This paper presents work by the International Energy Agency's Task 26 'Cost of Wind Energy' on technological and cost trends in land-based wind energy in six participating countries (Denmark, Germany, Ireland, Norway, Sweden, United States) and the European Union between 2008 and 2016. Results indicate that there is a general trend towards larger, taller machines with lower specific powers resulting in higher capacity factors, despite small falls in new site wind resources in most countries, while wind project capital costs and project finance costs also fell. This resulted in an average levelized cost of energy (LCOE) fall of 33% for new projects to 48/MWh at the end of the study period. Analysis of the components of levelized cost change indicated that changes in specific power, financing cost and capital cost accounted for 45%, 25% and 17% respectively of the estimated reduction. It is therefore important that trends in technological factors such as specific power are considered when assessing wind energy learning rates, rather than just capital costs, which has been the primary focus heretofore. While LCOEs have fallen, the value of wind energy has fallen proportionately more, meaning grid parity appears no closer than at the beginning of the study. Policymakers must therefore consider both the cost and value of wind energy, and understand the volatility of this gap when designing land-based wind energy policy measures.

This chapter focuses on considerations made when modeling cost of energy to be used in any of the abovementioned applications. The level of fidelity required to model each of the four, primary cost of energy elements depends on the characteristics of the wind power plant under consideration. Some "top -down" models utilize empirical data to reflect currently installed wind power plants, while physics -based, or "bottom up," models may be implemented to estimate aspects of future wind -power -plant technology. Regardless of the ultimate application of cost of energy modeling, it is important to carefully assess the wind-power-plant characteristics to determine the type of model and the level of fidelity required to represent each of the four cost of energy elements.

Author(s): Mone, Christopher; Hand, Maureen; Bolinger, Mark; Rand, Joseph; Heimiller, Donna; Ho, Jonathan

This report provides a deeper understanding of the wind project development process, from desktop studies to a successful project in the ground. It examines three siting consideration categories that wind project sponsors must include in the development process: wildlife (species that live in, near, or migrate through the area where wind development is possible), radar (wind turbines can cause interference with radar signals), and public engagement (representing communities and stakeholders who live near wind power projects). The research shows that although this country's abundant wind resource provides numerous options for addressing siting considerations, actually siting individual projects is becoming more difficult because of regulatory and other uncertainties. Model results are based on the premise that developers will be able to site, permit, and build successful projects, which is not always the case in reality.

This deck was presented for the 2016 Annual Technology Baseline Webinar. The presentation describes the Annual Technology Baseline, which is a compilation of current and future cost and performance data for electricity generation technologies.

Current and future cost and performance data for electricity generating technologies, including both renewable and conventional technologies.

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends—in part—on the future costs of both onshore and offshore wind. Here, we summarize the results of an expert elicitation survey of 163 of the world’s foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24–30% reductions by 2030 and 35–41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R&D and industry strategy. Further global deployment of wind energy, both onshore and offshore, will depend on its future costs. Wiser et al. report the results of a survey of 163 leading experts on the possibilities of cost reduction and technological advancements by 2050.

Renewable Electricity Futures Study - Volume One. This is part of a series of four volumes describing exploring a high-penetration renewable electricity future for the United States of America. This data set is provides data for the entire volume one document and includes all data for the charts and graphs included in the document.

Author(s): Wiser, Ryan; Jenni, Karen; Seel, Joachim; Baker, Erin; Hand, Maureen; Lantz, Eric; Smith, Aaron

This report builds from a similar previous analysis (Schwabe et al., 2011) exploring the differences in cost of wind energy in 2008 among countries participating in IEA Wind Task 26 at that time. The levelized cost of energy (LCOE) is a widely recognized metric for understanding how technology, capital investment, operations, and financing impact the life-cycle cost of building and operating a wind plant. Schwabe et al. (2011) apply a spreadsheet-based cash flow model developed by the Energy Research Centre of the Netherlands (ECN) to estimate LCOE. This model is a detailed, discounted cash flow model used to represent the various cost structures in each of the participating countries from the perspective of a financial investor in a domestic wind energy project. This model is used for the present analysis as well, and comparisons are made for those countries who contributed to both reports, Denmark, Germany, and the United States.

Recent work found that renewable energy could supply 80% of electricity demand in the contiguous United States in 2050 at the hourly level. This paper explores some of the implications of achieving such high levels of renewable electricity for supply chains and the environment in scenarios with renewable supply up to such levels. Expanding the renewable electricity supply at this scale by 2050 implies annual capacity additions of roughly 20 gigawatts per year (GW/year) over the next decade, rising to roughly 40 GW/year from 2040 to 2050. Given total 2012 renewable electricity capacity additions of slightly more than 16 GW, this suggests moderate growth of the related supply chains, averaging overall roughly 4% annual growth to 2040. Transitioning to high renewable electricity supply would lead to significant reductions in greenhouse gas emissions and water use, with only modest land-use implications. While renewable energy expansion implies moderate growth of the renewable electricity supply chains, no insurmountable long-term constraints to renewable electricity technology manufacturing capacity or materials supply are identified. (C) 2013 Elsevier Ltd. All rights reserved.

This paper presents high renewable electricity penetration scenarios in the United States using detailed capacity expansion modeling that is designed to properly account for the variability and uncertainty of wind and solar resources. The scenarios focus solely on the electricity system, an important sector within the larger energy sector, and demonstrate long-term visions of a U.S. power system where renewable technologies, including biomass, geothermal, hydropower, solar, and wind, contribute 80% of 2050 annual electricity, including 49–55% from wind and solar photovoltaic generation. We present the integration challenges of achieving this high penetration and characterize the options to increase grid flexibility to manage variability. Four high renewable pathways are modeled and demonstrate the robustness and diversity of renewable options. We estimate 69–82% annual greenhouse gas emission reductions and 3%–30% incremental electricity price increases associated with reaching 80%-by-2050 renewable electricity relative to reference scenarios. This paper affirms and strengthens similar analysis from the Renewable Electricity Futures study by using an improved model and updated data to better reflect investment and dispatch decisions under current outlooks for the U.S. electricity sector.

This paper highlights the key results from the Renewable Electricity (RE) Futures Study. It is a detailed consideration of renewable electricity in the United States. The paper focuses on technical issues related to the operability of the U. S. electricity grid and provides initial answers to important questions about the integration of high penetrations of renewable electricity technologies from a national perspective. The results indicate that the future U. S. electricity system that is largely powered by renewable sources is possible and the further work is warranted to investigate this clean generation pathway. The central conclusion of the analysis is that renewable electricity generation from technologies that are commercially available today, in combination with a more flexible electric system, is more than adequate to supply 80% of the total U. S. electricity generation in 2050 while meeting electricity demand on an hourly basis in every region of the United States.

With Balance of System (BOS) costs contributing up to 30% of the installed capital cost, it is fundamental to understand the BOS costs for wind projects as well as potential cost trends for larger turbines. NREL developed a BOS model using project cost estimates developed by industry partners. Aspects of BOS covered include engineering and permitting, foundations for various wind turbines, transportation, civil work, and electrical arrays. The data introduce new scaling relationships for each BOS component to estimate cost as a function of turbine parameters and size, project parameters and size, and geographic characteristics. Based on the new BOS model, an analysis to understand the non‐turbine wind plant costs associated with turbine sizes ranging from 1-6 MW and wind plant sizes ranging from 100-1000 MW has been conducted. This analysis establishes a more robust baseline cost estimate, identifies the largest cost components of wind project BOS, and explores the sensitivity of the capital investment cost and the levelized cost of energy to permutations in each BOS cost element. This presentation shows results from the model that illustrate the potential impact of turbine size and project size on the cost of energy from US wind plants.

The decreased costs of solar technologies have led to the prospect of a move for photovoltaic (PV ) and concentrating solar power (CSP ) from niche applications to major contributors to the U.S. electricity grid. This development has motivated a number of technoeconomic analyses of the potential deployment of both PV and CSP under varying economic conditions. Two studies sponsored by the U.S. Department of Energy (DOE ) and completed in 2012 can help us understand the potential opportunities and challenges for solar deployment on a large scale. These studies evaluated both the potential mix of renewable energy technologies that could serve a large fraction of the U.S. electricity demand and the associated evolution of the U.S. grid to 2050.

Over the past 30 years, wind power has become a mainstream source of electricity generation around the world. However, the future of wind power will depend a great deal on the ability of the industry to continue to achieve cost of energy reductions. In this summary report, developed as part of the International Energy Agency Wind Implementing Agreement Task 26, titled 'The Cost of Wind Energy,'we provide a review of historical costs, evaluate near-term market trends, review the methods used to estimate long-term cost trajectories, and summarize the range of costs projected for onshore wind energy across an array of forward-looking studies and scenarios. We also highlight the influence of high-level market variables on both past and future wind energy costs.