® ®® ® IRP Workshop Feb 9, 2015. ® February 9, 2015 - Workshop - Review of 2014 IRP Order -...

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IRP WorkshopFeb 9, 2015

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IRP Schedule

February 9, 2015 - Workshop- Review of 2014 IRP Order- December 30 and 31 Weather Event- Demand Forecast and 65% Calculation- Calculating COS Gas Prices

March 25, 2015 - Workshop- Wexpro Drilling and Compression Plans- Review of Upstream Gathering and

Transportation Contracts

2

®

IRP Schedule

May 4, 2015 – Workshop- Heating Season Review- Management of COS Gas for 2014 IRP year- Storage Update- Energy Efficiency Impact on Peak Day - Review of RFP

June 24, 2015 – Technical Conference

3

®

Review of Commission Order

Energy Efficiency Impact on Peak Day

TIMP/DIMP Inspection and Expenses

Demand Forecast and 65% Calculation

Shut-in and Exhibit Reporting

Calculation of COS Gas Price4

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®®

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December 30 and 31 Weather Event

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Temperatures and Demand

7

12/1/2

014

12/2/2

014

12/3/2

014

12/4/2

014

12/5/2

014

12/6/2

014

12/7/2

014

12/8/2

014

12/9/2

014

12/10/2

014

12/11/2

014

12/12/2

014

12/13/2

014

12/14/2

014

12/15/2

014

12/16/2

014

12/17/2

014

12/18/2

014

12/19/2

014

12/20/2

014

12/21/2

014

12/22/2

014

12/23/2

014

12/24/2

014

12/25/2

014

12/26/2

014

12/27/2

014

12/28/2

014

12/29/2

014

12/30/2

014

12/31/2

014

1/1/2

015

1/2/2

015

1/3/2

015

1/4/2

015

1/5/2

0150

10

20

30

40

50

60

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

Mean Transport (Dth) Sales (Dth) Total System(Dth)

Tem

p (D

egre

es F

)

Dem

and

(Dth

)

®

December 24 – 28, 2014

Due to Christmas, gas supply purchases and nominations were made on Dec 24th for gas days 25-29

On Dec 26th Questar Pipeline warned that nominations were expected to exceed pipeline capacity

On Dec 26th Questar Gas restricted customers to a 5% +/- tolerance effective Dec 28th until further notice (“OFO”)

Temperatures were near normal for this entire period with snow on Dec 25th

8

®

December 29, 2014

Temperatures dropped beginning on Monday Dec 29th

Weather forecasts continued to predict extreme cold temperatures and high winds for the next few days

The increase in demand for gas day 29 was met with increased withdrawals from Clay Basin and the aquifers

The Cycle 2 scheduled quantity report showed reductions for numerous transportation customers- This report now shows reductions by customer due to changes Questar Pipeline made

to the nominations process- These reductions occurred because the agent was utilizing interruptible capacity on

Questar Pipeline which had a constraint through the Coalville scheduling point- The agent was able to resolve the situation and no customers were contacted

9

®

December 30, 2014 “Icy Hell” Begins

Temperatures were extremely cold throughout the Questar Gas service territory- Demand exceeded the morning estimates due to colder temperatures and

high winds- Demand correlated well with the model used to forecast peak-day demand

Questar Gas used Clay Basin and aquifer storage along with Intraday purchases to manage the increased demand on the system

The Cycle 1 scheduled quantity report showed significant reductions to supply for transportation customers represented by four agents

▪ The reductions ranged from near 50% to 80% for agents based on nominations

10

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December 30, 2014

Questar Gas notified agents with reductions to fix their nominations for Cycle 2 or customers would be instructed to reduce usage starting at 8:00 am December 31, 2014- Notifications were made through emails, instant messages and phone

calls

The Cycle 2 scheduled quantity report indicated that reductions remained unresolved for two agent’s customers for gas day 31- At 9 pm, customers of these two agents were instructed to restrict their

usage to match their reduced nomination for December 31st, starting at 8:00 am

- One of these agents had their reductions resolved by morning and their customers were notified their supply was available

- The other agent did not have their reductions resolved until later the next day, and then those customers were notified their supply was available

11

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December 31, 2014 Extreme cold weather continued throughout the service territory and

producing regions- Cold temperatures were now impacting multiple production facilities

By 7:00 am, based on system concerns expressed by QGC Gas Control, the decision was made to call an interruption of all interruptible customers along the Wasatch Front and Wasatch Back- Customers were notified using the “rapid notify” system prior to 9:00 am- Agents were notified on an individual basis that interruptible customers were being

asked to reduce usage to match their firm amount- Nominating parties were then notified that the restriction for packing the Questar Gas

system had been lifted

By afternoon, system concerns were subsiding and the decision was made to allow interruptible customers to resume normal usage at 8:00 am January 1, 2015- Customers were notified using the “rapid notify” system at 5:00 pm

12

®

The end result

13

Gas DayTotal System

(Dth)Transport

(Dth)Total Sales

(Dth) Mean (ºF)12/30/2014 1,280,215 276,346 1,003,869 12

12/31/2014 1,148,547 217,969 930,578 11

December 30, 2014- Highest daily total system demand

▪ Previous high was 1,225,730 Dth on 1/14/2013

- Highest daily total Sales demand▪ Previous high was 997,135 Dth on 2/1/2011

System Interruption- Many customers complied with the interruption- Over 100 customers exceeded their firm amount and will be billed accordingly

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Demand Forecast and 65% Calculation

14

®

Calculation of 65%

Paragraph12 (a) “The Company and Wexpro will manage the combined cost-of-service production from Wexpro I properties and Wexpro II Trail Unit Acquisition Properties to 65% of Questar Gas’ annual forecasted demand identified in the Company’s Integrated Resource Plan (IRP).”- Settlement Stipulation Docket No. 13-057-13

15

®

Calculation of 65%

Paragraph12 (b) “The IRP plan year starting with the June 2015 through May 2016 IRP will be used to determine the initial annual forecasted demand.”- Settlement Stipulation Docket No. 13-057-13

16

®

Calculation of 65% - Denominator

17

IRP Forecast Demand

®

GS Forecasting Models

18

•Firm Sales

• Statistical Time Series

• Dynamic Regression

• End-use Modeling

® 19

Residential Demand(weather-normalized)

1-Mar-

85

1-Jan-86

1-Nov-8

6

1-Sep-87

1-Jul-8

8

1-May

-89

1-Mar-

90

1-Jan-91

1-Nov-9

1

1-Sep-92

1-Jul-9

3

1-May

-94

1-Mar-

95

1-Jan-96

1-Nov-9

6

1-Sep-97

1-Jul-9

8

1-May

-99

1-Mar-

00

1-Jan-01

1-Nov-0

1

1-Sep-02

1-Jul-0

3

1-May

-04

1-Mar-

05

1-Jan-06

1-Nov-0

6

1-Sep-07

1-Jul-0

8

1-May

-09

1-Mar-

10

1-Jan-11

1-Nov-1

1

1-Sep-12

1-Jul-1

340000000

45000000

50000000

55000000

60000000

65000000

70000000

75000000

Historical 12-Month Moving Total Demand

!2-M

onth

Tot

al D

th

® 20

Usage per Residential Customer(weather-normalized)

1-Mar-

85

1-Dec-

85

1-Sep-86

1-Jun-87

1-Mar-

88

1-Dec-

88

1-Sep-89

1-Jun-90

1-Mar-

91

1-Dec-

91

1-Sep-92

1-Jun-93

1-Mar-

94

1-Dec-

94

1-Sep-95

1-Jun-96

1-Mar-

97

1-Dec-

97

1-Sep-98

1-Jun-99

1-Mar-

00

1-Dec-

00

1-Sep-01

1-Jun-02

1-Mar-

03

1-Dec-

03

1-Sep-04

1-Jun-05

1-Mar-

06

1-Dec-

06

1-Sep-07

1-Jun-08

1-Mar-

09

1-Dec-

09

1-Sep-10

1-Jun-11

1-Mar-

12

1-Dec-

12

1-Sep-13

60

70

80

90

100

110

120

130

Moving 12-month Historical Usage Per Customer

Twel

ve-M

onth

Dth

Per

Cus

tom

er

® 21

Statistical Time Series

1-Mar-

85

1-Mar-

86

1-Mar-

87

1-Mar-

88

1-Mar-

89

1-Mar-

90

1-Mar-

91

1-Mar-

92

1-Mar-

93

1-Mar-

94

1-Mar-

95

1-Mar-

96

1-Mar-

97

1-Mar-

98

1-Mar-

99

1-Mar-

00

1-Mar-

01

1-Mar-

02

1-Mar-

03

1-Mar-

04

1-Mar-

05

1-Mar-

06

1-Mar-

07

1-Mar-

08

1-Mar-

09

1-Mar-

10

1-Mar-

11

1-Mar-

12

1-Mar-

13

1-Mar-

14

1-Mar-

15

1-Mar-

16

1-Mar-

17

1-Mar-

18

1-Mar-

19

1-Mar-

20

1-Mar-

21

1-Mar-

22

1-Mar-

23

1-Mar-

2460

70

80

90

100

110

120

130


Twel

ve-M

onth

Dth

Per

Cus

tom

er

® 22

Statistical Time Series

1-Mar-

85

1-Mar-

86

1-Mar-

87

1-Mar-

88

1-Mar-

89

1-Mar-

90

1-Mar-

91

1-Mar-

92

1-Mar-

93

1-Mar-

94

1-Mar-

95

1-Mar-

96

1-Mar-

97

1-Mar-

98

1-Mar-

99

1-Mar-

00

1-Mar-

01

1-Mar-

02

1-Mar-

03

1-Mar-

04

1-Mar-

05

1-Mar-

06

1-Mar-

07

1-Mar-

08

1-Mar-

09

1-Mar-

10

1-Mar-

11

1-Mar-

12

1-Mar-

13

1-Mar-

14

1-Mar-

15

1-Mar-

16

1-Mar-

17

1-Mar-

18

1-Mar-

19

1-Mar-

20

1-Mar-

21

1-Mar-

22

1-Mar-

23

1-Mar-

2460

70

80

90

100

110

120

130


Twel

ve-M

onth

Dth

Per

Cus

tom

er

® 23

Dynamic Regression

1-Mar-

85

1-Apr-8

6

1-May

-87

1-Jun-88

1-Jul-8

9

1-Aug-9

0

1-Sep-91

1-Oct-

92

1-Nov-9

3

1-Dec-

94

1-Jan-96

1-Feb-97

1-Mar-

98

1-Apr-9

9

1-May

-00

1-Jun-01

1-Jul-0

2

1-Aug-0

3

1-Sep-04

1-Oct-

05

1-Nov-0

6

1-Dec-

07

1-Jan-09

1-Feb-10

1-Mar-

11

1-Apr-1

2

1-May

-13

1-Jun-14

1-Jul-1

5

1-Aug-1

6

1-Sep-17

1-Oct-

18

1-Nov-1

9

1-Dec-

20

1-Jan-22

1-Feb-23

1-Mar-

2460

70

80

90

100

110

120

130

5

6

7

8

9

10

11

12

Moving 12-month Historical Usage Per Customer Gas Service Rate

Twel

ve-M

onth

Dth

Per

Cus

tom

er

Real

Gen

eral

Ser

vice

Win

ter R

ate

® 24

Dynamic Regression

1-Mar-

85

1-Apr-8

6

1-May

-87

1-Jun-88

1-Jul-8

9

1-Aug-9

0

1-Sep-91

1-Oct-

92

1-Nov-9

3

1-Dec-

94

1-Jan-96

1-Feb-97

1-Mar-

98

1-Apr-9

9

1-May

-00

1-Jun-01

1-Jul-0

2

1-Aug-0

3

1-Sep-04

1-Oct-

05

1-Nov-0

6

1-Dec-

07

1-Jan-09

1-Feb-10

1-Mar-

11

1-Apr-1

2

1-May

-13

1-Jun-14

1-Jul-1

5

1-Aug-1

6

1-Sep-17

1-Oct-

18

1-Nov-1

9

1-Dec-

20

1-Jan-22

1-Feb-23

1-Mar-

2460

70

80

90

100

110

120

130

5

6

7

8

9

10

11

12

Moving 12-month Historical Usage Per Customer Gas Service Rate

Twel

ve-M

onth

Dth

Per

Cus

tom

er

Real

Gen

eral

Ser

vice

Win

ter R

ate

® 25

Dynamic Regression

1-Mar-

85

1-Apr-8

6

1-May

-87

1-Jun-88

1-Jul-8

9

1-Aug-9

0

1-Sep-91

1-Oct-

92

1-Nov-9

3

1-Dec-

94

1-Jan-96

1-Feb-97

1-Mar-

98

1-Apr-9

9

1-May

-00

1-Jun-01

1-Jul-0

2

1-Aug-0

3

1-Sep-04

1-Oct-

05

1-Nov-0

6

1-Dec-

07

1-Jan-09

1-Feb-10

1-Mar-

11

1-Apr-1

2

1-May

-13

1-Jun-14

1-Jul-1

5

1-Aug-1

6

1-Sep-17

1-Oct-

18

1-Nov-1

9

1-Dec-

20

1-Jan-22

1-Feb-23

1-Mar-

2460

70

80

90

100

110

120

130

5

6

7

8

9

10

11

12

Moving 12-month Historical Usage Per Customer ForecastGas Service Rate

Twel

ve-M

onth

Dth

Per

Cus

tom

er

Real

Gen

eral

Ser

vice

Win

ter R

ate

® 26

Customer Growth

19911992

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

20112012

20132014

20152016

20172018

20192020

20212022

20232024

2025

-3000

2000

7000

12000

17000

22000

27000

Historical Additions

® 27

Customer Growth

19911992

19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

20112012

20132014

20152016

20172018

20192020

20212022

20232024

2025

-3000

2000

7000

12000

17000

22000

27000

Historical Additions Forecast

® 28


1-Mar-

85

1-Apr-8

6

1-May

-87

1-Jun-88

1-Jul-8

9

1-Aug-9

0

1-Sep-91

1-Oct-

92

1-Nov-9

3

1-Dec-

94

1-Jan-96

1-Feb-97

1-Mar-

98

1-Apr-9

9

1-May

-00

1-Jun-01

1-Jul-0

2

1-Aug-0

3

1-Sep-04

1-Oct-

05

1-Nov-0

6

1-Dec-

07

1-Jan-09

1-Feb-10

1-Mar-

11

1-Apr-1

2

1-May

-13

1-Jun-14

1-Jul-1

5

1-Aug-1

6

1-Sep-17

1-Oct-

18

1-Nov-1

9

1-Dec-

20

1-Jan-22

1-Feb-23

1-Mar-

2440000000

45000000

50000000

55000000

60000000

65000000

70000000

75000000

80000000

85000000

Historical 12-Month Moving Total Demand

!2-M

onth

Tot

al D

th

® 29


1-Mar-

85

1-Apr-8

6

1-May

-87

1-Jun-88

1-Jul-8

9

1-Aug-9

0

1-Sep-91

1-Oct-

92

1-Nov-9

3

1-Dec-

94

1-Jan-96

1-Feb-97

1-Mar-

98

1-Apr-9

9

1-May

-00

1-Jun-01

1-Jul-0

2

1-Aug-0

3

1-Sep-04

1-Oct-

05

1-Nov-0

6

1-Dec-

07

1-Jan-09

1-Feb-10

1-Mar-

11

1-Apr-1

2

1-May

-13

1-Jun-14

1-Jul-1

5

1-Aug-1

6

1-Sep-17

1-Oct-

18

1-Nov-1

9

1-Dec-

20

1-Jan-22

1-Feb-23

1-Mar-

2440000000

45000000

50000000

55000000

60000000

65000000

70000000

75000000

80000000

85000000

Historical 12-Month Moving Total Demand Forecast

!2-M

onth

Tot

al D

th

® 30

End-use

Water Heater Range Dryer Furnace0

10

20

30

40

50

60

70

Annual Consumption

Dth

® 31

End-use

• Distributes housing by size and shell quality (year built, insulation grade)

• Distributes end-use segments by appliance efficiency

®

Calculation of 65%

32

IRP Forecast Demand

IRP forecast demand is shown in section 3 and exhibits 3.10 and 3.11 of the IRP

®

2014 IRP Exhibit 3.10

33

®

2014 IRP Exhibit 3.11

34

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

SYSTEM GS

74.086

76.573

79.43

83.875

86.947

84.053

85.719

86.769

85.15

86.085

90.379

91.10526

91.445255

94.248445

92.674402

97.6

97 97 101

101

102

103

104

106

107

108

111

112

114

116

116

118

NON-GS SALES

6.439

8.911

9.271

8.614

9.523

9.685

9.866

10.356

10.753

10.687

9.713

8.79092

13.111037

12.478552

10.880363

10.3

10 10 11 10 9 9 9 9 9 9 9 9 9 9 9 9

TRANS

53.105

51.382

59.569

49.499

51.312

55.461

51.643

54.836

54.624

46.459

38.341

31.80262

31.204752

35.544794

53.750377

62.3

58 59 53 62 65 83 89 89 89 90 90 90 90 91 91 91

25

75

125

175

225

TEMP ADJUSTED THROUGHPUTDTH (MILLIONS)

Calendarized Tactical Plan Base Case Fore-cast

Ex

hib

it

3.1

1

®

Calculation of 65%

35

Actual Company Production

IRP Forecast Demand

IRP Demand is shown in exhibits 3.10 and 3.11 of the IRP

®

Total QGC Gas Supply

REDACTED

®

Production Supply Chain

37

Processing

Gathering

“Into Pipe” City GateWell Head

IRP Year Dth= 65%

Actual Well-head Production Volumes

Transportation

® ®® ® IRP Workshop Feb 9, 2015. ® February 9, 2015 - Workshop - Review of 2014 IRP Order -...

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Transcript of ® ®® ® IRP Workshop Feb 9, 2015. ® February 9, 2015 - Workshop - Review of 2014 IRP Order -...