OPTIMIZATION OF DISTRIBUTION NETWORKS
ONLINE CLOSED-LOOP OPTIMIZATION OF DISTRIBUTION NETWORKS Werner FEILHAUER Michael HEINE Andreas SCHMIDT PSI AG, EE DE PSI AG, EE DE PSI AG, EE - DE wfeilhauer@psi.de mheine@psi.de aschmidt@psi.de ABSTRACT
European Commission SGTF Expert Group Findings on Interoperability
Search Search for: European Commission SGTF Expert Group Findings on Interoperability Dr.-Ing. Manuel Sánchez Jiménez Team Leader Smart Grids Directorate General for Energy European Commission Energy Smart
Investigating Transformations With DESMOS
MPM D0 Date: Investigating Transformations With DESMOS INVESTIGATION Part A: What if we add a constant to the x in y = x? 1. Use DESMOS to graph the following quadratic functions on the same grid. Graph
Discrete Optimization with Decision Diagrams
Discrete Optimization with Decision Diagrams J. N. Hooker Joint work with David Bergman, André Ciré, Willem van Hoeve Carnegie Mellon University Australian OR Society, May 2014 Goal Find an alternative
Automatic Control & Systems Engineering.
Automatic Control & Systems Engineering. RECEDING-HORIZON CONTROL & OPTIMISATION OF POWER NETWORKS Rinu Ravikumar Vasudeva Panicker August 2013 Supervisor: Dr Paul Trodden A dissertation submitted in partial
Standard INT Dynamic Transfers
A. Introduction 1. Title: Dynamic Transfers 2. Number: INT-004-3 3. Purpose: To ensure Dynamic Schedules and Pseudo-Ties are communicated and accounted for appropriately in congestion management procedures.
Outline. Robust MPC and multiparametric convex programming. A. Bemporad C. Filippi. Motivation: Robust MPC. Multiparametric convex programming
Robust MPC and multiparametric convex programming A. Bemporad C. Filippi D. Muñoz de la Peña CC Meeting Siena /4 September 003 Outline Motivation: Robust MPC Multiparametric convex programming Kothares
Controlling Hybrid Systems
Controlling Hybrid Systems From Theory to Application Manfred Morari M. Baotic, F. Christophersen, T. Geyer, P. Grieder, M. Kvasnica, G. Papafotiou Lessons learned from a decade of Hybrid System Research
TSO-DSO RELATIONS IN THE FUTURE EUROPEAN POWER SYSTEM
TSO-DSO RELATIONS IN THE FUTURE EUROPEAN POWER SYSTEM Carlo SABELLI GO 15 San Francisco April 13 2016 42 TSOs in ENTSO-E the European Network for Transmission System Operators for Electricity 42 TSOs from
Matpower 4.0 User s Manual
Matpower 4.0 User s Manual Ray D. Zimmerman Carlos E. Murillo-Sánchez February 7, 2011 2010, 2011 Power Systems Engineering Research Center (Pserc) All Rights Reserved Contents 1 Introduction 7 1.1 Background................................
Graphing Absolute Value Functions
Graphing Absolute Value Functions To graph an absolute value equation, make an x/y table and plot the points. Graph y = x (Parent graph) x y -2 2-1 1 0 0 1 1 2 2 Do we see a pattern? Desmos activity: 1.
Research Interests Optimization:
Mitchell: Research interests 1 Research Interests Optimization: looking for the best solution from among a number of candidates. Prototypical optimization problem: min f(x) subject to g(x) 0 x X IR n Here,
MATCASC: A tool to analyse cascading line outages in power grids
MATCASC: A tool to analyse cascading line outages in power grids arxiv:308.074v [physics.soc-ph] Aug 203 Yakup Koç Trivik Verma 2 Nuno A. M. Araujo 2 Martijn Warnier Faculty of Technology, Policy and Management,
Ali Abur Northeastern University Department of Electrical and Computer Engineering Boston, MA 02115
Enhanced State t Estimation Ali Abur Northeastern University Department of Electrical and Computer Engineering Boston, MA 02115 GCEP Workshop: Advanced Electricity Infrastructure Frances Arriallaga Alumni
Basic Communication Operations Ananth Grama, Anshul Gupta, George Karypis, and Vipin Kumar
Basic Communication Operations Ananth Grama, Anshul Gupta, George Karypis, and Vipin Kumar To accompany the text ``Introduction to Parallel Computing'', Addison Wesley, 2003 Topic Overview One-to-All Broadcast
Standard INT Dynamic Transfers
Standard INT-004-3.1 Dynamic Transfers A. Introduction 1. Title: Dynamic Transfers 2. Number: INT-004-3.1 3. Purpose: To ensure Dynamic Schedules and Pseudo-Ties are communicated and accounted for appropriately
Robust Optimization in AIMMS
Robust Optimization in AIMMS Peter Nieuwesteeg Senior AIMMS specialist Online webinar July 20, 2010 Paragon Decision Technology Inc 5400 Carillon Point, Kirkland, WA, USA E-mail: info@aimms.com Internet:
Optimal Transmission Switching in Electric Networks for Improved Economic Operations 1
Optimal Transmission Switching in Electric Networs for Improved Economic Operations 1 Emily Bartholomew Fisher 2, Kory W. Hedman 3, Richard P. O Neill 4, Michael C. Ferris 5, and Shmuel S. Oren 6 1. Abstract
Digitalization beyond Smart Metering. SCCER-FURIES meeting 2 Nov. 2017/ Lausanne, Switzerland
FHNW, INSTITUT FÜR AEROSOL- UND SENSORTECHNIK, GRUPPE EL. ENERGIETECHNIK (PROF. SCHULZ) USI, INSTITUTE OF COMPUTATIONAL SCIENCE (PROF. KRAUSE) USI, ADVANCED LEARNING AND RESEARCH INSTITUTE (PROF. MALEK)
LocalSolver 4.0: novelties and benchmarks
LocalSolver 4.0: novelties and benchmarks Thierry Benoist Julien Darlay Bertrand Estellon Frédéric Gardi Romain Megel www.localsolver.com 1/18 LocalSolver 3.1 Solver for combinatorial optimization Simple
Lecture 14. Course wrap up & Smartgrid Architectures. Professor Lars Nordström Dept of Industrial Information & Control systems, KTH
Lecture 14 Course wrap up & Smartgrid Architectures Professor Lars Nordström Dept of Industrial Information & Control systems, KTH larsn@ics.kth.se Course map Outline of the lecture Course Wrap-up - Local
Congestion Management Ensuring Voltage Stability
IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 21, NO. 1, FEBRUARY 2006 357 Congestion Management Ensuring Voltage Stability Antonio J. Conejo, Fellow, IEEE, Federico Milano, Member, IEEE, Raquel García-Bertr,
Feasibility Study on Load Flow and Short Circuit Project
Feasibility Study on Load Flow and Short Circuit Project 101813-01 Prepared by: Transmission Planning Department Cleco Corporation, Inc. 2180 St. Landry Hwy P.O. Box 70 St. Landry, LA 71367 Final November
An Introduction to Network Codes & The Links Between Codes
An Introduction to Network Codes & The Links Between Codes April 2014 About ENTSO-E 41 TSOs from 34 countries 532 million citizens served 828 GW generation 305 Thousand Km of transmission lines Ten-Year
Contingency Modeling Enhancements Prototype Analysis with Production Cases
August 17, 2017 Table of contents 1. Executive summary... 4 2. Purpose... 4 3. Analysis of stressed system scenarios... 5 Methodology... 5 Non-binding scenarios... 6 Binding scenario... 7 Other observations...
Introduction to ANSYS DesignXplorer
Lecture 4 14. 5 Release Introduction to ANSYS DesignXplorer 1 2013 ANSYS, Inc. September 27, 2013 s are functions of different nature where the output parameters are described in terms of the input parameters
8. Solving Stochastic Programs
8. Solving Stochastic Programs Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S.
PowerFactory15. PowerFactory User s Conference and Future Networks Technical Seminar. 5-6 September 2013, Sydney - Australia
PowerFactory15 PowerFactory User s Conference and Future Networks Technical Seminar 5-6 September 2013, Sydney - Australia Flavio Fernández DIgSILENT GmbH, Germany 1 Overview PowerFactory s history Highlights
Fundamentals of Integer Programming
Fundamentals of Integer Programming Di Yuan Department of Information Technology, Uppsala University January 2018 Outline Definition of integer programming Formulating some classical problems with integer
SOLVING THE TASK ASSIGNMENT PROBLEM WITH A VARIABLE NEIGHBORHOOD SEARCH. Jozef Kratica, Aleksandar Savić, Vladimir Filipović, Marija Milanović
Serdica J. Computing 4 (2010), 435 446 SOLVING THE TASK ASSIGNMENT PROBLEM WITH A VARIABLE NEIGHBORHOOD SEARCH Jozef Kratica, Aleksandar Savić, Vladimir Filipović, Marija Milanović Abstract. In this paper
Power Flow Method for Loss Allocation in Radial Distribution Networks with DGs
Power Flow Method for Loss Allocation in Radial Distribution Networks with DGs G.Naguraiah 1, K. Jithendra Goud 2 1M.Tech student, Electrical Department, JNTUA College of Engineering, Anantapur, India.
Sect Graphing Techniques: Transformations
Sect. - Graphing Techniques: Transformations Recall the general shapes of each of the following basic functions and their properties: Identity Function Square Function f(x) = x f(x) = x - - - - - - - -
Research Collection. Localisation of Acoustic Emission in Reinforced Concrete using Heterogeneous Velocity Models. Conference Paper.
Research Collection Conference Paper Localisation of Acoustic Emission in Reinforced Concrete using Heterogeneous Velocity Models Author(s): Gollob, Stephan; Vogel, Thomas Publication Date: 2014 Permanent
3D diagrams of Eurostag generator models for improved dynamic simulations
3D diagrams of Eurostag generator models for improved dynamic simulations Achieve online dynamic security analysis To make good network situations short-term forecast, initializing dynamic simulations
Mesh Decimation. Mark Pauly
Mesh Decimation Mark Pauly Applications Oversampled 3D scan data ~150k triangles ~80k triangles Mark Pauly - ETH Zurich 280 Applications Overtessellation: E.g. iso-surface extraction Mark Pauly - ETH Zurich
Machine Learning Applications for Data Center Optimization
Machine Learning Applications for Data Center Optimization Jim Gao, Google Ratnesh Jamidar Indian Institute of Technology, Kanpur October 27, 2014 Outline Introduction Methodology General Background Model
A I only B II only C II and IV D I and III B. 5 C. -8
1. (7A) Points (3, 2) and (7, 2) are on the graphs of both quadratic functions f and g. The graph of f opens downward, and the graph of g opens upward. Which of these statements are true? I. The graphs
Preview Notes. Systems of Equations. Linear Functions. Let y = y. Solve for x then solve for y
Preview Notes Linear Functions A linear function is a straight line that has a slope (m) and a y-intercept (b). Systems of Equations 1. Comparison Method Let y = y x1 y1 x2 y2 Solve for x then solve for
Mixed Integer Non-linear Optimization for Crude Oil Scheduling
Mixed Integer Non-linear Optimization for Crude Oil Scheduling Ramkumar Karuppiah and Ignacio E. Grossmann niversit Enterprise-wide Optimization Project Introduction Purchasing and Scheduling of crude
OPTIMAL LOCATION OF SVC USING BENEFIT FACTORS TO IMPROVE THE VOLTAGE PROFILE IN POWER SYSTEMS
European International Journal of Science and Technology Vol. 4 No. 2 February, 2015 OPTIMAL LOCATION OF SVC USING BENEFIT FACTORS TO IMPROVE THE VOLTAGE PROFILE IN POWER SYSTEMS IRENE N. MUISYO a, KEREN
MINIMIZATION OF PART WARPAGE IN INJECTION MOLDING THROUGH IDEAL WALL THICKNESS DISTRIBUTION
MINIMIZATION OF PART WARPAGE IN INJECTION MOLDING THROUGH IDEAL WALL THICKNESS DISTRIBUTION Seminar: Auslegung und Simulation von temperaturbeanspruchten Kunststoffbauteilen MSc ME ETH Mario Studer Prof.
THIS paper describes the optimal power flow (OPF) architecture
1 MATPOWER s Etensible Optimal Power Flow Architecture Ray D. Zimmerman, Member, IEEE, Carlos E. Murillo-Sánchez, Member, IEEE, and Robert J. Thomas, Fellow, IEEE Abstract This paper describes the optimal
1. Answer: x or x. Explanation Set up the two equations, then solve each equation. x. Check
Thinkwell s Placement Test 5 Answer Key If you answered 7 or more Test 5 questions correctly, we recommend Thinkwell's Algebra. If you answered fewer than 7 Test 5 questions correctly, we recommend Thinkwell's
Energy Imbalance Market Technical Workshop. BAA Real-Time Congestion Balancing Account August 12, 2013
Energy Imbalance Technical Workshop BAA Real-Time Congestion Balancing Account August 12, 2013 Overview BAA Real-Time Congestion Balancing Account Real Time Convergence Bid Settlement Slide 2 BAA Real-Time
Service Restoration in DG-Integrated Distribution Networks Using an Exact Convex OPF Model
Service Restoration in DG-Integrated Distribution Networks Using an Exact Convex OPF Model 1 H. Sekhavatmanesh, Student Member, IEEE, M. Nick, Student Member, IEEE, M. Paolone, Senior Member, IEEE and
UNIT 8: SOLVING AND GRAPHING QUADRATICS. 8-1 Factoring to Solve Quadratic Equations. Solve each equation:
UNIT 8: SOLVING AND GRAPHING QUADRATICS 8-1 Factoring to Solve Quadratic Equations Zero Product Property For all numbers a & b Solve each equation: If: ab 0, 1. (x + 3)(x 5) = 0 Then one of these is true:
ETIP SNET (European Technology and Innovation Platform for Smart Networks for Energy Transition)
ETIP SNET (European Technology and Innovation Platform for Smart Networks for Energy Transition) Introduction to R&I activities in the scope of the ETIP SNET; presentation of the R&I roadmap 2016-2025.