www.smart-microgrid.ca project 2.3 demand response technologies and strategies: energy management...

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www.smart- microgrid.ca Project 2.3 Demand 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 Engineering University of Waterloo, Waterloo, Ontario, Canada

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www.smart-microgrid.ca

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

www.smart-microgrid.ca 2

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

www.smart-microgrid.ca

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