Automating and Optimizing Demand Response in Buildings

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1 Automating and Optimizing Demand Response in Buildings Presentation ti to the Center for Information Technology Research in the Interest of Society January 3, 28 Mary Ann Piette Staff Scientist, Building Technologies Dept. Environmental Energy Technologies Division Lawrence Berkeley National Laboratory Research Director, Demand Response Research Center drrc.lbl.gov Sponsored by California Energy Commission Public Interest t Energy Research Program and California Institute for Energy and the Environment

2 Presentation Overview Demand Response Basics and the DRRC Automating Demand Response Energy Information Systems in Commercial Buildings Optimizing Efficiency and DR in Buildings Future Opportunities 2

3 Terminology and Recent History California ISO Emergencies Stage I - min operating reserve level falls < 7 % Stage II - min operating reserve level falls < 5 % Stage III - reserve level falls < 3 % begin rotating outages Winter consecutive days in Dec. of Stage I or II alerts State under Stage III alerts Jan 16th - Feb 16th Statewide rotating blackouts 3 days in January 2 days in March 2 days in May 21 3

4 4

5 Definition and Technology Needs DR Definition: Action to reduce load when Contingencies occur that threaten supply-demand balance Market conditions occur that raise supply costs peak-load reductions different from efficiency, transient vs. permanent DR Communications Infrastructure Needs Create real-time, automated t DR infrastructure t to respond to changing contingency and market conditions DR infrastructure should coexist with legacy systems, technology and tariff improvements, with near- and long-term benefits. C a lifo rn ia D a ily P e a k L o a d s , 6, R e s id e n tia l A ir C o n d itio n in g Com m ercial Air Conditioning 5, 4, MW 3, 2, 1, Jan-6 M ar-6 M ay-6 Jul-6 Sep-6 Nov-6 5

6 DRRC Research Areas Energy Systems and Strategic Issues Valuing Demand Response Dynamic Tariffs and Rate Design Communications Infrastructure Buildings Automation, Communications and Control End-Use Control Strategies and Models Behavior response to dynamic tariffs Industry Automation, End-Uses and Controls 6

7 Buildings Side of Demand Side Management Efficiency and Conservation (Daily) - Environmental Motivation Protection - Utility Bill Savings - Efficient Shell, Design Equipment & Systems - Integrated System Operations Operations Peak Load Management (Daily) - TOU Savings - Peak Demand Charge savings - Grid Protection Low Power Design Demand - Limiting and Shifting Demand Response (Dynamic Event Driven) - Economic - Reliability - Emergency - Grid Protection Dynamic Control Capability* Demand - Limiting, Shifting, or Shedding Initiation Local Local Remote *Prefer closed loop strategies, granular control 7

8 8

9 9 Automating Demand Response

10 Automation Goals and Definition Recent Research Goals Cost - Develop low-cost, automation infrastructure to improve DR capability in California Technology - Evaluate readiness of buildings to receive signals Capability - Evaluate capability of control strategies for current and future buildings AutoDR Definition - Fully automated signal for end-use control Signaling Continuous, secure, reliable, 2-way communication with listen and acknowledge signals Industry Standards - Open, interoperable standard control and communications to integrate with both common EMCS and other end- use devices that can receive a relay or similar signals (such XML) Timing of Notification - Day ahead and day of signals are provided to facilitate a diverse set of end-use strategies 1

11 11 Manual DR - Common Practice

12 DR Automation Server and Client DRAS Clients 1. Software only (Smart) 2. Software & Hardware (Simple) 12

13 DR Automation Server Event Architecture DRAS UI Web Server Configure DR Program Get Operator Reports DRAS Configure DRAS Client Connection Check status, get reports DRAS UI Web Server Participant Site Participant Manager Program Operator Utility/ISO ` Web Client Internet (SSL Secured) Update RTP Info DR opt out Send RTP Info to DRAS Client Send Event Info to DRAS Client Internet (SSL Secured) Web Client DRAS Client ` Utility Information System Initiate DR Event Set Load Status Voice mail, , Page, etc. Modify DR Event Exception Alarms 3 rd Party Notification System

14 14 Auto-DR in 13, ft 2 County Office Current Practice

15 Aggregated AutoDR Results June 26, Zone 2 Power [MW] Aggregated Demand, 6/26/26 (OAT: 89 F) - Zone 2, 8 sites Moderate Price High Price 1.3 MW reduction during high price period : : : : : : : : : : : : : : : : : : : : : : : : ACWD B of A Chabot 253 Arnold 5 Douglas MDF Echelon Gilead 3 Gilead 342 Gilead 357 IKEA EPaloAlto Oracle Rocklin Target Hayward Adj OAT Reg BL CPP BL 15 Average kw Average % Average W/ft² Moderate High Moderate High Moderate High ACWD % 32% B of A % 12% Arnold % 29% Douglas % 22% MDF % 3%.52.9 Echelon -2 8 % 22% Oracle Rocklin % 14%.85.6 Target Hayward % 15% Aggregated % 16%.65.88

16 Results From AutoDR 27 7/6 DR Event 7/6/27 OAT Baseline CPP Baseline CPP MA Baseline Whole Building Pow : AM 1: AM 2: AM 3: AM 4: AM 5: AM 6: AM 7: AM 8: AM 9: AM 1: AM 11: AM 12: PM 1: PM 2: PM 3: PM 4: PM 5: PM 6: PM 7: PM 8: PM 9: PM 1: PM 11: PM 16

17 Comparison of End-Use Strategies Global temperature reset migrating to State Energy Code HVAC Lighting Other Global temp p. adjustment Duct static pres. Increase SAT Increas se Fan VFD lim mit Increase CHW temp. Fan qty. red duction Pre-cooling Cooling valv ve limit Boiler locko out Slow recove ery Building use ACWD Office, lab X X X X X X X BofA Office, data center X X X X X Chabot Museum X X 253 Arnold Office X X 5 Douglas Office X X MDF Detention facility X Echelon Hi-tech office X X X X X X X X Centerville Junior Highschool X X Irvington Highschool X X Gilead 3 Office X Gilead 342 Office, Lab X X Gilead 357 Office, Lab X X IKEA EPaloAlto Furniture retail X IKEA Emeryville Furniture retail X IKEA WSacto Furniture retail Oracle Rocklin Office X X Safeway Stockton Supermarket X Solectron Office, Manufacture X X Svenhard's Bakery X Sybase Hi-tech office X Target Antioch Retail X X Target Bakersfield Retail X X Target Hayward Retail X X X X Walmart Fresno Retail X X Extended sh hed period Common ar rea light dim light dim Office area Turn off ligh ht Dimmable ballast tching Bi-level swit process shed Non-critical

18 Communications Systems Site Communication Price Client Price Client Price Client Device Method Host Host Location Hosted at Co-Lo ACWD Relay at site ADAM66 DRAS DRAS Co-Lo Yes B of A Relay at site ADAM66 DRAS DRAS Co-Lo Yes Chabot Relay at site ADAM66 DRAS DRAS Co-Lo Yes 253 Arnold Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes 5 Douglas Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes MDF Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes Echelon Software client ilon i.lon Kenmark San Francisco, CA No Centerville CLIR CLIR CLIR Onsite No Irvington CLIR CLIR CLIR Onsite No Gilead 3 Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes Gilead 342 Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes Gilead 357 Relay w/wan ADAM66 DRAS DRAS Co-Lo Yes IKEA EPaloAlto Relay at site ADAM66 DRAS DRAS Co-Lo Yes IKEA Emeryville CLIR CLIR CLIR Onsite No IKEA WSacto CLIR CLIR CLIR Onsite No Oracle Rocklin CLIR CLIR CLIR Onsite No Safeway Stockton CLIR CLIR CLIR Onsite No Solectron CLIR CLIR CLIR Onsite No Svenhard's Relay at site ADAM66 DRAS DRAS Co-Lo Yes Sybase CLIR CLIR CLIR Onsite No Target Hayward Software client Canon Technologies Target Minesota Yes Target Antioch Software client Automated Logic Target Minesota Yes Target Bakersfield Software client Automated Logic Target Minesota Yes Walmart Fresno Software client EnergyICT EnergyICT Belgium Yes 18

19 19 Enhance Current AutoDR Web Portal: Retain Chain

20 Time Scales of Building/Grid Optimization Automated DR Future Daily energy efficiency Daily kwh minimized Time-of use energy Day time kwh minimized Daily peak load managed Daily max kw Hourly kw Dayahead (slow) DR Real- time DR Day of kw Spinning reserve (fast) DR Minutes Service Levels Optimized Time of Use Optimized Service Levels Temporarily Reduced 2

21 21 EnergyPlus DR Assessment Tools

22 Related Research - Pre-Cooling Studies # of Sites/ Location Peak Shift (W/ft 2) % (whole building) Strategies Comfort Peak outside temp o F 23 1 / Santa Rosa 2.3 ~6% Pre cool one step temp set up No complaints / Santa Rosa, Sacramento.5~2. 1~66% Pre cool one step temp set up Comfort survey / Oakland.5~1. 1~25% Pre cool - various shed & recovery strategies Comfort survey, indoor monitors / Visalia.5~1. 1~15% Pre cool - various shed & recovery strategies Comfort survey, indoor monitors

23 Linking DR and Energy Efficiency Ideal start - good commissioning, retrocommissioning, advanced/new controls HVAC - Direct digital control (DDC) global temperature adjustment In process for Title Closed loop Lighting Continuum - Zone Switching, Fixture Switching, Lamp Switching, Stepped Dimming, Continuous Dimming Maybe you can use a strategy every day? Desire to try DR Y DDC zone N control? Y Global temp. N Y Air distribution Adjustment System DDC? capability? N Y Can program N Y Central plant GTA? DDC? N Global temp. adjustment Air distribution control Central plant control Do not try DR at this time 23

24 24 Energy Information Systems in Commercial Buildings

25 Information Monitoring & Diagnostic System Research from 1993 Data acquisition system High quality sensors (power, flows, temps) Data visualization tools High frequency data Automated diagnostic prototype research IMDS Remote Archive Supersymmetry LBNL Internet ISDN Connection On-Site Electric Eye Software Real-time Remote Web Browser Public Access IMDS On-Site Lighting Archive Whole Building HVAC Other Chillers Cooling Pumps Air Tower Distribution 25

26 IMDS Evaluation Results Key Benefits of IMDS Dramatic improvement in controls & automation Better comfort & reduced complaints Extended equipment life Temperature (Deg gree F) Return Air Temp 6: Supply Air Temp Outside Air Drybulb 12: Supply Intake Temp BEFORE 18: 24: Desire for New Technology Continuous archive Real-time graphical analysis Web-based remote access Temperature (D Degree F) Supply Air Temp 6: Return Air Temp Supply Intake Outside Air Temp Drybulb 12: AFTER 18: 24: 26

27 Inlet Vane Control Problem Oscillations begin after incorrect tuning Chiller Load (Tons) 2 1 Chilled Water Temperatures (Degree F) 8 Chiller Power (kw) Oscillations are not visible in 15-minute data Chiller Load (Tons) 2 6: 12: Time of Day (18 Aug 1999) 18: 24: Chilled Water Temperatures (Degree F) Chiller Power (kw) 4 2 6: 12: Time of Day (18 Aug 1999) 18: 24: 27

28 Energy Information Systems at University of California Santa Barbara 5.3 Million Sq. Ft. 989 Acres 19 Students 9 Faculty 3 Staff 11.5 MW Peak Demand Down from 15 MW

29 Energy Information System Operations EIS users: energy manager, facility managers Use: 3 min/day, or more when settings have been changed. What: Time-series energy energy consumption data as daily routine. Bonus: Reporting features support participation in energy conservation programs. 29

30 Findings from the EIS Fan Nighttime Reduction Baseline: 465 kw 3

31 Findings from the EIS Fan Nighttime Reduction Baseline: 235 kw 31

32 Benefits Analysis Electricity Cost Saving Electricity Peak Demand [MWH] [kw] Total May-April1 83,7 12,742 May1-April2 75,1 11,362 Savings 8,6 1,3 Cost saved $43, $16, $59, (1.3%) (12.4%) (1.8%) Due to EIS (5%) $215, $8, $295, EIS first year cost: $295, Payback period: 1.2 year 32

33 33 Optimizing Efficiency and DR in Buildings

34 Improving DR capability in Buildings from Present to Future Improved levels of granularity/modular control Improved intelligence of building modes lighting, HVAC, other Improved end-use metering, service level performance metrics HVAC Lighting Other Global temp. adjus stment Duct static pres. In ncrease SAT Increase Fan VFD limit CHW temp. Increa ase Fan qty. reduction Pre-cooling Cooling valve limit Boiler lockout Slow recovery Extended shed pe eriod Common area ligh ht dim Office area light d im Turn off light Dimmable ballast Bi-level switching Non-critical proces ss shed Building use ACWD Office, lab X X X X X X X B of A Office, data center X X X X X Chabot Museum X X 253 Arnold Office X X 5 Douglas Office X X MDF Detention facility X Echelon Hi-tech office X X X X X X X X Centerville Junior Highschool X X Irvington Highschool X X Gilead 3 Office X Gilead 342 Office, Lab X X Gilead 357 Office, Lab X X IKEA EPaloAlto Furniture retail X IKEA Emeryville Furniture retail X IKEA WSacto Furniture retail Oracle Rocklin Office X X S f St kt S k t X Solectron Office, Manufacture X X Svenhard's Bakery X Sybase Hi-tech office X Target Antioch Retail X X Target Bakersfield Retail X X Target Hayward Retail X X X X Walmart Fresno Retail X X Multi-objective optimization Safeway Stockton Supermarket X 34

35 New Construction Vision: Zero Energy Building Creating a New Generation of Net-Zero Energy, Carbon-Neutral Buildings Automation Energy sensors & actuators Wireless communication Feedback control systems Functional Building Materials Thermal Structural Tunable Windows Cool Stuff

36 Multi-Objective Optimization Energy -On/off mode/control -Weather/solar/wind / -Occupancy/comfort/schedule -Equipment loads - Continuous diagnostics Operating Costs - Rate $/kwh, TOU, demand charges - Dynamic critical, variable peak, RTP - DR program shed frequency, duration - Maintenance and operations Emissions -Real-time CO 2 /kwh (time of day) -Grid or on-site power -Energy source Demand Response/Grid - Loads to limit, shift, shed - Service level control capability - Service level requirements Duration, frequency of DR participation - Spinning reserve participation Conventional Variable Air Volume Ice/Chilled Water Storage VAV with Pre Cooling Operating Demand Energy Costs Emissions Response (kwh) ($) (CO 2 ) ($/kw) 36

37 37 Auto-DR in 13, ft 2 County Office Current Practice

38 Auto-DR in 13, ft 2 County Office with Optimized Shed Shape 38

39 Future Directions DR strategies as a Mode in Optimized Control Orchestrate modes using schedules, signals, optimization algorithms: Occupied/Unoccupied i d Maintenance/Cleaning Warm up/cool down Night purge/pre-cooling Low power DR mode Intelligence needed for decision making Customized, simple and transparent interface KWH Financial feedback systems need to present operational value Embed DR Communications in EMCS Need more sensors, algorithms, real-time simulations, feedback! 39

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