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Task 26 Work Plan and Objectives

Please find below our work plan and objectives

Task 26 formally began in January 2009 and is currently operating in its fourth task extension phase. Since 2009, Task 26 participants have produced results in four general areas related to cost of wind energy:

Cost of Land-based Wind Energy

Providing transparency in the cost elements of wind projects among all participating countries will result in better understanding of the cost drivers of wind technology and the reasons for differences among participating countries.

 

In the first phase of the task, participants used a common model to estimate the Levelized Cost of Energy (LCOE) for typical land-based wind projects in their respective countries.

 

In the second phase, a common template for representing the population of land-based wind technology, cost, and performance trends was developed. A report describing these trends and estimating the cost of energy over the period from 2008 to 2012 was produced. In the 2015 extension, participants will continue to build on past efforts.

Cost of Offshore Wind Energy

Offshore wind technology has been installed by some participating countries, and others are exploring the potential uses of this technology. A representative baseline offshore wind plant description was developed in the recent phase of the task. This baseline provides an opportunity for two types of analysis to better understand and define cost drivers for offshore wind energy:

 

  1. A common cash flow model, which explores the impact of market and policy aspects of offshore wind in each country relative to the baseline technology description
  2. Component models (e.g., electrical infrastructure, operations and maintenance) under development by various countries, which can be compared and improved through collaborative efforts relative to the baseline technology description

 

Based on insights gained through sensitivity analysis and model comparisons, Task 26 will identify characteristics of offshore wind cost models that could be of use to a range of stakeholders, including decision makers.

Future Cost of Wind Energy

Estimates of future cost and performance for wind technology are important for analyses of the potential for wind energy to meet national targets for carbon emission reductions or renewable electricity generation. Learning curves are one method for assessing the effect of technology development, manufacturing efficiency improvement, and economy of scale. Component level cost and scaling relationships can also be used to estimate future technology development pathways.

 

Engineering models can isolate theoretical improvements associated with individual technical changes, e.g., larger rotors. These models can also project theoretical cost and energy production from future technology advances. Expert elicitation provides a quantifiable means for assessing a range of expert perspectives on future cost of energy. All projections of future wind energy costs can be informed by analysis of historical trends that capture both technology and market-related influences.

 

Repowering is becoming an increasingly relevant issue in the wind energy landscape, as significant capacities of wind turbines are reaching the end of their technical/economic lifetimes across Europe and the US. Due to repowering being an emerging trend, there is very little research done on the topic to date. Achieving a better level of understanding regarding technical, performance and economic impacts of repowering would therefore be a value-adding contribution to the currently existing knowledge base, and provide critical input to informed decision-making on the part of policy-makers, investors, etc.

Value of Wind Energy

High shares of wind pose fundamental challenges to the current market set-up. The higher the share of prioritized wind power, the lower the share of market-based dispatchable power, which affects the merit order of the supply and lowers the power prices in general.

 

Variable wind energy supply may also create hours with very high prices in cases with little wind and high electricity demand, or even negative prices in hours with high wind and low demand. Even though these extreme prices are only observed in a minor number of hours per year it challenges the current market and price mechanisms.

 

A possible scenario setup for further investigating the value of wind power within the Task could be aimed at exploring the effects of applying different turbine technologies, thereby combining the knowledge on technology cost and trends from the wind task with an outlook on how technology costs compare to the value of wind power. Is the extra cost of low cut-in wind speed wind turbines beneficial from a system perspective? In this way added value compared to other scenario analyses would be a closer look at technology characteristics, as well as wind speed and resource modeling.

 

A possible scenario setup could also be to reach a certain desired level of wind power generation by different paths with respect to applied technology and regional distribution. The results can be illustrated in terms of key parameters, such as total system costs and the electricity price wind plants receive in the electricity market compared to average market prices.

 

Electric sector models will be used to explore these questions. The primary analysis will be conducted using Balmorel, an economic and technical partial equilibrium model that simulates the power system and least-cost dispatch. Supplemental analysis of relevant regions may be conducted using e.g. PLEXOS, a production cost model widely used by the electric industry.

Objectives

In our current research activities, Task 26 work consists of three primary objectives.

  1. To provide insight and intelligence on the cost of wind energy and key drivers of historical trends.
  2. To provide perspective on the potential future costs of wind energy and insight into variables that could drive costs higher or lower over time.
  3. To explore the value components of wind power, which have become increasingly important as energy sector planners and grid operators anticipate a future with significantly higher penetrations of variable renewable resources and societies seek to transition their economies and workforces in accord with increasing supplies of renewable energy.

Work Packages

Work Package 1

Historical Onshore and Offshore Wind Power Costs and Drivers

This work package (WP) supports transparency and insight into current wind energy cost trends, annual costs, and technology trends data for onshore wind installations in each of the participating countries. All data will be made available to IEA Wind and the public through shareable templates or the existing web-based data viewer.

WP1 also includes three additional activities:

  1. Modeling onshore operations and maintenance costs to gain a better understanding of life extension and repowering decisions and drivers.
  2. Exploring methods and analyses that seek to quantitatively assess the drivers of technology and plant differences among the participating countries.
  3. Conducting an in-depth analysis of onshore wind repowering in Denmark, which has many repowering projects and large datasets available, and comparing ongoing repowering activity in other countries. This research will collect insights on key indicators, reasons behind repowering projects, and the economic drivers and characteristics of repowering projects.

Work Package 2

Future Onshore and Offshore Wind Power Costs and Drivers

This work package supports the characterization and understanding of future trends in wind energy costs. Estimates of future wind technology cost and performance help inform understanding of impacts from potential research and development activities, as well as innovations on wind technology. Under WP2, IEA Task 26 participants will implement a new expert survey that focuses on:

  1. Future LCOE and LCOE drivers
  2. Expectations for future technology development (turbine size and configuration)
  3. Offshore wind, especially given the recent declines in tender prices.

In addition, under this WP task participants will compile published data on the current and future status of wind power cost and performance into a catalogue that includes different technology and geographical areas.

Work Package 3

Explorations in the Value of Wind Power

Abundant supply during hours of very high wind generation can cause resource underutilization and drive wind energy prices lower. WP3 focuses on finding creative ways to understand, characterize, and potentially enhance the system value of wind. In this context, this work package contains two primary activities:

 

Activity 1: Data provision and tracking of market value for onshore and offshore wind

Closely connected to the data tracking efforts on cost and performance elements in WP1, this activity ensures a continuous dialogue on the topic and supports data integration into other Task 26 work products.

 

Activity 2: Levelized Revenue of Energy

In recent years, estimating LCOE for wind power has taken a bottom-up approach by estimating different cost elements. However, auction results, which are based on different designs and conditions, are rarely directly comparable to LCOE. Levelized revenue of energy (LROE) provides the option to calculate all revenues of a project including payments based on auction results over the lifetime of a project. The LROE concept can include auction results as a central element for estimating the cost of wind power and can help calibrate input assumptions for bottom-up cost modeling.

The following work subtasks support the cost analyses of wind energy conducted by Task 26:

  • Subtask A) Defining the concept of LROE by identifying the different components and methodologies, including:
  • Revenue from support/procurement schemes over the project lifetime
  • Revenue from power markets over the project lifetime
  • Grid connection cost estimates, if not included
  • Projected power prices over the project lifetime
  • Definitions of weighted average cost of capital (WACC) assumptions.
  • Subtask B) Applying the identified concepts from Subtask A to auction results from the participating countries to establish a comparable overview on auction results across countries.

 

Activity 3: Modeling the Value of Wind

Another way to boost the value of wind energy is having access to cost-competitive electricity storage that allows facilities to capture generated electricity for later when the electricity is more valuable. With this idea in mind, several manufacturers are offering hybrid generation systems that combine wind power and storage technologies. Under this activity, Task 26 will use the power system model Balmorel to explore ways to boost the value of wind and investigate the interaction between wind turbine design and on-site storage availability.

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