project 2.3 demand response technologies and strategies: energy management and metering
DESCRIPTION
Project 2.3 Demand Response Technologies and Strategies: Energy Management and Metering Kankar Bhattacharya and Claudio Ca ñ izares Students: Rupali Jain, Rajib Kundu, Felipe Ramos Gaete Department of Electrical & Computer Engineering University of Waterloo, Waterloo, Ontario, Canada. - PowerPoint PPT PresentationTRANSCRIPT
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Project 2.3Demand Response Technologies and Strategies: Energy Management and
Metering
Kankar Bhattacharya and Claudio Cañizares
Students: Rupali Jain, Rajib Kundu, Felipe Ramos Gaete
Department of Electrical & Computer EngineeringUniversity of Waterloo, Waterloo, Ontario, Canada
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Research Objectives• Develop new Demand Response models
and tools for various customer categories in an Energy Hub (continuation of an ongoing OCE project):– Industrial Hubs: Various types not considered
so far– Residential Hubs: Buildings– Agricultural Hubs: Implementation of
previously developed greenhouse models– Commercial/Institutional Hubs: Arena models
and implementation• Determine resulting benefits in terms of
reduction in peak load and energy consumption
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Source: Energy Hub Management System Projecthttp://www.energyhub.uwaterloo.ca/
Macrohub
MacrohubMacrohub
Macrohub
LDC
Residential Microhubs
Institutional & Commercial Microhubs
Agricultural Microhubs
IndustrialMicrohubs
Energy market price, system condition, weather forecast
Overview
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Source: Energy Hub Management System Projecthttp://www.energyhub.uwaterloo.ca/
Overview
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Overview
Agricultural Hubs:
Greenhouses
Residential Hubs:Large
Residential Complexes
Commercial &
Institutional Hubs:
Ice Rinks
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2011 •Literature review on DR and load models: various industries, arenas and buildings
2012 •Mathematical model development & optimization studies
2013 •Mathematical model development & optimization studies
2014 •DR models tuning, testing and possible implementation
2015 •DR models tuning, testing and possible implementation
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This ProjectDesign
scheduling algorithms to
determine cost and benefits
Algorithms for optimizing DR
Project 2.2Impact on steady
state, and dynamic performance
Supervisory control and power
management strategies
Project 2.1Identification of
benefitsMethod for quantifying
benefits
Project 2.4 Control,
communication layers
Models for different operating scenarios
and study cases
Project 1 Operation, control and protection of smart microgrids
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Gaps
Real case studiesSector specific dataImplementation