The Virginia Center for Wind Energy at James Madison University, supported by the National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE), performed a study that applied the new offshore Jobs and Economic Development Impacts (JEDI) model to estimate the economic impacts associated with potential offshore wind power development off the coasts of Virginia, North Carolina, South Carolina, and Georgia. The Southeast region presents an ample wind resource in waters beyond 12 miles from the coast. According to the American Wind Energy Association, the region currently employs an estimated 11 percent of the total U.S. wind workforce. This analysis finds that construction costs for offshore wind within the region are among the lowest in the nation, suggesting a competitive advantage for this industry.
The major attributes associated with the region were identified and analyzed in order to define likely scenarios for offshore wind development in the region. Relevant data and justifiable assumptions were made to develop five scenarios for JEDI analysis.
The offshore wind industry represents a major opportunity to provide clean, stable-priced energy using a domestic renewable resource, while promoting significant job growth and economic development. The industry is currently being driven by individual state policies, with Mid-Atlantic and Northeastern states all competing to become the “hub” of this new industry. While state-by-state competition can drive down costs, a regional approach would realize the full potential of the industry. Some of the benefits of a coordinated regional approach include:
• reduction of ratepayer impacts by spreading costs over a wider base
• the ability to spread costs and share lessons learned
• coordination of research, resource assessment and environmental studies
• expansion of the scope of transmission integration analyses
• allocation of economic development resources based on comparative strengths
• aggregated or collaborative procurement could result in lower energy costs
In this study, a regional approach was adopted in the development of scenarios for application to the Jobs and Economic Development Impacts (JEDI) model, to investigate the potential economic impacts of offshore wind in the Southeast. A regional overview highlighting the comparative strengths of the Southeast region—Virginia, North Carolina, South Carolina and Georgia—is provided in Section 2. The JEDI model is described in Section 3. In Section 4, the development of three distinct, justifiable offshore wind energy scenarios for the Southeast is discussed. Finally, in Sections 5 and 6, the results of JEDI model runs are presented followed by conclusions.
2. Regional Overview
In order to be able to develop reasonable justifiable assumptions for the offshore wind industry in the Southeast—defined in this study to be Virginia (1) (2) (3) (4), North Carolina (5), South Carolina (6) (7) and Georgia (8) (9), the major characteristics of the region must be understood. These include Federal and State activities, the wind resource, transmission infrastructure, ports and the existing supply chain in the region. Each state was researched thoroughly, through reliable sources as well as collaboration with local and regional experts in the region.
Federal and State Activities
The Bureau of Ocean Energy Management (BOEM) manages the exploration and development of the nation’s offshore resources. BOEM runs a number of offshore Renewable Energy Programs and it grants leases, easements, and rights-of-way for orderly, safe, and environmentally responsible renewable energy development activities.
To assist the development of offshore wind energy in the region, BOEM established Renewable Energy Task Forces in Virginia, North Carolina and South Carolina, to facilitate intergovernmental communications regarding outer continental shelf renewable energy activities.
According to the National Renewable Energy Laboratory (NREL), the Southeast region represent 45 percent of the total East Coast offshore wind resource and 82 percent of the resource in shallow water and more than 12 miles offshore, as shown in Figure 1. (10) NREL resource maps show that average wind speeds are slightly lower in the southern states. However, the most important metric is ultimately the Levelized Cost of Energy (LCOE), and the Southeast has numerous advantages that should result in lower LCOE in the region.
The Southeastern states represent five of the six largest electricity markets on the East Coast with high per-capita electricity consumption and five of the six fastest growing populations (see Figure 2) (11). The low electricity rates in the region attract energy-intensive industries, which points to a high demand growth rate and the ability to accommodate long-term, large-scale offshore wind energy development.
The U.S. Energy Information Administration (EIA) estimates that the Southeast region offers the lowest construction costs for offshore wind energy among East Coast states, as shown in Figure 3 (12). This advantage would result in lower capital and expenditures (CAPEX) and energy costs from offshore wind and a competitive advantage for manufacturers that locate facilities in the region.
Currently, electricity supplied in the Southeast primarily comes from coal, nuclear and natural gas (11)—all technologies that are susceptible to fuel price volatility and large-scale outages. Dispatchable generating technologies, such as coal, gas-combined-cycle and nuclear can be controlled by the systems operator and can be switched on and off based on their economic attractiveness to supply electricity and to supply network reliability services. Electricity rates can change quickly as the demand for electricity changes throughout the day, while power generation must continuously be adjusted to match electrical load to avoid outages. Non-dispatchable generating technologies such as wind energy would diversify the region’s electricity supply and provide long-term, stable-priced energy by putting less demand on conventional technologies to match the electrical load.
Infrastructure and Workforce
The Southeast is home to some of the largest and industrious ports and logistics infrastructure in the United States, including ports at Norfolk Harbor (VA), Newport News (VA), Morehead City (NC), Wilmington (NC), Charleston (SC), and Savannah (GA) (13). The region has a highly skilled manufacturing and maritime workforce and employs thousands of people in the land-based wind industry, despite having no large-scale wind plants. (14) (15)
3. The Offshore Wind Jedi Model
The Offshore Wind Jobs and Economic Development Impact Model (JEDI) was developed by the National Renewable Energy Laboratory (NREL) in order to demonstrate the magnitude of economic impacts associated with developing and operating offshore wind power plants in the United States. (16)
The JEDI model uses input-output analysis to estimate the number of jobs, income (wages and salary), and economic activity that may be supported in the state (or region) from the project (1). Three separate impacts are examined,
• Project Development and Onsite Labor Impacts
• Turbine and Supply Chain Impacts
• Induced Impacts
In order to accomplish this analysis, multipliers and expenditure patterns were used to derive these results. These regional multipliers for employment, earnings, and output and personal expenditure patterns were derived from the Impact Analysis for Planning (IMPLAN) model 3.0 (17).
JEDI utilizes either default or user-supplied construction cost data, operating cost data as well as data pertaining to the percentage of goods and services acquired in the region to produce outputs. From a broad perspective, JEDI input variables can be classified into three main categories
• Market and Deployment—The number and size of wind turbines deployed each year.
• Regional Investment—The percentage, for each component or service, which is being acquired or produced regionally.
• Cost—The cost (per MW capacity) of an offshore wind project.
JEDI provides information to understand the magnitude of the gross economic impacts within the region being analyzed, including construction-related spending and operations and maintenance, as well as the portion of the spending that could occur regionally. JEDI reports the local jobs in Full-Time Equivalents (FTEs), earnings and output supported as a result of the project for the construction phase and for the ongoing operations phase. Construction phase impacts are assumed to occur of the equivalent of one year, while O&M impacts are assumed to be ongoing for the life of the facility.
First, the offshore wind JEDI model is intended to construct a reasonable profile of expenditures and demonstrates the magnitude of gross economic impacts, and is an estimate, not a prediction.
Second, the JEDI is a static model that relies on inter-industry relationships and personal consumption patterns and does not account for supply-side changes such as inflation, changes in technology, taxes, or subsidies. Additionally, the model does not consider constraints on labor, goods or money.
Third, the model was not designed to provide cash flow projections or for use as a cash flow analysis tool and results do not measure of project viability or profitability.
Finally, the analysis assumes that sufficient revenues are generated for equity and debt repayment and annual operating expenditures. (1)
4. Scenario Development
As discussed in Section 3, the JEDI model is built around three major variables – Market and Deployment, Regional Investment, and Cost, based on information gathered and other similar studies. (18) For each, three distinct ‘paths’ with varying rates for how these variables change over time were developed. Three distinct scenarios, running from 2020-2030 for offshore wind energy in the Southeast were generated, and JEDI was run for each year.
Market and Deployment
For Market and Deployment, a conservative, a moderate and an aggressive approach to the deployment of offshore wind turbines in the Southeast region were created. An analysis of the historical growth rates for electricity capacity, as shown in Table 1, indicates that this is around 2.2GW/year. It was assumed that the Southeast could support a maximum build-in rate of around 1.1GW/year.
For Low Market and Deployment, as shown in Table 2, investment in the offshore wind industry was assumed to be very conservative, defined by pilot projects and small wind farms. For Medium Market and Deployment, as in Table 3, a moderate level of investment in the industry was assumed. Initially, this path is similar to that of the low growth path, with a more consistent level of growth being observed in the later years of the model run. For High Market and Deployment, as in Table 4, an aggressive level of offshore wind turbine deployment was assumed, and assumed a large percentage or new power-generating plants derived from offshore wind facilities.
As in the case of Market and Deployment, three different paths for how the regional supply chain could develop were built. The higher the regional share percentage in a specific line item, say wind turbine blades, the more money is being circulated into the regional economy, thereby creating more regional jobs.
Each individual component was examined separately when determining its potential for regional sourcing. The regional share of many of these components and services were not expected to change over time, called static components and services. A list of these, with regional share percentages and justifications are given in Figure 5. Components and services of which the regional share is expected to vary over time are called dynamic components and services, and are discussed in the next section. Table 5
Dynamic Components and Services
For the Low Regional Investment path, it was assumed that the development of the regional supply chain is minimal due to uncertainties in the industry. However, due to the presence of manufacturers and developers already in the region, some regional contributions are expected, but development of supply chain is slow.
Initially, the Medium Regional Investment path was assumed to be similar to the low path, but higher growth rates are applied, as more of the larger components are manufactured regionally, and as expertise is gained. Approximately half of manufacturing and services are assumed to be regional by 2030. Table 6
The High Regional Investment path assumed immediate and significant regional investment into the offshore wind industry, resulting in a rapid development of the supply chain. Nearly all components and services are regionally sourced by 2030. A summary of all three Regional Investment paths are given is Figure 6.
Three simple Cost reduction models were established for application to the JEDI model, which may occur due to technological advancements, economies of scale, and other factors. These paths, establish upper and lower bounds for cost reduction in the Southeast. A baseline Cost of $5,600/MW in 2015 was established based on 2010 Energy Information Administration (EIA) estimates for the industry in the region (12).
For the High Cost path, there is limited development in offshore wind energy technologies, and a cost reduction of 3.5% every 5 years was applied, resulting in an overall cost reduction of around 10%. For the Medium Cost path, a more aggressive cost reduction model was applied, representing more significant technological advances. A cost reduction of 7.2% every 5 years was applied, resulting in an overall cost reduction of around 20%. For the Low Cost path, the most aggressive cost reduction model was applied, representing optimal improvements in the technology. The average cost of offshore wind is assumed to decrease by 11.2% every 5 years, for an overall cost reduction of around 30%. A summary of the cost reduction models are given in Table 7.
Using this method, three combinations of these variables were combined that best represented all the combinations and to reduce redundancy. Scenario A, shown in Table 8, is the most conservative of the three scenarios, representing a small industry with limited regional investment due to uncertainties. As such, much of the labor and capital is outsourced and the high cost reduction model was adapted. Scenario B, as shown in Table 9, represents an ‘average case’ marked by moderate and steady growth in both Market and Deployment and Regional Investment. This growth helps spurn advancements and efficiencies and the Medium Cost reduction model was applied. The details of Scenario C are given in Table 10 and represent the ‘best case’ scenario for the offshore wind industry. Therefore, a high Market and Deployment and Regional Investment paths were selected, presenting a situation where the industry grows very quickly, resulting in a Low Cost reduction model being selected for this scenario. Table 10
Construction is highly labor intensive, requiring a large number of workers to complete a project, supporting thousands of jobs. However, unless the offshore wind market is robust with multiple projects in the pipeline, these jobs may cease to exist after construction.
For Scenario A, the offshore wind industry is projected to support around 1,000 FTEs, increasing to over 4,000 FTEs in 2030, as shown in Figure 4. In other words, the industry is expected to require four times more labor after 10 years, despite conservative increases in Market and Deployment and Regional Investment. Many of the total jobs created are from supply chain and induced impacts.
Scenario B, as shown in Figure 5, shows significantly higher projected jobs throughout the modeling period, increasing from under 4,000 FTEs in 2020 to over 18,000 FTEs in 2030. Scenario C, as shown in Figure 6, projects the most FTEs by a significant margin, with the 2020 estimate of 15,000 FTEs being very close to the 2030 value of Scenario B. By 2030, if all the assumptions made hold, this Scenario projects over 40,000 FTEs.
An important metric to consider in order to be able to directly compare jobs supported by each scenario is the normalized FTEs per MW. As seen in Figure 7, this will show how more Regional Investment into the offshore wind supply chain will support more jobs per MW installed than if the supply chain were developed outside the region. For instance, in 2020, where the percentage investment during the construction phase is comparable for all three scenarios, the normalized FTEs/MW values are similar, ranging from around 14 FTEs/MW in Scenario A to around 19 FTEs/MW in Scenario C.
Since the three scenarios follow different regional investment growth patterns, the rate at which the normalized FTEs/MW grow accordingly. Scenario A assumes marginal increases in regional investment – therefore the model suggests that around 19 FTEs/MW would be supported by 2030. On the other hand, Scenario C assumed an aggressive investment growth pattern, and this is reflected in the FTEs/MW value over time, which increases very sharply to over 35 FTEs/MW by 2025. During the next five years, the rate of growth tapers off because much of the supply chain is already regional, with a normalized value of around 39 FTEs/MW by 2030.
Jobs–Operations and Maintenance
For operations and maintenance, the total number of FTEs projected is significantly less than for construction. However, these jobs last for 20 to 25 years, the typical lifetime of an offshore wind project, and are therefore permanent, career-length opportunities. Construction jobs, as reported by JEDI, are the equivalent of one year (job-years or person-years).
The results for FTEs supported under Scenarios A, B, and C are given in Figure 8, Figure 9 and Figure 10 respectively and show very similar patterns as for construction. The majority of jobs would be in supply chain and induced impacts – this trend is even more prevalent during the operations and maintenance phase.
Similarly to the analysis in the previous section, Scenario A projected the least FTEs, with around 2,700 FTEs over 1,695MW total generating capacity by 2030. On the other hand, Scenario B supports around 7,000 FTEs over 4,027MW generating capacity, and the expected total for Scenario C is over 16,000 FTEs over 9,760MW capacity by 2030.
For operations and maintenance, the normalized FTEs/MW increases at a much slower rate from around 1.64 FTE/MW to around 1.67 FTEs/MW for all three scenarios. This is because it is assumed that the majority of services and materials would already be regionally sourced for this phase of a project, therefore this metric stays relatively consistent from 2020 through 2030.
Earnings and Output
As explained previously, earnings refer to wages and salaries paid to workers and employer-provided supplements, while output refers to the total economic activity supported by the scenario of analysis. As expected, as the industry grows the model projects higher earnings and outputs for all three scenarios. The earnings and output charts for Scenarios A, B and C can be seen in Figure 11 and Figure 12 respectively. All three sets of charts show similarities – (1) the growth patterns for earnings/outputs are very similar for each scenario; (2) Turbine and Supply Chain has the highest portion of earnings and output across all scenarios, typically over half the total; (3) conversely, Project Development and Onsite Labor has by far the smallest portion of earnings and output, particularly for scenario A; and (4) there is a greater discrepancy in these proportions for the output rather than the earnings.
The Southeast has the capacity to become a long-term leader in offshore wind energy, with ample resources for the industry to thrive. A very good shallow wind resource, low manufacturing costs, manufacturing expertise and access to some of the largest and most industrious ports on the East Coast are all very attractive features of this region.
The JEDI model was used to provide estimates of the magnitude of economic impacts for the region using three distinct scenarios. Scenario A projected the least economic activity and is considered to be too small to encourage industry growth. Scenario C projects the largest gross economic impacts, but it requires the regional supply chain to develop at a extremely fast rate. Finally, Scenario B is a moderate and offers sufficient economic returns to encourage growth.
As described previously, the results of this study are only estimates intended to provide a reasonable profile of what the offshore wind industry could look like in the Southeast region. Since a mature offshore wind industry does not currently exist in the United States, revisions of this model would be required in the future, as the impacts of the industry are better understood.
Economic impacts; supply chain; Southeast region; JEDI; offshore wind
The U.S. D.O.E. Wind & Water Power Technologies Office funded James Madison University and the National Renewable Energy Laboratory to perform this work under Contract No. DE-AC36-08GO28308. Addtionally, the authors would like to acknowledge Simon Mahan, Renewable Energy Manager, Southern Alliance for Clean Energy and Brian O’Hara; President, Southeastern Coastal Wind Coalition.
1. See www.secoastalwind.org for more information on how a regional approach can benefit the Southeast
6. Input-output analysis is a method of evaluating and summing the impacts of a series of effects generated by expenditure.
7. A ‘User Add-in Location’ feature was added to allow users to derive the necessary data to complete analysis for specific regions. The necessary inputs include direct, indirect, and induced multipliers for employment, earnings and output, and personal consumption expenditure patterns – calculated as a percentage for each industry, for the 14 aggregated industries and the IMPLAN 432 industry sectors
8. A FTE is equivalent to 2,080 hours of work, and could also mean 2 part-time jobs of 1,040 hours each.
9. Economic activity in the region
10. Note that nearly half of this capacity growth occurred between 2000 and 2004.
11. Generally, these are components and services which are easily produced regionally, such as concrete and legal services
12. These are components and services which require expertise in offshore wind industry, such as foundations and project financing.
13. A linear scaling system was applied for Regional Investment percentages between 2021 and 2024, and 2026 to 2029.
14. $100 million against $200 million
15. $450 million against $1.4 billion
16. $300 million against $1 billion
17. $1.8 billion against $7 billion
18. $1.25 billion vs. $3.75 billion
19. $4.25 billion vs. $11 billion
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4. Annual Report 2012. 2012.
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