DR in cold climate: Current R&D activities at IREQ Marie-Andrée Leduc, ing. M.Sc. Researcher Building Energetics IREQ

11/10/2014

1 www.peakload.org

Overview • Hydro-Québec and IREQ • Context • DR research • Residential • Space heating • Water heating

• Commercial and Institutionnal • HVAC control – Field study • Analytics

• Future work

11/10/2014

2 www.peakload.org

HYDRO-QUÉBEC AND IREQ

11/10/2014

3 www.peakload.org

Hydro-Québec at a glance • Integrated, gvnm’t owned utility • Installed capacity: 36 068 MW (hydro) • 33 885 km of transmission lines • interconnections with Ontario, NB/NE and NY markets • Annual electricity sales : 205 TWh • Customers: +4M • 3,7 M residential, • 291 000 commercial, 18 600 industrial

• AMI rollout to be completed by 2018 http://meters.hydroquebec.com/ 11/10/2014

4 www.peakload.org

IREQ – Institut de Recherche d’Hydro-Québec • 2 sites (IREQ, LTE) • 470 employees • Several fields of expertise including: End uses (Building Energetics Team) Electrical equipments Material science Robotics and civil works Mechanics, metallurgy and hydro/wind Information and measuring systems Electrical networks and mathematics 11/10/2014

5 www.peakload.org

CONTEXT

11/10/2014

6 www.peakload.org

Our climate Land of extremes

Montreal data 2013… • Ambiant temperatures

• Winter mean daily: -8,1°C (low: -24,7°C) • Summer mean daily: 23,2°C (high: 33,2°C)

• Water supply temperature • Winter 4°C • Summer 18°C

11/10/2014

7 www.peakload.org

Our peak • interruptible ind. (850 MW) • dual energy res. (640 MW)

• Electricity used as primary energy source for heating for most of our customers

11/10/2014

Source: Régie de l’énergie du Québec, R-3891-2014 and R-3864-2014

• 2014 Winter peak: 39 031 MW • Current DR programs :

8 www.peakload.org

DR RESEARCH

11/10/2014

9 www.peakload.org

DR applications under study • Focus on capacity

• Ancillary services are now being studied Existing programs or previous commercial pilots

IREQ’S role is to… Temperature sensitive Dual energy tariff • Estimate the potentiel of various DR resources • Evaluate different technical DR approaches (impacts, pros/cons) • Advice BUs using knowledge based on our research 11/10/2014

Source: NERC. Demand Response Availability Data System (DADS): Phase I and II Final Report. Princeton, NJ: North American Electric Reliability Corporation , 2011.

IREQ research

10 www.peakload.org

RESIDENTIAL customers Loads studied • • • • •

space heating water heating hot tubs ventilation appliances

Methodology • • • •

Characterization (extensive monitoring, tech. review) Simulation (ind. loads, load aggregation) DR potential evaluation Demonstration www.peakload.org

Residential Space heating Building stock characteristics • • • •

Wood-framed construction Heated basement and garage Electricity as primary source for heating Largely baseboard Zone by zone heating, decentralized control

Questions to be answered.. What is an acceptable setback for DR in a heating context? How do we define/measure acceptable ? Should preheating be done ? By how much ? How many thermostats should be controlled ? What will be the interactions between the different zones if partial control is done? How will it affects the DR potential what about the level of uncertainty of this resource ? What type of setpoint trajectories offers the best tradeoff between comfort and load reduction ? What about the rebound effect, how can it be limited ? What is the maximum allowable penetration rate of this DR resource ? ... 11/10/2014

12 www.peakload.org

Residential Space heating – lab testing EHBE: Experimental Houses for Building Energetics • unoccupied • better understand the physics (setpoint modulation, partial control) Fournier, M. Leduc, M-A, Study of Electrical Heating Setpoint Modulation Strategies for Residential Demand Response, eSim2014 Proceedings Le Bel, C., Gélinas, S., 2013. All-electric experimental twin houses: the ultimate demand management testing tool, Proceedings of The IASTED International Symposium on Power and Energy (PE 2013), Marina Del Rey, California, November 11-13, 2013. 11/10/2014

13 www.peakload.org

Residential Space heating – field study • occupied • bungalow 12 baseboards total and partial control several strategies tested

• load reductions whole house: 1,8 to 5,1 kW 4 thermostats: 0,9 to 2,6 kW

11/10/2014

14 www.peakload.org

Residential Space heating – building simulation and grid interation Grid impact of DR resource - simulated housing stock • Maximum allowable penetration rate depends on the shape of the grid’s overall demand profile and load control strategy

11/10/2014

Setpoint trajectories for optimized control Demand profiles for advanced strategies

15 www.peakload.org

Domestic Hot Water Heaters • DHWH stock characteristics Mostly customer owned Electric DHWH 93% Default setpoint 60°C Very cold water supply

• Research activities Load caracterization (lab testing and water withdraw profiles) Detailed load modeling (TRNSys) Grid integration modelling for DR potential evaluation Moreau, A., Control Strategy for Domestic Water Heaters during Peak Periods and its Impact on the Demand for Electricity, ICSGCE 2011, Energy Procedia 12 (2011) 1074-1082 11/10/2014

16 www.peakload.org

GIWH Innovation • Control of the lower element Standard tanks/thermostat retrofit capabilities

• DR potential 600 W/customer 5% less potential than shutting off power

• Benefits Maximizes hot water availability

• Proof of concept in SGZ – Boucherville (2 GIWH) 11/10/2014

17 www.peakload.org

Commercial and institutional (CI) customers Loads studied • HVAC

Research activities • DR potential evaluation Leduc, M.-A. (2013), Demand response in Quebec’s CI buildings: potential and strategies, ICEBO2013

• Simulation of HVAC controls optimization Lavigne, K., Daoud, A., Sansregret, S., Leduc, M.-A. (2014), Demand Response Strategies in a Small All-Electric Commercial Building in Quebec, Proceedings eSim2014

• Field study To be published at the Annual ASHRAE Conference 2015, abstract accepted

• Analytics • Baseline modeling www.peakload.org

CI HVAC control – Field study • Building characteristics

BANK

All-electric buildings DDC control

OFFICE

• DR strategies

RETAIL

o Customized DR strategies for each site o HVAC only, based on technical surveys, building simulation and analytics o Implemented into BAS, semi-ADR

Preconditionning Air intake limitation Zonal temperature adjustments Cycling *No ETS 11/10/2014

SCHOOL

RETAIL

19 www.peakload.org

CI HVAC control – Field study 50

100

40

80

30

60

kW

kW

o Jan-Feb 2014 o 4 to 6 events o Daily mean T -10°C to -24°C

120

60

20

40

10

20

0

0 0:00

2:00

4:00

6:00

8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00

profile

0:00

2:00

4:00

6:00

8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00

baseline

profile

baseline

• Significant load reduction AM

(31-66 %)

PM

• Acceptable impacts on comfort levels evaluation based on • Occupants surveys • BAS log data and additionnal sensors 11/10/2014

-6

-4

-2

0

2

W/pi2 20 www.peakload.org

CI – Analytics

2011 -9.23 (kW/°C) : (R2=0.94)

Classe 1, 31 jours

2012 -7.95 (kW/°C) : (R2=0.94)

Classe 1, 31 jours

40

500

500

450

450 Classe 2, 63 jours

40

Classe 2, 63 jours

400

450

450

400

400

400

350

350

350

10 20

350 20

30

10 20 300

Using 15-min data…

10/02/2013 24/02/2013

0 10 0

24/02/2013 10/03/2013

0 0

5 5

10/03/2013 24/03/2013

20

10 15 Classe 3, 33 jours Heure locale

20

5

250

0 0

5

10 15 Heure locale 250

20

10 15 Heure locale

20

Classe 4, 32 jours

200

Classe 3, 33 jours

40 24/03/2013 07/04/2013

21/04/2013 05/05/2013

kW

20 30

kW

kW

07/04/2013 21/04/2013

200

10 20

30 150 40 -40

-20

0 T (°C)

20

150 -40

40

-20

5

10 15 Heure locale

20

0 10 0

5

5

10 15 Classe 5, locale 44 jours Heure

20

0 0

10 15 Heure locale

20

0 0

5

10 15 Classe 6, locale 17 jours Heure

20

16/06/2013 30/06/2013

28/07/2013

40

150 -40

200

-20

0 T (°C)

20

40

150 -40

-20

0 T (°C)

20

40

kW

30 40

20 30

kW

kW kW

14/07/2013 28/07/2013

20

Classe 6, 17 jours

40

30 40

30/06/2013 14/07/2013

0 T (°C)

10 20

0 10 0

Classe 5, 44 jours

250

20 30

19/05/2013 02/06/2013

40

300

250

200

05/05/2013 19/05/2013

02/06/2013 16/06/2013

300

Classe 4, 32 jours

40

30 40

kW

le débutant Semaine le débutant Semaine

10 15 Heure locale

300

0 10 0

P (kW)

20 30

P (kW)

kW

30 40

kW P (kW) kW

kW

30 40

P (kW)

30/12/2012 13/01/2013

27/01/2013 10/02/2013

using non supervised clustering algorithms

2014 -8.07 (kW/°C) : (R2=0.85)

500

30/12/2012

13/01/2013 27/01/2013

• Operationnal patterns recognition

2013 -8.77 (kW/°C) : (R2=0.87)

500

10 20

20 30 10 20

D

L

M M J V Jour de la semaine

S

0 10 0

5

20

0 10 0

5

20

L

M M J V Jour de la semaine

S

5

10 15 Heure locale

20

0 0

10 15 Heure locale

D

0 0

10 15 Heure locale

5

10 15 Heure locale

20

Dominant response

• Linear regression models

FREQUENCY Null response

Negative response

Positive response

1

29/12/2013

12/01/14 0.8

16/02/14 12/01/2014

0.6

16/03/14 13/04/14

26/01/2014

0.4

11/05/14 0.2 15/06/14 1

23/02/2014

15

20

24

0

1

5

10

15

20

24

20/04/2014

50

1

-4

40

0.8

-6 -8 -10

30 20

-12

10

-14

0

1

5

10

15

20

24

K pos (kW/°C)

06/04/2014

-2

P base (x10kW)

K neg (kW/°C)

1

5

10

15

20

24

1

5

10

15

20

24

1

5

10

15

20

24

0.6 0.4 0.2

1

5

10

15

20

0

24

18/05/2014 1

0.8

10

0.8

0.6

5

0.6

2

R neg

15/06/2014

15

0.4

2

01/06/2014

1

R pos

Week starting

23/03/2014

04/05/2014

• VizBem – load profile vizualisation tool

10

MODEL PARAMETERS

09/03/2014

• Statistics (peak)

5

 (°C)

(detailed thermal response)

09/02/2014

0

0.4

29/06/2014 0.2

-5

0.2

13/07/2014 Sun Mon Tue Wed Thu Fri Sat Pos

Nul

Nég

0

1

5

10

15 Time

20

24

-10

1

5

10

15 Time

20

24

0

Time

Millette, J.; Sansregret, S.; SIMEB: Simplified interface to DOE2 and EnergyPlus – A user’s perspective – case study of an existing building, BS2011 : 12e Conférence bisannuelle de l’IBPSA, Sydney, 11-14 novembre 2011. Sansregret, S., Lavigne, K., Spreadsheet tool development for visualizing building performance and simulation data to help calibrating models, 2014 ASHRAE/IBPSA-USA Building Simulation Conference, Atlanta, GA, September 10-12, 2014

Simeb, https://www.simeb.ca/ 11/10/2014

21 www.peakload.org

FUTURE WORK

11/10/2014

22 www.peakload.org

Ongoing DR research projects… • HEMS with focus on heating optimization Experimental validation of optimal partial control and complex setpoint trajectories

• Optimization of DR resources dispatch Optimally dispatching resources to achieve desired results, building on strengths and limits of each one

• Dynamic DR in the CI market Modeling predictive control Intelligent load manager based on extended submetering

• HQ buildings to be DR-ready • Autonomous load contribution to spinning and non-spinning reserves Smart loads

• Industrial DR activities DR potential evaluation Small industrial solutions 11/10/2014

23 www.peakload.org

Acknowledgement Eric Le Courtois, researcher LTE, project manager, Residential DR Ahmed Daoud, researcher LTE, project manager, CI DR Hugues Fortin, reseracher LTE, procect manager, Industrial DR • Stéphane Alarie, researcher IREQ • Jean-François Boudreau, researcher IREQ • Stéphane Boyer, technician LTE • Sylvain Chénard, technician LTE • Guy Desbiens, IT, IREQ • Michaël Fournier, researcher LTE • Nedeltcho Kandev, researcher LTE • Sylvain Lahaie, researcher LTE 11/10/2014

• • • • •

André Laperrière, researcher LTE François Laurencelle, researcher LTE Karine Lavigne, researcher LTE Marie-Andrée Leduc, researcher LTE Sylvie Legendre, Valorisation de la technologie • Sylvain Martel, researcher LTE • Alain Poulin, researcher LTE

24 www.peakload.org