Proprietary information – Columbia University. All rights reserved, 2009 – 2010. Smart Grid Issues Panel Discussion 25 October 2010 David Waltz.

Slides:



Advertisements
Similar presentations
The Utility View: Electrical Vehicle Impact IEEE CCW October 25, 2010.
Advertisements

Strategic Capacity Planning for Products and Services McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Outage Reporting Hierarchy Background Data Capture Structure Next Steps.
1 Smart Grid Vision Electric Grid Modernization Steering Committee Grid Facing Technology Subcommittee January 14, 2013.
Data and Computer Communications
DISPUTES & INVESTIGATIONS ECONOMICS FINANCIAL ADVISORY MANAGEMENT CONSULTING Early Lessons Learned from DOE-EPRI Framework Experience Melissa Chan MA DPU.
Introduction Build and impact metric data provided by the SGIG recipients convey the type and extent of technology deployment, as well as its effect on.
VSE Corporation Proprietary Information
Opportunities for Demand Response in California Agricultural Irrigation Gary Marks iP Solutions Corp. 10/15/2012.
ERCOT VRT Study, Phase I ERCOT ROS Meeting December 10, 2009.
Smart Grid Applications: Viewpoint of an Electrical Power Engineer Francisco de Leon October 2010.
1 © 2012 Lockheed Martin Corporation, All Rights Reserved Intelligent Microgrid Solutions Efficient, Reliable and Secure Solutions for Today’s Energy Challenges.
Xanthus Consulting International Smart Grid Cyber Security: Support from Power System SCADA and EMS Frances Cleveland
Sampling distributions. Example Take random sample of students. Ask “how many courses did you study for this past weekend?” Calculate a statistic, say,
Developing an Approach to the Analytic Gap: Advanced Mathematics for Scale and Complexity Dr. Kirstie Bellman, Co-PI (Partner Shankar Sastry, UCB) Aerospace.
Washington DC October 2012 The Role of PEV and PV in the Changing Electric Utility Market Mike Rowand Duke Energy.
Ee392n - Spring 2011 Stanford University Intelligent Energy Systems 1 Lecture 3 Intelligent Energy Systems: Control and Monitoring Basics Dimitry Gorinevsky.
Embedded and Real Time Systems Lecture #2 David Andrews
By Lauren Felton. The electric grid delivers electricity from points of generation to consumers, and the electricity delivery network functions via two.
Assembling the Parts of the Puzzle: “Interoperability” is What Makes Them Fit Together John Jimison Managing Director Energy Future Coalition.
When Grids gets smart Claes Rytoft Senior Vice President ABB World Forum on Energy Regulation IV Athens, Greece October , 2009.
PowerPoint ® Presentation Chapter 12 Utility Interconnection Distributed Generation Generators Inverters Interconnection Codes and Standards Interconnection.
American Electric Power (AEP) Virtual Power Plant Simulator (VPPS) Tom Jones, Manger – Corporate Technology Development American Electric Power Grid-InterOp.
Smart Integrated Infrastructure The Progression of Smart Grid Presentation to National League of Cities Martin G. Travers – President, Telecommunications.
Mobile Ghent Mobile positioning data and transport: a theoretical, methodological and empirical discussion 24 October 2013 Bert van Wee Delft University.
INTERNET OF THINGS Challenges of 21 st century and Technological innovation February -2011
Smart Grid Technologies Damon Dougherty – Industry Manager.
3/31/20091 Electric Power Grid Performance Presentation by Anthony J Spurgin Independent Consultant San Diego, CA
Smart Grid m Yumiko Kimezawa August 12, 20111Colloquium.
APC InfraStruxure TM Central Smart Plug-In for HP Operations Manager Manage Power, Cooling, Security, Environment, Rack Access and Physical Layer Infrastructure.
COLUMBIA UNIVERSITY Department of Electrical Engineering The Fu Foundation School of Engineering and Applied Science IN THE CITY OF NEW YORK Networking.
Information-Based Building Energy Management SEEDM Breakout Session #4.
Copyright 2010 – Johnson Controls, Inc. 1 A Day in the Life of a Smart Campus Clay Nesler VP, Global Energy & Sustainability Johnson Controls
1 Critical Mission Support Through Energy Security Susan Van Scoyoc Concurrent Technologies Corporation 16 August 2012 Energy Huntsville Meeting Huntsville,
Planning and Analysis Tools to Evaluate Distribution Automation Implementation and Benefits Anil Pahwa Kansas State University Power Systems Conference.
An Overview of the Smart Grid David K. Owens Chair, AABE Legislative Issues and Public Policy Committee AABE Smart Grid Working Group Webinar September.
67th NECPUC ANNUAL SYMPOSIUM Whiz Bang New Stuff June 17 th, 2014.
Value now. Value over time. © Copyright 2010, OSIsoft, LLC All rights Reserved. Enabling Data Infrastructure for Utility Sustainability John Lacy November.
Discussion topics for PSRA-TF meeting on energy and utility applications September 24, DRAFT.
© 2014 Pegasystems Inc. Orchestrating The Internet of Everything with The Process of Everything January 2014.
Presentation Identifier (Title or Location), Month 00, 2008 Cost and Benefit Analysis Framework: Update EPRI Smart Grid Advisory Meeting October 14, 2009.
PS ERC New Pserc Projects Mladen Kezunovic. PS ERC Newly approved projects "...Enhanced Reliability..." Kezunovic "...Automated Integration..." McCalley.
Outage Communication – Improving the Flow of Information Presented at the EEI Transmission, Distribution, and Metering Conference Tucson, Arizona October.
MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG Big Events Hans-Arno Jacobsen Middleware Systems Research Group MSRG.org.
Cogeneration (CHP – Combined Heat & Power) October 2013 © Siemens AG All rights reserved.
1 V&V Needs for NextGen of 2025 and Beyond A JPDO Perspective Maureen Keegan JPDO Integration Manager October 13, 2010.
Text Computational Optimisation for Smart Energy Systems Eric Pauwels, CWI, Amsterdam EIT Digital funded collaboration between CWI, TU Berlin, TU Delft.
Foundations of Information Systems in Business. System ® System  A system is an interrelated set of business procedures used within one business unit.
Predictive Learning for Energy Storage Dinos Gonatas (978) Ryan Hanna Center for Renewable Resources and Integration.
Ronald J. Zimmer CAE President & CEO Continental Automated Buildings Association LinkedIn Profile M2M Canada: Driving the Machine to.
Smart Grid Schneider Electric Javier Orellana
Energy: Machines, Motion and Light Energy exists in many different states. Energy can be transformed from one state to another in order to power machines.
Oncor Transmission Service Provider Kenneth A. Donohoo Director – System Planning, Distribution and Transmission Oncor Electric Delivery Co LLC
Distribution Automation The utilization of IEDs (Intelligent Electronic Devices) and advanced communications to unlock the benefits of operational efficiency.
A smart grid delivers electricity from suppliers to consumers using two-way digital technology to control appliances at consumers' homes to save energy,
William Stallings Data and Computer Communications
Breakout Session on Smart Grid Data Analytics
Product reliability Measuring
Building a Sustainable Energy Future
Load Balancing: List Scheduling
The Management of Renewable Energy
EE5900: Cyber-Physical Systems
Failures of Technological Systems
Sahar Rahim MS-Electrical Engineering Supervisor: Dr. Nadeem Javaid
H.O.M.E. Home Organization and Monitoring of Energy
2500 R Midtown Sacramento Municipal Utility District
Statistical Thinking and Applications
In ABB AbilityTM Electrical Distribution Control System (EDCS)
Load Balancing: List Scheduling
Presentation transcript:

Proprietary information – Columbia University. All rights reserved, 2009 – Smart Grid Issues Panel Discussion 25 October 2010 David Waltz

Proprietary information – Columbia University. All rights reserved, 2009 – Control  Smart Grid will have smart sensors everywhere  Much control will be distributed  Certainly at level of home or office  Large building? Neighborhood?  Distributed generation (wind, solar, co-gen,…)  Transmission/distribution control is more problematic  Would like to dynamically balance system loading, use “islanding” to limit fault cascades  What kinds of actions can be taken? Devices lacking and/or not standardized beyond ~circuit breaker level  Need centralized picture of overall system state  In emergencies, crews and equipment will need to be dispached  Distributed sensors need to collect, combine, summarize, decide who to tell about state (both central system, customers)

Proprietary information – Columbia University. All rights reserved, 2009 – Data & Control  First, utilities need to start collecting and saving data if they are not already doing so  It’s now possible to start assembling “best practices” for what data to collect, and what form to store it in to support analysis  More data is probably the greatest need  Critical events (e.g. failures) are rare  Learning requires statistically meaningful numbers of samples  Analytics and modeling are also very important  Machine Learning is key  Systems, loads, weather are constantly changing, so fixed models are inappropriate  As more distributed control possible, and more sensor data is collected, system models need to be adaptable  Ultimately, optimizing decision support that can deal with uncertain futures is required