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