title of presentation goes here - nfmt · ahu to chiller plant floor to building building to site...

Title of Presentation

Goes Here

Presenter Name Title, Company

The Future of Building

Information is Tags

Chris Hollinger Business Line Manager, Siemens Building Technologies

Learning Objectives:

• Understand tags and what they are, and a bit of how they developed

• Discuss tags in the context of building automation systems

• What building automation management problems does tagging solve?

• Where will tags go in the future?

What is a tag?

• A hashtag is a type of label or metadata tag used on social network and microblogging services

Tagging has evolved over the course of time to solve a common problem

– information management

Twitter hyperlinks all hashtags in tweets

Twitter introduces trending topics and Introduces algorithm to tackle spam to make sure trends are natural

2009 2010

Social bookmarking website Delicious provided a way for its users to add "tags" to their bookmarks; Delicious also provided browseable aggregated views of the bookmarks of all users featuring a particular tag. Flickr allowed its users to add their own text tags to each of their pictures, constructing flexible and easy metadata that made the pictures highly searchable

2003

First Web2.0 conference: Tagging was popularized by websites associated with Web 2.0 and is an important feature of many Web 2.0 services.

2004

Tagging is also a solution to BAS information management

BACnet XD submitted for public review and comment providing semantics tags on objects and properties; providing discoverable arrangements of objects and properties; describing proprietary objects, properties, and datatypes; providing property metadata like writability, range, volatility, etc.; declaring device capabilities (PICS data).

2013

Project Haystack formed Project Haystack is an open source initiative to streamline working with data from the Internet of Things. We standardize semantic data models and web services with the goal of making it easier to unlock value from the vast quantity of data being generated by the smart devices that permeate our homes, buildings, factories, and cities. Applications include automation, control, energy, HVAC, lighting, and other environmental systems.

2014

Hashtags, used in…

• Twitter, the birthplace of social media tags

• Google+

• Facebook

• Instagram

• Pinterest

What is a tag used for? Why? •Because it makes it easier for users to find messages with a specific theme or content. •Users create and use hashtags by placing the hash character (or number sign) # in front of a word or unspaced phrase, either in the main text of a message or at the end. •Searching for that hashtag will then present each message that has been tagged with it.

What is a tag used for?

• For example, a hashtag #nfmtorlando2015 allows users to find images that have been tagged as containing #nfmtorlando2015. Hashtags can be used to collect public opinion on events and ideas at the local, corporate, or world level.

How do we narrow down tag searches? #NFMT #NFMT_Conference

#BACnet

• Which tag will pull the best info on the 2014 Soccer World Cup?

searching Twitter for #worldcup2014returns many tweets from individuals around the globe about the 2014 FIFA World Cup.

WorldCup

WorldCup2014

SoccerWorldCup

World cup example #worldcup

#worldcup2014

#soccerworldcup

Twitter best practices for hashtag use:

• Be specific: – If you’re using a hashtag to join a conversation, make sure the hashtag is

specific and relevant to your topic. If you’re talking about Obama's health care plan, use #Obamacare instead of simply #Obama. A vague or generic hashtag like #health or #opinion isn’t effective either.

Twitter best practices for hashtag use:

• Keep it simple: – Hashtags, like links, look like spam if they are used too often. Three

hashtags should be the maximum on Twitter and Facebook, but you can get away with more hashtags on Instagram and Vine. And don’t hashtag the same word twice (“#Gravity is a great movie! Everybody go see #Gravity”). It’s #redundant.

Twitter best practices for hashtag use:

• Give context:

– A tweet that contains only hashtags is not only confusing — it's boring. If your tweet simply reads, “#happy,” your followers will have no idea what you’re talking about. Similarly, if you tweet, “#BreakingBad is #awesome,” you’re not really adding much to the conversation.

In BAS, what does tagging add?

• Classic protocol definitions leave gaps in the project implementation definition: – Context definition for information. What does this

information actually represent and how to use it? – Consistency from project implementation to project

implementation – Search and consume the data for analytics purposes – Integration of proprietary pieces of information, either

proprietary objects or proprietary extensions to standard objects

– Ability to create virtual hierarchies of related objects to facilitate logical associations amongst multiple devices and objects

Problem: Point Names are typically per project, per contractor or per individual implementation whim

Result: Data is difficult to present and integrate, difficult to sort, difficult to parse, difficult to harvest for valuable information Not consistent across projects

Options: 1. Rename points system-wide Pros: Solves the problem of having consistent point names for now Cons: One time solution, which takes immense amount of effort and likely will break many system interdependencies such as graphics, defined reports, system logic 2. Use a mapping gateway device Pros: Allows for intelligent pseudo naming without changing the original name and disrupting system wide usage Cons: Requires effort for mapping plus a gateway device, and project specific implementation 3. Tagging Pros: Allows intelligent pseudo naming without changing the original name and disrupting system wide usage and implementation may be standardized across many projects or even industry Cons: Consensus required on standard for meaningful and consistent tagging

What can be done to provide standardized semantic tags for BAS?

Agree on the definition of “semantic tagging model”.

The Project Haystack tagging model has three significant aspects, which have differing

levels of relevance to BACnet

The Tagging Dictionary Standardized Tag Sets Standardized Hierarchical Models

Marker (semantic) Tags Value Tags Ref Tags

Tag combinations that allow Descriptive Object Types to be identified

Standardized Ref Tags are used to construct standard hierarchies for modeling applications, geographic areas, building floors, devices and networks, etc.

Descriptive Object

Goal is to provide a model that can be applied to either BACnet or Haystack. The first

element of this model is the Descriptive (or “self-describing”) Object Type.

Standardized Descriptive Object Types are not explicitly provided by either Haystack or

BACnet. However, the model can easily be applied to either, assuming incorporation of

tagging elements into BACnet objects.

Space temperature Humidity CO2 Damper position Cooling valve position

Standardize information represented as a descriptive tags:

Space temperature current value in deg F Humidity in % RH CO2 in PPM Damper position is 50% open Cooling valve position is 100% open

Standardize the properties and attributes of the value tags:

Descriptive Structure

The second element of the is the Descriptive (or “self-describing”) Structure.

Project Haystack defines a number of standardized Descriptive Structure Types (ahu <-

vav, site <- floor, equip <- point, etc.).

Sensor to equipment VAV box to VAV AHU AHU to chiller plant Floor to building Building to site

Standardize relationships represented in a reference tag:

VAV box #10 to VAV AHU #2 AHU #2 to Chiller #1 Floor #1 to Building #2 Building #2 to Site Orlando

Data represented as examples of the structured relationship:

Standardized Semantic Tag Sets

Combinations of semantic tags are used to indicate what the Object or Structure

represents. To achieve interoperability, it is necessary for these combinations to be

standardized. It is not adequate for only the individual tags to be standardized.

VAV box space temperature = zone; point; temperature; sensor

Standardize application type represented in a tag structure:

VAV box damper position = zone; point; damper; sensor

Standardize application type represented in a tag structure:

VAV box humidity = zone; point; humidity; sensor

Standardize application type represented in a tag structure:

Mapping Between BACnet and Haystack Models

The primary focus should be on standardizing tags and tag sets for the purpose of

describing the real-world entities that each object represents.

BACnet Object Haystack Model

Standard semantic tags and tag sets

Building #1 System A; AHU #1-4

Room setpoint = 69 Room setpoint = 73

Room setpoint = 72 Room setpoint = 73

Room setpoint = 69 Room setpoint = 73

Room setpoint = 71 Room setpoint = 71

Building #2 System B; AHU #1-7

What AHU and VAV box system points would be important to track?

VAVDPos

RACO2 VAVHVPos

RATemp

SATemp

AHUSPLYAIRTemp

AHUSPLYFSPD

VAVCLGVPos SACO2

Building #1, System A, AHU#2

SAFLW

What AHU and VAV box system points would be important to track?

VAVDmprPos

RtnAirCO2 VAVHtVlvPos

RtnAirTemp

SplyAirTemp

AHUSplyAirTemp

AHUSplyFanSpd

VAVClgVlvPos SplyAirCO2

Building #2, System B, AHU#2

SplyAirFlow

What AHU and VAV box system points would be important to track?

VAV box damper positions

Heating valve position

Return air temp

Supply air temp

Return air CO2

Supply air temp

Supply air CO2

Fan Speed

Cooling valve

Supply Air Flow

Building #1 CWS A

Building #2 CWS B

Example Point Name

CWS A

Example Point Name

CWS B

Tag Examples

ChWSTemp CHWST chilled, water, temp,

leaving, sensor

ChWRTemp CHWRT chilled, water, temp,

entering, sensor

CondWSTemp CNDWST condensed, water,

temp, leaving, sensor

CondWRTemp CNDWRT condensed, water,

temp, entering, sensor

ChWFlow CHWFL chilled, water, flow,

sensor

RefrCondTemp RFRCNDT Condenser, refrig,

temp, sensor

RefrCondPres RFRCNDPR Condenser, refrig,

pressure, sensor

RefrLiqTemp RFRLQDT Condenser, refrig,

temp, sensor

Intelligent Discovery • Objects know what they are

• Not just an AI, a return air temp sensor

• Not just an AO, a heating coil valve

• Combining this knowledge with system views is

the basis for further automated fault detection

• This information then allows for trending and

reporting like data across the system

Intelligent Design • Objects know what they are

• Not just an AI, a discharge air temp sensor

• Not just an AO, a cooling coil valve

• Building graphics is easier since objects know what

mechanical component they represent

Intelligent Graphics Creation • Produce high volume graphics automatically based

on common application model and common

tagging mechanisms

Central Plant Energy Analysis • Easily find and track values for comparisons and

trend analysis

• Total plant kW

• Outside air temperature

Central Plant Energy Analysis • Easily find and track values for comparisons and

trend analysis

• Total plant kW

• Outside air temperature

• Total Plant kW/Ton

Query report: • Total kW • Outside air temperature • Total kW/ton

Equipment Performance Analysis • Easily find and track values for comparisons and

trend analysis

• Assess efficiency

• Assess trends in performance

• Compare like plants

Query report: • Total AHU kWh • Total kWh • Outside air temperature Avg

Query report: • Chiller Total kWh • Economizer System Enable

Efficiency Analysis and Comparisons • Easily find and track values for comparisons and

trend analysis

• Heat kBTU

• Electricity kWh

• Gas therms

Analyze Data Efficiency Comparisons

• Track utility usage

• Assess trends in utility usage over time

Case study: Bass Pro Shop’s Energy Management System

Hardware Components Installed:

Building Automation System

HVAC Controls

Lighting Controls

Smoke Evacuation Controls

Weather Station

Energy Meters

Utility Meters

Graphics, Analytics and M&V Data Server

Energy Distribution

TM

Measurement & Verification

Continuous Commissioning Energy Distribution

• Reporting Levels and KPI’s: Whole Building and

Evaluated Energy Conservation Measures

• Key Inputs: eQUEST Model, Electricity, Gas, Water,

PV, Weather, Occupancy, Operational Schedule

• Features: IPMVP Compliant M&V Energy Savings

Dashboard – Baseline Model vs Actual Results

• Dashboard of KPIs for whole building, sub-meters

• Measurement of kW, kWh, cf, cfh, therms, Btu, gal,

cfm, temp F◦, kW/ton, lbs CO2

• Summary, Demand, Consumption, Meter Page

Details, Charts/Graph/Tabular

• Dashboard of KPIs for whole building, sub-meters

• Measurement of kW, kWh, cf, cfh, therms, Btu, gal,

cfm, temp F◦, kW/ton, lbs CO2

• Summary, Demand, Consumption, Meter Page

Details, Charts/Graph/Tabular

• Track and measure mechanical system performance

• Compare to seasonal adjustments

• Compare to as built values

Tagging can be your standard, help define it!

http://project-haystack.org

http://www.bacnet.org

Learning Objectives:

1. Please list your four learning objectives on this page

2. Second Objective

3. Third Objective

4. Fourth Objective