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October 2013

Company Profile: TEAM-1 Academy

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For Team-1 Academy, one success has led to another. Success in the hazardous waste management and industrial cleaning markets, complimented by a grand total of zero injuries, planted the seeds for their HazMat response team. HazMat response teams, formed in 1995 and sold in 2008, specialized in cleaning up high-hazard chemical spills and conducting high-hazard confined space entry work.

“Many of these confined space jobs involved technical rope rescue, which allowed us to get into doing stand-by rescue for confined spaces and working at heights,” said Scott Connor, director of training for TEAM-1 Academy. “Our rescue/safety equipment division came from repeated requests by many of our customers to provide such a service. We are the authorized distributor of many of the top manufacturers in the world of safety and rescue. We only promote manufacturers that our own rescue teams use their products. So right now we have three main departments: training, equipment sales, rescue/rope access services.” Figure 1

Successful in these areas, TEAM-1 naturally became a popular choice to conduct training sessions to the fire service, police, and the military—both in Canada and the U.S.

Continuing that trend of evolution and expansion into emerging industries, TEAM-1 has been able to grow with the wind industry sector since the company began. “It’s growing everywhere,” Connor said. “Our company deals with all industry sectors, and the wind/renewable energy sector is an exciting one.”

It’s a natural progression from TEAM-1 to the wind industry; its fall protection/rescue-from-heights courses are widely recognized. Connor said, “So much of the work that is done on the wind turbines involves some type of fall protection and having rescue capabilities. It was a natural transition for many of our customers that already use us in their other divisions to start using us in their wind businesses.”

In addition to safety/training courses, TEAM-1 also performs on-site services such as equipment inspections and confined space stand-by rescue services. The company also sells top-line safety and rescue equipment, including fall protection gear and hand/eye/ear/foot protection.

One example of TEAM-1’s commitment to the wind energy industry is its regular presence at industry trade shows and exhibitions. The company will be exhibiting this year at the Canadian Wind Energy Association’s Annual Conference and Exhibition in Toronto (booth 1100). Figure 2

“We look forward to the CanWEA show every year,” Connor said of the event. “All our customers attend and it is great to see them and show them our newest products. We look forward to meeting new customers and will answer any questions they have should they come to visit us. The CanWEA show is a great show and we are proud to be a part of it.”

As members of SPRAT (Society of Professional Rope Access Technicians) and ISFP (International Society of Fall Protection), TEAM-1 encounters various wind energy scenarios on a regular basis. It’s helped them develop fast and professional solutions to difficult access problems such as blade inspection, painting, and cleaning.

Fully-insured and offering CEU’s, TEAM-1 provides training courses and other services for Canadian government (provincial and federal) environmental, safety, and inspection agencies, along with some of the largest companies in the world. Last year, TEAM-1 attained ISO9001 and 18000 certification (their company facilitates close to 1,000 safety and rescue courses per year without any injuries); many of their clients have been with them for over 20 years. Figure 3

One of the key contributors to TEAM-1’s being recongnized as an authority in rescue and at-height safety training, Connor explained, is its staff of experienced, communicative instructors, who do more than simply “instruct.” These instructors have the benefit of extensive experience and are the backbone of these sessions.

“It is easy to find people that know the information,” Connor said. “Very few people can convey it professionally. We will only hold a training course if we can do it very well—we don’t just hire any instructor. It may take years before an assistant instructor with our company becomes a lead instructor.”

So when a customer calls last minute with a need for a training session, TEAM-1 makes an effort to cover it with one of their 16-plus instructors. If no instructor is available, there’s no settling for less.
“We refuse to contract some so-called instructor off the street to make a buck. Imagine if an accident occurred during a training exercise or on the job—when the investigation team or prosecution learns of this, they will have a heyday.”

The training normally takes place at the customer’s site. TEAM-1 travels all over the world to conduct training sessions to ensure the customer is learning their equipment at their location. Of course, this on-site option isn’t ideal for all customers, some of whom can’t free up the location or have too many on site disruptions, so TEAM-1 offers three training locations, located in southern Ontario, to be used at no extra charge.

“The customer may have employees that need to travel to the training location from all corners of the continent,” Connor said. “Our southern Ontario training centers are close to major airports and hotels and are very safe places to be.”

“People are most impressed that we could do such dangerous work and never have an injury,” Connor continued. “That record remains to this day. We encourage our potential customers to do their homework and their due diligence and they will see why we are the most recommended and trusted name in rescue and safety. Our philosophy is simple: provide services that are the benchmark for the industry and maintain this under all costs. A company works so hard to get a reputation like ours and our employees realize that. Our employees are proud of the company name and reputation.” 

 

For more information visit www.team1academy.com.

A Road Map for Efficiency

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There have been many significant advances in software for the wind energy industry over the past decade. A search of the Internet reveals hundreds of different software products for the wind industry, covering specific topics such as: site selection, wind forecasting, turbine design, wind data analysis, wind farm modeling and visualization, and flow modeling, among others. These are primarily engineering and design tools. While they are important in their own right, they do not help in the day-to-day operation of the business.

You can also find standalone products from other industries for applications such as: project management, maintenance & spares inventory, health and safety, land lease and royalty payments, and contract management, as well as standard enterprise resource planning (ERP) solutions for accounting and finance, which can be applied to any industry.

However, this same search does not return a single result for an integrated solution for the overall management of wind farm operations—a solution that would bundle together all of the required operations management and intelligence applications into a single, integrated solution for running the business.

This situation has also existed—and has been successfully addressed—in other industries. Initial solutions tended to be “point solutions,” which were focused on a specific topic. Over time, problems developed with duplication of data and processes, and there were difficulties in integrating the different “islands of automation.”

Further solutions were later developed to address these problems, initially in discrete manufacturing, and subsequently in process industries. In those industries today, we see two very important developments which have resulted in the elimination of the problems:

• The creation of standards for deploying information systems
• The development of integrated solution maps for the required applications.

As a result, software companies started building integrated solutions, with industry-standard interfaces. In manufacturing today, there is a wide selection of integrated solutions available to the benefit of all prospective customers.

These same developments need to be brought into the Wind Industry.

Develoment of Standards
A key example of standards for manufacturing systems is ISA 95, as seen in Figure 1.

These same levels of automation exists in the wind industry. While significant progress has been made at the lowest level by integrating sensors and SCADA systems, as well as standard ERP solutions for accounting and finance, little has been done in developing integrated solutions for the middle layer—operations management and intelligence.

Solution Map
The time has come to specify a similar solution map for the wind industry, in which:

• all of the functions required for operations management (running the business) are addressed;
• the solution provides the operational intelligence for performance management;
• the system is built around a common, shared database;
• the solution provides seamless integration of related systems and data from operations (SCADA, data historians), with the business systems (ERP, financials), as well as the Internet (forecasting and pricing).

The following represents an initial proposal for the desired content of a solution map for an operations management and intelligence system for the wind energy industry. Figure 2

Just like the ISA 95 standard for the manufacturing industry, the standard model for the wind industry should consist of five layers, as outlined in Figure 4. Here, the solutions in Levels 1, 2 & 4 are well developed. The balance of this section will focus on the application needs for Level 3 – Operations Management & Intelligence. The individual modules are grouped into subsystems under the headings of “Generation,” “Maintenance,” “Health & Safety,” “Accounting & Reporting,” “Performance Management,” and “Technology.” The proposed solution map calls for a common data structure, and for integration between all of the modules. This is accomplished through the use of a common set of foundation modules.

Foundation Modules
The foundation modules include the basic building blocks to configure the system for use, and include: Asset Hierarchy; Event Manager; Performance Criteria; Electronic Logs; Alarms and Notifications; and KPI (key performance indicator) Manager.

• Asset Hierarchy­—This module allows the user to manage overall asset hierarchy, from organizational units (company, geographical unit, division, plant, etc.) down to equipment, sub-assemblies, and components. There is no limit to the number of levels the user can create in the hierarchy. The asset hierarchy module is the backbone of the software solution—against which all performance criteria, events, and activities are structured. This solution seamlessly integrates with other standard industry solutions [ERP, computerized maintenance management systems (CMMS) and data historians] to provide the information on asset availability to all foundation modules and application modules
• Event Manager—Operating and non-operating events within the organization are detected, recorded, and communicated through the Event Manager Module. This module (Figure 10) is suited for monitoring operating events that cannot be tracked manually or with traditional system alarms. It can also capture events either electronically or manually. This module automates and highlights unusual conditions, and notifies the user when these events occur. As a result, the user is able to reduce operating costs and improve yields with fast, effective follow-up, while improving regulatory compliance, reducing incidents, and analyzing events.
• Performance Criteria—Once the Asset Hierarchy has been established and attention switches to collecting data for analyzing performance, the targets, standards, or metrics for the different events (performance criteria), must be established. Examples include: the rated output of the wind turbine for different wind speeds; expected operating temperature for wind turbine gearbox oil; and the schedule for preventive maintenance tasks. Performance Criteria can also be established for the business—for expected daily generation; target for real-time energy prices; and other daily, weekly, monthly, or annual statistics.
• Electronic Logs—This module provides an electronic log framework (Figure 3) to allow users to make log entries under predefined categories such as safety, environment, and operating procedures, among others. The log entries should be supportable with any digital media (voice, pictures, videos).
• Alarms and Notifications—The Alarms and Notifications engine is intended to notify users that any predefined situation may be developing or occurring. Notifications can be sent via email or text message. The software includes an escalation function should there be no response within a predefined time frame.
• KPI Manager—This module provides a real-time solution framework for the collection, analysis, and calculation of key performance indicators. The KPI Manager delivers accurate and timely information the user needs in order to enhance visibility into operations and increase the efficiency and effectiveness of resources. It provides accurate key performance indicator data throughout the organization, allowing everyone to drive performance improvement initiatives. The KPI Manager rolls up low-level performance indicators (such as unit-specific production generation) to high-level business objectives (e.g. site productivity or asset utilization). Users can quickly drill down to view actual performance measures and respond appropriately.

Generation Management Modules
The modules in Generation Management are related to tracking electricity generation and downtime and include: Generation, Downtime, Outage Management, Generation Forecast, and Lost Generation Analysis.

• Generation—Generation data—collected from SCADA systems through the data historian or other central collective—is tracked by individual asset, summarized, and presented in real-time display (Figure 4). This data can be used for comparisons to specifications, or comparisons between equivalent units.
• Downtime—This module provides tracks all downtime events—planned or unplanned, imposed or self-induced. These events are captured either manually or automatically, and include the capability to code events by different fault codes (e.g. manufacturer, O&M, NERC, PPM). The user should be able to review and modify all events captured in the system. Displays (Figure 5) to review event logs, as well as charts to analyze downtime by turbine, component, fault code, etc., should be included.
• Outage Management—This application supports logging and tracking of site outages—planned and unplanned—and captures generation and resource availability at the time of the outage, while triggering required notifications or work orders. This increases visibility of outage information across the organization; ensures that key personnel are notified of outages; captures critical information associated with an outage; and ensures the required procedures are followed for bringing a unit back online.
• Generation Forecast—An environmental forecast is brought into the system from a third-party provider. This information is used to calculate the expected generation from each asset, considering known outages for maintenance or curtailment. The generation forecast can also be converted to a financial forecast based on market or contact prices.
• Lost Generation Analysis—This module allows the user to analyze and categorize all lost generation, both in terms of lost production and lost revenue. Standard reporting categories in the industry are: generation, gross availability, contract availability, project availability, and commercial availability. The solution must also consider downtime related to curtailment or maintenance. The loss analysis should use pricing from contract actual agreements, or real-time pricing from the Web. (Figure 9)

Maintenance Modules
The modules for maintenance functionality are those related to planning, coordinating, and tracking maintenance activity, and include: Equipment Records, Maintenance Information, Work Orders, Inspection Tours, Condition Monitoring, and Spares Inventory.

• Equipment Records—This module allows the user to maintain a complete hierarchical record of all operating equipment. There should be no limit to the number of levels in the hierarchy, and the asset hierarchy should include all sub-components (e.g. sub-assemblies and parts). Ideally, the Equipment Records module also points to digital records of the equipment such as engineering drawings, pictures, and operating manuals.
• Maintenance Information—Detailed information should be associated with the equipment records, specifying the maintenance work to be done, the interval between service, the job skill requirements, and the spare parts and tooling required for the work.
• Work Orders—The system should support work orders for different types of activity, such as inspection tours, corrective maintenance, and preventive maintenance. The work orders should clearly identify the following: equipment involved; safety procedures to be followed; repairs to be made; parts and tools required; and the expected start and completion date of the work.
• Inspection Tours—This function (Figure 6) allows the user to use printed reports or mobile devices to specify safety or maintenance inspection requirements to field personnel. With mobile devices, the user can easily communicate maintenance tasks (safety procedures, job steps, drawings, etc) to field personnel, who in turn can use the device to indicate task completion, record verbal comments, or take photographs and videos of the situation.
• Condition Monitoring—This module (Figure 7) allows the user to collect condition data from the operating units, comparing this data standard or expected values. It also triggers any necessary alarms, alerts, notifications, or work orders. The system should handle any type of condition measures, including vibration analysis, oil sample analysis, bore hole photography, and dynamic loads, while coordinating this information with other system data (e.g. weather conditions, generation data).
• Spares Inventory—Here, the user can track the quantity and location of all spare parts, sub-assemblies, or tools, along with the associated information for procurement. The module should also allow for tracking equivalent parts or allowable substitutions. In the case of repairable or re-usable parts, the module should also allow for tracking usage history of such parts.

Health and Safety Modules
• Incident Tracking—Our incident tracking application allows you to enter new incidents and assign them to the right personnel for investigation and resolution. It classifies incidents in a variety of categories enabling powerful search capabilities and flexible reporting.
• Work Place Hazards—This application assists workplace safety professionals in documenting workplace and material hazards, and in recording a complete history of the hazard investigations and assessments. It covers job safety analysis, ergonomic analysis, lockout/tagout, and risk assessment. It also allows the user to record any events and analyze them using the root cause analysis application.
• Compliance Management—Provides the user the ability to make compliance programs repeatable, sustainable, and cost-effective. Compliance Management provides a common framework and an integrated approach to manage all compliance requirements faced by an organization. It enables companies to manage cross-industry mandates and regulations such as SOX, OSHA, EH&S, and FCPA, as well as industry-focused regulatory guidelines from FDA, FERC, FAA, HACCP, AML, Basel II, and Data Retention laws.
• OSHA Reporting—This application allows the user to track all health and safety issues, material and workplace hazards, and risk assessments, and has the capability to generate all OSHA standard reports. The module can easily track safety investigations and audits, while also providing the ability to record the costs associated with safety incidents. In addition to standard reports, this module lets the user create personalized dashboards and analytical reports to optimize reporting.
• Environmental Issues—This module provides users a means to track all issues related to the environment in one central system. It allows you issues related to land use, track oil spills and waste disposal, and track issues related to wildlife and birdlife. The software can also track the noise created by wind turbines operating in different wind conditions.

Accounting and Reporting Modules
The modules in Accounting and Reporting are those related to executing accounting tasks, as well as providing in-house and statutory reporting about operations, above and beyond the functionality ERP solutions provide, and include: Energy Settlements, Lease and Royalty Payments, NERC GADS Reporting, Revenue Forecasting, Day Ahead Training, and Warranty Management. Figure 11

• Energy Settlements—All Generation and downtime information is paired with metered data and pricing information to calculate Energy Settlements. Pricing data can be taken from contracts or from real-time pricing on the Web, and can also be used to value losses from downtime events.
• Land Lease & Royalty Payments—This application tracks all of the agreements for the user’s operating assets. It manages contracts for land lease and royalty payments, automatically triggering payments for any period and/or frequency. It also allows the user to preview the complete output to ensure accuracy and completeness prior to transferring the data into an accounting system.
• NERC GADS Reporting—The application should be programmed to generate the reporting requirements specified by the North American Electric Reliability Corporation (NERC) Generating Availability Data System (GADS). It allows users to gather and verify event and performance data, as well as analyze (Figure 8) current and historical event and performance data, including energy availability, outages, and demand factors.
• Revenue Forecasting—The revenue forecast application allows the user to import weather condition forecasts, and then calculate a generation forecast using the historical performance of each asset (taking into consideration all planned maintenance outages, curtailment, or other planned outages). It also translates data into revenue forecast by accessing contract pricing stored in the system, or by accessing real-time pricing data on the web.
• Day-Ahead Trading—Comparing forecasting module information with customer power commitments, the software can predict anticipated surplus generation for a future time period. This surplus can then be offered on the day-ahead trading market at asking price.
• Warranty Management—This module allows the user to monitor all assets under warranty, tracking work performed and replacements made during the warranty period. This includes tracking parts or sub-assemblies that have been removed, repaired and put back into service as warrantied parts on other turbines. This system should be put in place well before the equipment comes out of warranty, so equipment records are established and the maintenance tracking procedures are in place.

Performance Management
The modules for Performance Management are those related to collecting, analyzing, and reporting on all data across the organization, and include: Operational Planning, Capacity Analysis, Performance Analytics, Comparative Reporting, Root Cause Analysis, and Activity Tracking.

• Operational Planning—This enables improvement of operational planning capability through increased visibility of key site-related data. It consolidates critical operations data into a single, centralized location for visualization and analysis. Planned and unplanned downtime events, scheduled and unscheduled outages, and weather forecast data are all centralized into a single, consolidated system that can provide the insight needed to enhance operational planning.
• Capacity Analysis—Gaining insight into project capacity can dramatically increase the profitability of renewable asset(s). Whether it is individual wind turbine power curve or an entire wind farm’s peak power, the capacity analysis application provides the operator with the ability to understand how well assets are performing in relation to their rated capacity.
• Performance Analytics—Allows the user to create performance summaries for all operating assets, including measures such as gross, contract, and commercial availability, performance to manufacturer’s standards, and comparative performance. The software should support hundreds of thousands of data calculations, generating actionable intelligence to support performance improvement initiatives and the pursuit of increased ROI.
• Comparative Reporting—One of the key benefits of an information system independent from a particular vendor’s SCADA system is that it allows the user to consolidate and compare data from different units. This can be accomplished by establishing codes for normalizing data from different sources. Examples include using fault codes from multiple vendors, and comparing performance of similar turbines in different areas versus the prevailing wind speeds in those areas.
• Root Cause Analysis—The root cause application should serve an accountability function. It enables the user to analyze structures, prioritize corrective actions, and track progress. This ensures that resources are focused, to avoid performance losses. Root Cause Analysis improves problem resolution with automatic and precise downtime logging, tracks implementation of recommendations, and allows the user to assesses effectiveness of recommendations.
• Activity Tracking—Projects are defined and broken down into specific tasks, including responsibility, start/end dates, priority, targeted results, and risk evaluation. Daily updates can be viewed both on a per project basis as well as in schedule performance charts. Hierarchical management of data allows authorized viewing up the organizational ladder. Impact of change activities can be measured over time. Software supports drill down to source data.

Additional Features
• Design Studio—The Design Studio allows for creation and/or modification of displays and reports within the system. The user can also configure customized KPI’s, as well as create custom modules within the software.
• Visualization—The software should provide tools for visualization (Figure 12), including map overlays, a dashboard object library, dashboard/report templates, and a library of pre-defined KPI’s.
• Import/Export—The software should allow the user to import data from external systems (e.g. bulk loading specific turbine fault codes, or importing regional wind forecasts). The software should also allow exporting of data to related systems, as well as the export of on-screen content to Excel or PDF formats.
• Interfaces—This includes the software required for interfacing with other related business systems, SCADA systems, data historians, or the Web.
• Mobile Technology—With the exponential growth of mobility and due to the distributed nature of the wind energy assets, it is imperative that the system solution utilize mobile technology. Alerts and notifications should be transmitted to mobile devices. Dashboards, performance summaries, and KPI’s should be visible on smartphones and tablet computers.
• Messaging Network—This module allows users to have better interaction with the platform’s data flow. By providing a push-and-pull mechanism, users are able to experience enhanced interaction with module applications and faster notifications from any computer, or device connected to the Messaging Network.
• Data Mining & Analysis—The software should allow for ad hoc data mining and querying of the data, making selections by asset, event type, tag status, or tag information. Results should be presentable in tabular form or in charts (Figure 13), and the user should be able to perform “what if” analyses or causal analyses on the resultant data.

The End Product
If we summarize all of the preceding information into a single model, we end up with the solution map for Operations Management and Intelligence for wind farm management, outlined in Table 1 and Table 2.

Hopefully this will be viewed as a viable first step in the creation of an overall model for Wind Farm Information Systems. Ekho for Wind, from Ekhosoft, has been developed in accordance with this proposed standard model. The author welcomes feedback and suggestions on the proposed model, and is open to inquiries about Ekho for Wind. 

Potential Economic Impacts from Offshore Wind in the United States – The Southeast Region

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Abstract
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.

1. Introduction
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.

Wind Resource
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.

Market Size
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.

Cost
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).

Model Input
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.

Model Output
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.

Caveats
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.

Regional Investment
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.

Cost
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.

Scenario Compilation
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

5. Results
Jobs–Construction
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.

6. Conclusions
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. 

Keywords
Economic impacts; supply chain; Southeast region; JEDI; offshore wind

Acknowledgements
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.

Footnotes
1. See www.secoastalwind.org for more information on how a regional approach can benefit the Southeast
2. www.boem.gov/Renewable-Energy-Program/index.aspx
3. http://www.boem.gov/Renewable-Energy-Program/State-Activities/Virginia.aspx
4. http://www.boem.gov/Renewable-Energy-Program/State-Activities/North-Carolina.aspx
5. http://www.boem.gov/Renewable-Energy-Program/State-Activities/South-Carolina.aspx
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

References
1. Virginia Coastal Energy Research Consortium. Virginia Offshore Wind Studies, July 2007 to March 2010, Final Report. 2010.
2. Jonathan Miles, Rick Thomas, Jay Titlow, Jon Klinck, Ann Kirwin. Virginia Offshore Wind Advanced Technology Demonstration Site Development. s.l. : A Final Report to the Virginia Department of Mines, Minerals and Energy on Work Performed under Contract # C11-6073, 2012.
3. Virginia Offshore Wind Development Authority. Annual Report 2011. 2011.
4. Annual Report 2012. 2012.
5. The University of North Carolina at Chapel Hill. Coastal Wind Energy for North Carolina’s Future. 2009.
6. Wind Energy Production Farms Feasibility Study Committee. South Carolina’s Role in Offshore Wind Energy Development. s.l. : Prepared in response to Act 318 of 2008. A Joint Resolution Requiring Recommendations from the Wind Energy Production Farms Feasibility Study Committee, 2009.
7. Colbert-Busch, Elizabeth, Carey, Robert and Saltzman, Ellen. South Carolina Wind Energy Supply Chain Survey and Offshore Wind Economic Impact Study. s.l. : Prepared for the South Carolina Energy Office by the Clemson University Restoration Instutute and Clemson Strom Thurmond Institute, 2012.
8. Laport, Christine and Alber, Merryl. Offshore Wind Energy: Consideration for Georgia. s.l. : Prepared by the Georgia Coastal Research Council, for the Georgia Department of Natural Resources. Coastal Resources Division. 41 Pages, 2011.
9. Southern Winds & Georgia Institute of Technology. Summary Project Report 2007 – A study of wind power generation potential off the Georgia coast. 2007.
10. Musial, Walter and Ram, Bonnie. Large-Scale Offshore Wind Power in the United States: Assessment of Opportunities and Barriers. [Online] September 2010. [Cited: November 12, 2012.] http://www.nrel.gov/docs/fy10osti/40745.pdf. DOI: NREL/TP-500-40745.
11. Detailed State Data – Annual Data for 2011. U.S. Energy Information Administration: Independent Statistics & Analysis. [Online] October 2, 2012. [Cited: October 25, 2012.] http://www.eia.gov/electricity/data/state/.
12. Updated Capital Cost Estimates for Electricity Generation Plants. U.S. Energy Information Administration Office of Energy Analysis. [Online] November 2010. [Cited: October 30, 2012.] http://www.eia.gov/oiaf/beck_plantcosts/pdf/updatedplantcosts.pdf.
13. U.S. Army Corps of Engineers. Tonnage for Selected U.S. Ports in 2011. Navigation Data Center. [Online] April 25, 2013. [Cited: June 05, 2013.] http://www.navigationdatacenter.us/wcsc/portname11.html.
14. U.S. Department of Energy – Energy Efficiency and Renewable Energy. 20% Wind Energy by 2030 – Increasing Wind Energy’s Contribution to U.S. Electricity Supply. [Online] 2008 July. [Cited: August 12, 2012.] http://www.nrel.gov/docs/fy08osti/41869.pdf. DOI: DOE/GO-102008-2567.
15. State Fact Sheets. American Wind Energy Association. [Online] 3rd Quarter 2012. [Cited: November 16, 2012.] http://www.awea.org/learnabout/publications/factsheets/factsheets_state.cfm.
16. National Renewable Energy Laboratory. Energy Analysis – Jobs and Economic Development Impact Models. [Online] September 5, 2012. [Cited: October 15, 2012.] http://www.nrel.gov/analysis/jedi/.
17. MIG. MIG – creators of IMPLAN. [Online] 2012. [Cited: June 5, 2013.] http://implan.com/V4/Index.php.
18. al., Lisa Frantzis et. Offshore Wind Market and Economic Analysis – Annual Market Assessment. Burlington, MA : Navigant Consulting, Inc., 2013. Document Number DE-EE0005360.

Unforeseen subsurface conditions: Mitigating the risks of what can’t be seen

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Construction contracts require owners and contractors to accept risk as part of the project construction. Two closely related risks on wind energy projects are unforeseen subsurface conditions and pre-existing hazardous materials. Properly evaluating and handling these risks is a necessary part of being a successful wind energy contractor.

Wind energy balance of plant (BOP) contracts typically contain clauses requiring the contractor to acknowledge that it is familiar with the local conditions of the project site. In addition, BOP contracts commonly require the contractor to assume much of the risk of these local conditions. Contractors must be skillful in limiting the scope of these clauses by using carefully drafted language specifying the contractor’s responsibility for unforeseen subsurface conditions and pre-existing hazardous materials.

Wind energy contractors must approach the risks of unforeseen subsurface conditions and pre-existing hazardous material with caution. Examples of how to mitigate risks associated with wind energy projects include:

Subsurface Conditions Clause
The subsurface conditions clause (also called an “unforeseen subsurface condition” or “unforeseen conditions” clause) should be drafted to give the contractor the right to schedule and/or cost relief under certain conditions:

1. Subsurface or latent physical conditions at the project site are materially different from the conditions described in the contract documents, including the geotechnical report and other materials provided to the contractor by the owner.
2. Conditions are discovered at the project site that are  previously unknown and are of an unusual nature, or are materially different from those conditions that are ordinarily encountered and generally recognized as inherent in working at the project location, or
3. The contractor encounters hazardous materials or conditions that exist at the project site as of the time of the contract and were not brought to the site, or created by, the contractor or its subcontractors (defined as pre-existing hazardous materials or conditions). 

In order for this clause to protect the contractor and afford potential cost and schedule relief, the contractor needs to make a thorough review of all of the documents that are provided to it by the owner. In addition, the contractor must make itself familiar with the subsurface conditions that actually exist at the site and that are normally expected in the project location.

Geotechnical Investigation
The best way to become familiar with the subsurface conditions of a project site is to conduct a thorough geotechnical investigation of the site (or make sure that one is provided by the owner). The report should be performed by a reputable and experienced geotechnical engineer, and should be based upon borings made at every turbine location and at selected points along the roads and substation locations. The report should contain a description of the soil types at each boring, groundwater elevations, electrical and thermal resistivity testing results, and a full array of laboratory analyses of the soil (particle size, moisture content, Atterberg limits, compaction testing results, chemical analyses, etc.). In addition, the report should contain recommendations for the type of foundations that are appropriate for the soils conditions, as well as recommendations for the civil infrastructure design parameters.

A properly performed geotechnical report can provide the information the contractor needs to evaluate the risks of any surprises from unforeseen subsurface conditions.  In addition, the report will provide the information needed to design the roads, foundations and electrical collection system without any undue risk of errors caused by unanticipated subsurface condition.  In contract terms, the report should demonstrate that the contractor has performed the necessary due diligence required to become familiar with the local subsurface conditions, and avoid the risk of differing site conditions.

Pre-Existing Hazardous Materials
Contractors should strive to limit their responsibility with respect to the presence of hazardous materials at the project site to things that they can control (i.e. hazardous materials that are brought to the site by the contractor or its subcontractors). The obvious major risk is the presence of hazardous materials that are unbeknownst to either the contractor or the owner. In such cases, the risk should be on the owner since they are party with the greater ability to control the risk. In instances where pre-existing hazardous materials or conditions are encountered by the contractor, its responsibility should be limited to first promptly notifying the owner, and then performing any legally required “emergency” actions before leaving the area (with its costs borne by the owner). As long as the contractor’s actions are not negligent, it should not be responsible for the existence, discovery, or release of pre-existing hazardous materials. 

Listen to the story that turbine data is trying to tell you

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I don’t want to waste my time, labor, or money doing unnecessary things.
This year I have spent much of my time here talking about data collection on wind turbines in a variety of forms. This is because I want to know when I should do something—when I should react. I am looking for a trigger point to intelligently move into action.

Let’s face it, wind turbines will eventually have problems. So far, every machine I have ever worked on has needed grease, and has broken down. When it comes to maintenance, I figure that you have two options. The first option is to collect data and determine where you should be spending your time, labor, and money. The alternative—your second option—is to just guess or wait until the machine breaks down, and then react to fix it.

The problem with waiting and reacting is that you may never catch up. You will always feel like you are in the dark and be frustrated by the loss of control of the consumption rate of your resources. Besides slowly falling behind, surprise failures affect the entire team’s morale, demolish budgets due to high repair costs,  and cause revenue losses due to the turbine being off line. The best you can hope for is an insurance claim, such as when a turbine totals itself out (e.g. a failure due to fire).

Even when you have data from multiple sources, the machines are still subject to failure. The difference is there are fewer surprises when you can see the failure coming at you. Sometimes data collection allows you to catch and solve the problem in one machine, and make proactive repairs to other turbines before the the same failure affects  all the machines in the fleet.

Sometimes, it makes sense to just let the machine fail. But there is a difference in knowingly letting it fail and having a failure occur without warning. Armed with data, the failure doesn’t catch you by surprise.  The team knows what is going to happen and can plan for it accordingly.

It’s kind of like going to the dentist. When I go to the dentist, I like to know what the dentist is planning on doing. I sure I don’t want him surprising me.

Many of the articles written here this year concerned with different ways of collecting data so as to get a feel as to what is going on for each turbine’s critical components. Each one of these data collection methods is a way to get data to trigger an action. The action part is key. Data collection by itself is not the goal. This data needs to be formatted so that it is able to be reviewed by someone. This should be done immediately in order to maximize the benefits. As such, it makes sense to incorporate incentives for employees who review the data. They should constantly be asking “Where is the new data for us to review?”

I’m sure many feel that they are overloaded with data, but this data is very important, and for some types of failures, time is money. The quicker you are able to react to what the data is telling you can often mean the avoiding significant unplanned added costs.

Even those who are not familiar with the intricacies of the different machinery components can notice trends, and will be able to tell when things are out of the norm. They may not know what is going on, but they can see that something is different and can ask for help from someone who is more experienced.

Sometimes I hear or see that maintenance data is not being reviewed on a timely basis. Ignoring that constant stream of data may seem trivial most of the time. It may seem like you are reducing your workload. Maybe you are. But in reality it just means that, in the event of a failure, you may realize that the data you ignored was telling you a story. The failure may even have been avoidable. Instead, it caught you by surprise and cost your team.

Oil sampling, for example, is a common data collection method that requires analysis. If not followed through properly, there are many areas in which data from oil sampling can fail to be functional.
The first area of failure is taking the oil sample improperly. There are many ways to mess this up, and all have their failure modes. Taking the oil sample at the wrong location or at the wrong time (such as during a period of long-term machinery standstill) introduces the risk of the sample becoming contaminated.

Another failure in prompt data collection occurs when the retrieved oil samples are allowed to bounce around a few days in a truck, or to sit on the counter or desk for weeks before finally sending them in for analysis.

The next failure point in the oil sample cycle occurs when emails containing oil sample data are ignored by the recipient.

A bad oil sample is a trigger to cause action, not an action in itself. The final step in an oil sample cycle should be the review of the data by the technician who took the sample. The technician should be asking to see the oil sample results. If the technician sees the results of their work, they are more likely to perform the task properly, eliminating sampling failures before the data is collected, because they will want to know the results of their work.

Do any of these problems seem familiar? If so, it is time to step up and improve your data collection review.

That’s just one example of how data can be used to trigger a service or action.   

Tower Ring method for cleaning wind towers significantly raises safety and environmental standards

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Health and Safety experts will tell you: “The best way to reduce risk, is to eliminate the risk.” Pretty simple logic, right? Try applying that philosophy to cleaning 300-foot-tall wind towers!

Wind power generation has been around for decades now. Local, state and federal initiatives are supporting (and in many cases, mandating) the movement toward renewable energy production—with wind power leading the way. While wind energy production has many proven advantages over less “green” electrical power generating sources, wind turbine generators (WTG’s) are still subject to mechanical failures that can result in environmental, health, and safety impact. For example, gearboxes can (and sometimes do) leak. Seals, fittings, and hoses can (and sometimes do) fail. These leaks and failures can allow lubricants, mineral oils, synthetic oils, hydraulic fluids, and greases to escape. With the major components of the WTG being housed uptower, any significant oil, grease, hydraulic leak or catastrophic failure is going to have those substances running down the length of the tower—making their way to the ground/soils or water table. Not only is the leak unsightly (ugly), it also creates an environmental hazard.

Traditionally, the preferred way to clean WTG towers was to have technicians hanging/suspending from ropes; raised in a man lift, boom truck, or crane; or attached to a hoisted scaffolding system (sometimes more than 300 feet above the ground). In addition to the possibility of falling from heights, these methods submit technicians directly to wind, heat, rain, and other weather conditions—exposing them to even greater risk.

Brothers Sonny and Broque Fraughton of Evanston, Wyoming-based Gladiators Cleaning, make their living washing trucks and cleaning coal mining equipment. Through their knowledge of and expertise with heavy equipment and vehicle cleaning, the pair devised a practical and ingenious solution and applied it to the wind power industry.  Instead of using people to clean the towers, they developed a high-pressure, heated water, washing “ring system,” that fits entirely (360˚) around the tower, to do the work (see Figure 1).

For the past two years, the brothers have been working with a team of wind energy professionals, electrical engineers, and auto wash system experts to perfect their “un-manned” WTG tower cleaning system. After developing and patenting their tower ring apparatus, they took their equipment (remote controlled hoist truck and pressure wash system) out to the wind farms. There, they met and partnered with Greener Solutions (www.greenersafer.com) to identify and utilize safe, high-powered, environmentally friendly cleaning chemicals to safely and quickly remove the dirts, oils, greases and other contaminates from the WTG towers and equipment. In addition, they also employ the use of microbial based cleaners/de-greasers for bioremediation (using hydrocarbon feeding microbes to “eat” the contaminates).

The risks associatied with high winds and dangerous weather (safety regulations) related to technicians hanging from ropes or being raised in man lift baskets, are much higher than when using the unmanned ring tower cleaning method and equipment.

This allows for the ring system to be safely utilized in scenarios where traditional methods would put people and their equipment at higher risk.

It also means less stand-by/down time when wind conditions become marginal. As a result, Greener Solutions and Gladiators Wind are now approved product and service providers for clients like: Suzlon, PacifiCorp Energy, EDF, EDPR, GE Wind, Iberdrola Renewables, among others. The unique ring apparatus design and industrial cleaning methods are giving OEM’s, wind farm owners, and service providers a safe, efficient, responsible option to consider when it comes to WTG tower cleaning.

Conversation with Ajay Swamy

Tell us about Acciona’s unique perspective in designing its wind turbines.

ACCIONA Windpower has a unique ability to understand what our customers need because we have been and will always be in their shoes. ACCIONA is one of the world’s leading renewable energy operators. We own over 8,400 MW of renewable energy facilities around the globe, including over 7,000 MW of wind power. Our 20 years of experience as an owner and operator has helped us design wind turbines that deliver benefits over the lifetime of a project. As an owner and operator, two important criteria are reliability and performance. Accordingly, we developed a robust design that has resulted in extremely low failure rates for critical components and over 98 percent availability across our global fleet.

Acciona’s newest turbine is the AW3000. How was it developed?

ACCIONA Windpower was one of the first OEMs to design a 3MW machine. We began design work on the AW3000 in 2006 because we understood a larger nameplate created economies of scale that could drive down a project’s cost of energy. If you can build a project with fewer turbines, there is less land to be developed, fewer foundations, and fewer roads to build. Also, higher nameplate capacity means fewer turbines to maintain, which lowers lifetime O&M labor costs. Finally, a higher nameplate means developers can focus on the best-producing turbine positions. These differences can add up to lower the COE by 10 percent or more compared with a 1.5MW or 2MW nameplate.

What’s inside? Tell us about the technology of the AW3000.

The AW3000 has double bearing support for the main shaft. Additionally, it uses a six-pole, doubly-fed induction generator that allows the generator to rotate at lower RPM than many of our competitors. These two features, when combined with other elements of the design, significantly isolate and reduce the load on the gearbox. This reduces maintenance costs and ensures a long life for the WTG. We are the only OEM that generates electricity at 12kV (i.e. at the generator terminals). This enables the turbine to be connected directly to a 12kV collection system without using a step-up transformer. Eliminating costly pad-mount transformers and reducting energy losses results in significant savings on the order of $50,000-$150,000 per MW, depending on the layout.

What are the key benefits of choosing the AW3000?

The choice of four different rotor sizes (100m, 109m, 116m, and 125m) and four different tower heights (hub heights of 92m 95.5m, 100m, and 120m) allows the AW3000 to be configured to meet the requirements of various wind classes and site conditions. The availability of concrete towers for 100m and 120m hub height further enhances its versatility. The variety of options from a single platform enables a developer whose site has multiple wind class locations to use the same platform and configure each wind turbine for its specific location.

Furthermore, the large diameter rotor and high performance blades will lead to a significant increase in net capacity factor. Using wind and site data, we have seen that the AW3000 can deliver an NCF of over 50 percent at some projects currently in development. The other design features I mentioned earler enable the turbine to have a high availability. For developers, this means a very competitive LCOE resulting in a high IRR and/or high probability of success in the procurement stage.

How do these configurations pair up with variance in geography and wind resources?
We offer four rotor diameters and a suite of tower heights in both steel and concrete that can meet the needs of almost any project globally. The 100 meter rotor is ideally suited for high-wind sites, while the 109 and 116 meter rotors give the AW3000 exceptional performance at medium-wind speed sites. Recently, we introduced a 125 meter rotor that competes in low-wind environments.

ACCIONA also has a robust suite of options, including: a cold weather package, condition monitoring, automatic lubrication, medium voltage inside the tower, and shadow flicker mitigation, to name a few. A service lift inside the tower is standard with every wind turbine.

How is the AW3000 being received in the wind turbine marketplace?

ACCIONA Windpower has been gaining momentum with the AW3000 platform in Canada and around the globe. We have finalized agreements that bring the total footprint for the AW3000 turbine to over 1GW. Our ability to win two RFPs for major Canadian projects in a short time frame has helped make the case both for the AW3000 as a competitive wind turbine and for Acciona as a capable partner.

For more information about Acciona Windpower turbines, visit AW3000.com or email sales@acciona-na.com. Also, the company’s commercial team is regularly present at major industry events like CanWEA to meet with developers and answer questions.