which state is yoda?

3
Viewpoint Which state is Yoda? Matt Croucher n Seidman Research Institute, W.P. Carey School of Business, Arizona State University, USA article info Article history: Received 29 June 2011 Accepted 13 December 2011 Available online 31 December 2011 Keywords: Economic impact JEDI Solar abstract As Yoda famously said ‘‘Size matters not,y. Look at me. Judge me by size, do you’’. If indeed we do judge by size then Pennsylvania appears to be the Yoda of solar deployment. & 2011 Elsevier Ltd. All rights reserved. 1. Introduction There is a growing desire by public-policy makers to understand the economic impact caused by solar generation being constructed and operated within a particular state. Also, many solar proponents argue that building solar generation within a particular state will reduce the flow of ‘‘energy dollars’’ that leave the state in form of resource payments for things like oil, natural gas and coal. The National Renewable Energy Laboratory (NREL) has created several excel-based models that potentially assist with understanding the economic impact of solar deployment. 1 These Jobs and Economic Development Impact (JEDI) models 2 are publically available for various types of technologies including wind, natural gas, solarconcentrating solar power (CSP) and photovoltaic (PV) and coal. The purpose of this brief is to use one of the JEDI models availablewe selected the photovoltaic modelto answer a simple question. Which state for a given amount of solar deploy- ment leads to the greatest state economic impact? Simply put, which state is the most powerful JEDI? Which state is Yoda? Section 2 describes our methodology and results. Section 3 provides some conclusions and warnings about the results. 2. JEDI modeling results The JEDI model used was the JEDI–Photovoltaics release number PV1.10.01. Our methodology was simple. We left all default variables unchanged and simply changed the State in which the assumed construction and operation of the PV systems would take place. 3,4 Thus, for each state examined the year of construction was 2010, the average name plate size of the PV system was 2.5 kilo- watts (KW), 100 installations were assumed, all systems were new residential construction and all monetary values are in 2008 dollars. Table 1 summarizes the results. Using the total economic output created during construction as the metric, which determines overall rankings then it appears that Pennsylvania, Illinois, Minnesota, Ohio and Wisconsin are states that would derive the greatest level of economic activity from solar generation being deployment within their state. 5 Interestingly, Arizona, a state with the highest solar insola- tion, 6 is ranked the lowest in terms of economic impact from the construction and operation of photovoltaic systems. California, another state with a high level of solar insolation, is ranked 38th. Contents lists available at SciVerse ScienceDirect journal homepage: www.elsevier.com/locate/enpol Energy Policy 0301-4215/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2011.12.031 n Tel.: þ1 480 965 4198; fax: þ1 480 965 0748. E-mail address: [email protected] 1 These models utilize information from interviews with project developers and industry experts as well as various inputs from IMPLAN. IMPLAN is a sophisticated input–output (IO) model that is often used to examine the economic impact of various situations. 2 Hence the title reference to Yodapossibly the greatest JEDI. 3 That is not to say that none of the parameters in the model ever changed. For instance when the state was changed from California to Arizona some of the default underlying parameters did change but these were pre-determined within the model itself and thus left unchanged. Essentially we did not override any of the internal settings. 4 NREL does allow changes in the default settings and also note within their literature that ‘‘To the extent that a user has and can incorporate project-specific data as well as the share of spending expected to occur locally, the results are more likely to better reflect the actual impacts from the specific project.’’ 5 If jobs created during construction was used then New Mexico, Ohio, Vermont South Dakota and Idaho are the top five. If jobs during operations was the ranking metric, New Mexico, Idaho, Vermont, Pennsylvania and Oklahoma would be the top five. In all cases Arizona would be in the bottom 10–20. 6 See NREL insolation maps. Energy Policy 42 (2012) 613–615

Upload: matt-croucher

Post on 05-Sep-2016

215 views

Category:

Documents


0 download

TRANSCRIPT

Energy Policy 42 (2012) 613–615

Contents lists available at SciVerse ScienceDirect

Energy Policy

0301-42

doi:10.1

n Tel.:

E-m1 Th

and ind

sophisti

impact2 H

journal homepage: www.elsevier.com/locate/enpol

Viewpoint

Which state is Yoda?

Matt Croucher n

Seidman Research Institute, W.P. Carey School of Business, Arizona State University, USA

a r t i c l e i n f o

Article history:

Received 29 June 2011

Accepted 13 December 2011Available online 31 December 2011

Keywords:

Economic impact

JEDI

Solar

15/$ - see front matter & 2011 Elsevier Ltd. A

016/j.enpol.2011.12.031

þ1 480 965 4198; fax: þ1 480 965 0748.

ail address: [email protected]

ese models utilize information from intervi

ustry experts as well as various inputs f

cated input–output (IO) model that is often u

of various situations.

ence the title reference to Yoda—possibly the

a b s t r a c t

As Yoda famously said ‘‘Size matters not,y. Look at me. Judge me by size, do you’’. If indeed we do judge

by size then Pennsylvania appears to be the Yoda of solar deployment.

& 2011 Elsevier Ltd. All rights reserved.

1. Introduction

There is a growing desire by public-policy makers to understandthe economic impact caused by solar generation being constructedand operated within a particular state. Also, many solar proponentsargue that building solar generation within a particular state willreduce the flow of ‘‘energy dollars’’ that leave the state in form ofresource payments for things like oil, natural gas and coal.

The National Renewable Energy Laboratory (NREL) has createdseveral excel-based models that potentially assist with understandingthe economic impact of solar deployment.1 These Jobs and EconomicDevelopment Impact (JEDI) models2 are publically available forvarious types of technologies including wind, natural gas, solar—

concentrating solar power (CSP) and photovoltaic (PV) and coal.The purpose of this brief is to use one of the JEDI models

available—we selected the photovoltaic model—to answer asimple question. Which state for a given amount of solar deploy-ment leads to the greatest state economic impact? Simply put,which state is the most powerful JEDI? Which state is Yoda?

Section 2 describes our methodology and results. Section 3provides some conclusions and warnings about the results.

3 That is not to say that none of the parameters in the model ever changed. For

instance when the state was changed from California to Arizona some of the

default underlying parameters did change but these were pre-determined within

the model itself and thus left unchanged. Essentially we did not override any of

the internal settings.

2. JEDI modeling results

The JEDI model used was the JEDI–Photovoltaics releasenumber PV1.10.01. Our methodology was simple. We left all

ll rights reserved.

ews with project developers

rom IMPLAN. IMPLAN is a

sed to examine the economic

greatest JEDI.

default variables unchanged and simply changed the State inwhich the assumed construction and operation of the PV systemswould take place.3,4

Thus, for each state examined the year of construction was2010, the average name plate size of the PV system was 2.5 kilo-watts (KW), 100 installations were assumed, all systems werenew residential construction and all monetary values are in 2008dollars.

Table 1 summarizes the results.Using the total economic output created during construction

as the metric, which determines overall rankings then it appearsthat Pennsylvania, Illinois, Minnesota, Ohio and Wisconsin arestates that would derive the greatest level of economic activityfrom solar generation being deployment within their state.5

Interestingly, Arizona, a state with the highest solar insola-tion,6 is ranked the lowest in terms of economic impact from theconstruction and operation of photovoltaic systems. California,another state with a high level of solar insolation, is ranked 38th.

4 NREL does allow changes in the default settings and also note within their

literature that ‘‘To the extent that a user has and can incorporate project-specific data

as well as the share of spending expected to occur locally, the results are more likely to

better reflect the actual impacts from the specific project.’’5 If jobs created during construction was used then New Mexico, Ohio,

Vermont South Dakota and Idaho are the top five. If jobs during operations was

the ranking metric, New Mexico, Idaho, Vermont, Pennsylvania and Oklahoma

would be the top five. In all cases Arizona would be in the bottom 10–20.6 See NREL insolation maps.

Table 1Economic impact associated with PV deployment across the States.

Source: JEDI.

Ranking State Construction and installation period Operation period

Jobs Earnings $000 Output $000 Annual jobs Annual earnings $000 Annual output $000

1 PENNSYLVANIA 28.98 1214.37 3220.16 0.20 8.14 22.62

2 ILLINOIS 27.65 1226.09 3150.66 0.18 7.87 21.09

3 MINNESOTA 29.36 1198.14 3131.11 0.03 1.85 2.99

4 OHIO 31.32 1185.48 3111.35 0.03 1.79 2.82

5 WISCONSIN 30.08 1097.74 2915.96 0.03 1.83 2.96

6 MARYLAND 25.62 1148.61 2904.59 0.03 1.85 2.93

7 VERMONT 30.50 1073.91 2896.05 0.20 6.87 18.63

8 MISSOURI 28.02 1057.00 2872.99 0.20 7.25 20.32

9 NEW YORK 22.17 1110.25 2865.26 0.03 1.89 3.04

10 NEW MEXICO 31.50 1046.24 2853.82 0.22 7.28 20.34

11 MASSACHUSETTS 23.19 1148.61 2847.50 0.03 1.89 2.99

12 NEVADA 24.01 1058.76 2834.27 0.03 1.78 2.83

13 TENNESSEE 26.14 1014.28 2829.65 0.18 6.74 19.52

14 OREGON 27.08 1033.37 2824.56 0.03 1.81 2.96

15 NEBRASKA 29.33 1015.68 2808.39 0.19 6.59 18.67

16 FLORIDA 26.11 1076.35 2807.66 0.03 1.86 3.03

17 HAWAII 26.85 1012.79 2753.21 0.17 6.71 18.69

18 WASHINGTON 23.95 1029.07 2743.80 0.15 6.26 17.17

19 UTAH 27.55 1001.28 2743.34 0.19 6.56 18.56

20 OKLAHOMA 29.18 970.03 2740.97 0.20 6.37 18.71

21 MICHIGAN 26.02 1045.96 2723.97 0.03 1.80 2.87

22 GEORGIA 24.36 1023.36 2723.03 0.16 6.54 18.18

23 NEW JERSEY 20.62 1044.11 2718.34 0.03 1.82 2.86

24 COLORADO 23.82 987.71 2716.32 0.16 6.27 18.14

25 IDAHO 30.22 958.43 2715.94 0.20 6.23 18.33

26 LOUISIANA 27.26 999.18 2711.10 0.03 1.78 2.84

27 TEXAS 23.54 960.67 2705.83 0.03 1.76 2.87

28 SOUTH DAKOTA 30.26 950.70 2693.61 0.03 1.77 2.87

29 ALABAMA 27.57 998.09 2689.52 0.18 6.43 18.02

30 KANSAS 27.81 980.30 2682.41 0.03 1.78 2.87

31 ARKANSAS 29.57 983.02 2680.56 0.20 6.34 18.11

32 INDIANA 28.00 1001.47 2679.90 0.18 6.48 18.03

33 ALASKA 25.23 955.57 2645.85 0.16 6.11 17.52

34 CONNECTICUT 20.29 1016.65 2627.86 0.03 1.85 2.93

35 NORTH CAROLINA 26.76 1002.91 2623.58 0.06 2.69 5.65

36 VIRGINIA 23.51 1042.79 2623.56 0.15 6.50 16.92

37 NORTH DAKOTA 29.72 946.06 2620.46 0.03 1.76 2.84

38 CALIFORNIA 21.19 960.01 2615.08 0.03 1.82 2.97

39 KENTUCKY 27.32 979.22 2613.60 0.18 6.34 17.36

40 NEW HAMPSHIRE 23.21 991.12 2610.10 0.16 6.62 17.79

41 MISSISSIPPI 28.92 941.65 2607.43 0.20 6.21 17.63

42 MAINE 26.60 939.81 2606.61 0.18 6.15 17.49

43 MONTANA 29.26 898.86 2598.32 0.03 1.72 2.80

44 IOWA 28.67 951.32 2592.71 0.03 1.77 2.85

45 DISTRICT OF COLUMBIA 18.43 1160.13 2588.72 0.11 7.04 15.39

46 SOUTH CAROLINA 27.21 974.81 2582.86 0.17 6.12 16.73

47 WEST VIRGINIA 28.40 950.02 2567.35 0.19 6.19 17.08

48 WYOMING 26.04 844.12 2485.26 0.17 5.31 15.53

49 RHODE ISLAND 22.59 945.61 2443.61 0.14 5.85 14.99

50 DELAWARE 21.24 966.40 2402.47 0.13 5.77 14.36

51 ARIZONA 21.33 880.30 2372.78 0.03 1.81 2.95

M. Croucher / Energy Policy 42 (2012) 613–615614

3. Conclusion

The purpose of this study was to examine the economic impactof photovoltaic solar electric systems being deployed acrossstates. Using the JEDI model created by NREL we find thatPennsylvania, Illinois, Minnesota, Ohio and Wisconsin are statesthat enjoy relatively large amounts of economic activity duringconstruction (which tends to be when the majority of economicactivity from the construction and operation of PV systems willoccur).7

7 For instance assuming a PV system last 30 years the total economic output

from the operations phase in Pennsylvania is approximately $680 million whilst

during the construction and installation phase the economic output is estimated

to be $3.2 billion—over 4 times as much as the operations phase.

Thus, it initially appears that from a national stimulus point ofview more solar deployment should occur within these states.Also, Arizona is ranked last in terms of the overall economicactivity from the construction, installation and operation of PVsystems.

However, caution should be taken when interpreting theresults from Section 2. First the JEDI models only look at grosseconomic activity caused by the deployment of PV systems.8 Thatis, no consideration is taken to evaluate how these systems willbe paid for, what generation facilities will the PV systems offset

8 Also the JEDI models are only a ‘‘stripped-down’’ version of IMPLAN which

itself is a more complex input-output model.

M. Croucher / Energy Policy 42 (2012) 613–615 615

and the potential resulting impact on electricity prices—whichthemselves will cause changes in the state’s overall economicactivity.9

Also, the JEDI model for PV systems ignores the impactcapacity factor differences across the States may have on theefficiency of the systems, the resulting output generated and theresulting levelized cost of electricity as well as rates of returns onthe PV systems.

That is not to say the JEDI models are not useful tools. For onethey highlight some of the numerous factors that have to be

9 In a relatively simplistic manner the implicit assumption made is that the

solar generation that is deployed is for export purposes – thus the costs of the

system are borne by people outside of the state.

considered when examining the economic impact of solar gen-eration. They also illustrate how the economic impact from solargeneration deployment will differ across states due, in part, to thevarying nature of each individual state’s economy.

Thus, to fully understand the economic impact solar deploy-ment would have on a state’s overall economy takes carefulconsideration and attempts to simplify the analysis can lead tosurprising results such as the ones found within this paper,namely Arizona is not a desirable state in which to deploy solarfrom an national economic development stand-point.