ENERGY ONTOLOGY FOR NET-ZERO ENERGY BUILDINGS

Presented by Philip Odonkor

IE 500 – ONTOLOGICAL ENGINEERINGNovember 24, 2014

IE 500

Ontological Engineering

Presentation Overview

• Introduction to Net Zero

Buildings

• Problem Statement

• Proposed Approach

• Ontology

• Conclusions

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The Energy Challenge

North America

S. America

Europe

Africa

Asia

Globally, buildings consume 32% of the total energy produced.

They represent a key cog in the needed transition towards energy sustainability.

Net-Zero energy building clusters offer a viable solution for energy sustainability.

Australia

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What are Net-Zero Energy Buildings?

Buildings which generate as much energy as they consume.

zHome Townhome Project, Seattle

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Objective

Develop an ontology which accurately

captures and models the energy interactions

within net zero energy buildings to enable

informed energy strategies.

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Ontologies of Interest

Describes the physical environment of a building.

Building Ontology

An ontology describing user information and preferences

User Preference OntologyCaptures knowledge with regards to the weather

Environment Ontology

Captures information regarding onsite energy sources, energy grid, energy.

Energy Ontology

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Ontologies of Interest

Describes the physical environment of a building.

Building Ontology

An ontology describing user information and preferences

User Preference OntologyCaptures knowledge with regards to the weather

Environment Ontology

Captures information regarding onsite energy sources, energy grid, energy.

Energy Ontology

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Existing Ontologi

es

At least 7 Ontologies of

interest

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Existing Ontologi

es

DogOnt Ontology Modelling for Smart Home

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Existing Ontologi

es

Codamos Ontology Modelling Electrical Energy

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Existing Ontologi

es

BONSAI Ontology Modelling for Environment

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NetZOntOntology modeling for Net-Zero energy buildings

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Ontological Engineering

Scope

• Defining buildings and spaces within them

• Defining appliances which consume energy

• Linking appliances with on/off states

• Linking appliances with functionality

• Associate power consumption to appliances at different

on/off states

• Generating instances

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Imported Ontologies

• BFO 1.1 - Upper lever Ontology

• OBO metadata-ontology – Annotation purposes

• UCUM - The Unified Code for Units of Measure Ontology

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Key Classes : Building

Building

Commercial

Residential Townhouse

Detached House

Condominium

is_a

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Key Classes : Appliances

Appliance

Major

Small

Blender

Game Console

is_a

Fridge

Electric Stove

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BFO Integration

Buildings and Appliances – Independent Continuants - Material Entity - Object Building Environment – Independent Continuants - Site

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OBO Annotation Integration

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System Modeling Using Competency Questions

Building Environment Room

Kitchen

On/OffState

Discrete State

State

Desk Fan

Appliance

Small Appliance

is_in

has_state

has_functionality

What types of rooms are in the building?

……………

What types of energy consumers are in the

building?……………

What instances of energy consumers do we have?

……………

How do we know if instance is on or off?

……………

How do we know what functionality is offered by

instance?

On/OffFunctionality

Control Functionality

Functionality

Competency questions are targets for what your ontology should be able to answer, given sufficient facts (i.e. data) in your knowledgebase.

is_a

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Which rooms have energy consuming devices?

……………

System Queries

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What are these energy consuming devices?

……………

System Queries

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Which devices have a ‘wash’ functionality and a

power consumption of 650W?

……………

System Queries

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Conclusions

• NetZOnt: An ontology for modeling the energy interactions in NetZero energy buildings

• System modeling was done using Competency Questions

• Can be used to design energy conservation strategies

• Extend model to incorporate user preference and environment ontologies.

• Develop query structure to compute energy consumption at any given time.

Future Work Summary

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Acknowledgements

I will like to acknowledge the efforts of Barry Smith, Ron Rudnicki and Alan Ruttenberg for

their guidance in this project.

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