Publications

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Wind energy development in the United States has been steadily growing over the past decade. This trend has resulted in the expansion of wind energy into areas that have a good wind resource but may have other deployment barriers being looked at more closely. One such barrier is that of the potential impact that wind turbines pose to radar systems. Wind turbines located within the line-of-sight of radar systems can cause clutter and interference and can result in performance degradation. Mitigation of any interference that wind turbines have on radar systems begins with the understanding of the potential those impacts to radar systems through modeling and simulation. The intent of this document is to catalog and provide the reader with a list of the modeling and simulation capabilities along with enabling databases for wind turbine — radar interference and related issues that are currently in use in various government agencies as well as those tools that are available to the public for free or fee. A brief description of the tool is given along with other pertinent characteristics of the tool including the owner, developers, user, classification, status, and the point-of-contact. This document does not provide an exhaustive description of the tools' capabilities nor does it include tools that were developed privately.

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As wind farms scale to include more and more turbines, questions about turbine wake interactions become increasingly important. Turbine wakes reduce wind speed and downwind turbines suffer decreased performance. The cumulative effect of the wakes throughout a wind farm will therefore decrease the performance of the entire farm. These interactions are dynamic and complicated, and it is difficult to quantify the overall effect of the wakes. This problem has attracted some attention in terms of computational modelling for siting turbines on new farms, but less attention in terms of empirical studies and performance validation of existing farms. In this report, Supervisory Control and Data Acquisition (SCADA) data from an existing wind farm is analyzed in order to explore methods for documenting wake interactions. Visualization techniques are proposed and used to analyze wakes in a 67 turbine farm. The visualizations are based on directional analysis using power measurements, and can be considered to be normalized capacity factors below rated power. Wind speed measurements are not used in the analysis except for data pre-processing. Four wake effects are observed; including wake deficit, channel speed up, and two potentially new effects, single and multiple shear point speed up. In addition, an attempt is made to quantify wake losses using the same SCADA data. Power losses for the specific wind farm investigated are relatively low, estimated to be in the range of 3-5%. Finally, a simple model based on the wind farm geometrical layout is proposed. Key parameters for the model have been estimated by comparing wake profiles at different ranges and making some ad hoc assumptions. A preliminary comparison of six selected profiles shows excellent agreement with the model. Where discrepancies are observed, reasonable explanations can be found in multi-turbine speedup effects and landscape features, which are yet to be modelled.

Sandia's Continuous Reliability Enhancement for Wind (CREW) Program is a follow on project to the Wind Plant Reliability Database and Analysis Program. The goal of CREW is to characterize the reliability performance of the US fleet to serve as a basis for improved reliability and increased availability of turbines. This document states the objectives of CREW and describes how data collected for CREW will be used in analysis. A critical aspect to the success of the CREW project is data input from participating owner/operators. The level of detail and the quality of input data provided dictates the type of analysis that can be accomplished. Options for analysis range from high level availability summaries to detailed analysis of failure modes for individual equipment items. Specific types of input data are identified followed by samples of the type of output that can be expected along with a discussion of benefits to the user community.

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Wind turbines have grown in size and capacity with today's average turbine having a power capacity of around 1.9 MW, reaching to heights of over 495 feet from ground to blade tip, and operating with speeds at the tip of the blade up to 200 knots. When these machines are installed within the line-of-sight of a radar system, they can cause significant clutter and interference, detrimentally impacting the primary surveillance radar (PSR) performance. The Massachusetts Institute of Technology's Lincoln Laboratory (MIT LL) and Sandia National Laboratories (SNL) were co-funded to conduct field tests and evaluations over two years in order to: I. Characterize the impact of wind turbines on existing Program-of-Record (POR) air surveillance radars; II. Assess near-term technologies proposed by industry that have the potential to mitigate the interference from wind turbines on radar systems; and III. Collect data and increase technical understanding of interference issues to advance development of long-term mitigation strategies. MIT LL and SNL managed the tests and evaluated resulting data from three flight campaigns to test eight mitigation technologies on terminal (short) and long-range (60 nmi and 250 nmi) radar systems. Combined across the three flight campaigns, more than 460 of hours of flight time were logged. This paper summarizes the Interagency Field Test & Evaluation (IFT&E) program and publicly- available results from the tests. It will also discuss the current wind turbine-radar interference evaluation process within the government and a proposed process to deploy mitigation technologies.

This paper attempts to describe the options to expand the scope of the current Interagency Field Test & Evaluation (IFT&E) objectives to include wind turbine encroachment on agency missions for offshore wind development in the United States. The options described here build on the recently completed IFT&E test campaigns that took place in 2012 and 2013. Those tests, which looked at the CARSR, ASR-11, ARSR-4, and eight proposed mitigation technologies, found that wind turbines can significantly impact the ability of radars to detect aircraft and meet mission requirements above and near wind farms. One of the more immediate successes of the IF&E Program is that today, several of the infill radar technologies which were tested, took the results of their IF&TE performance to move well beyond Technology Readiness Level 6/7 and some have been deployed and are operating at airports in the United Kingdom (UK). As well, the UK Ministry of Defense (MOD) has deployed the replacement radar which was tested to address specific concerns with especially concerning offshore wind farms. The UK MOD continues to test and hopes to refine these systems so that identified shortfalls in surveillance capability and operations which remain can be addressed. Wind energy has been steadily growing in the U.S. With a current capacity of over 60 GW today and the expectation that this capacity will need to grow to 300 GW to meet the U.S. Department of Energy's (DOE) goal of 20% wind energy in the future, offshore wind farms are gaining more attention. The specific impacts of wind turbine interference on maritime radars have not been determined at this time. However, the DOE did fund a study conducted by the University of Texas at Austin entitled, "Assessment of Offshore Wind Farm Effects on Sea Surface, Subsurface and Airborne Electronic Systems," that focused on identifying the broader Wind-Turbine/Radar Interference: Offshore Test Options SAND2014-17870 effects of electromagnetic interference expected to be caused by offshore wind farms.' A review of that study would be worth the reader's time. And while no comprehensive field studies have been accomplished, it is worth noting that many mitigation solutions that were tested I the IFT&E Program are derived from short-range maritime radar systems. The Wind and Water Power Technologies Office (WWPTO), within the DOE Office of Energy Efficiency and Renewable Energy, supports the development, deployment, and commercialization of wind and water power technologies. This report is funded by the WWPTO.

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This report investigates strategies to mitigate anticipated wind energy curtailment on Maui, with a focus on grid-level energy storage technology. The study team developed an hourly production cost model of the Maui Electric Company (MECO) system, with an expected 72 MW of wind generation and 15 MW of distributed photovoltaic (PV) generation in 2015, and used this model to investigate strategies that mitigate wind energy curtailment. It was found that storage projects can reduce both wind curtailment and the annual cost of producing power, and can do so in a cost-effective manner. Most of the savings achieved in these scenarios are not from replacing constant-cost diesel-fired generation with wind generation. Instead, the savings are achieved by the more efficient operation of the conventional units of the system. Using additional storage for spinning reserve enables the system to decrease the amount of spinning reserve provided by single-cycle units. This decreases the amount of generation from these units, which are often operated at their least efficient point (at minimum load). At the same time, the amount of spinning reserve from the efficient combined-cycle units also decreases, allowing these units to operate at higher, more efficient levels.

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