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DOE OSTI2024

Identifying Potential Sub-Synchronous Oscillations Using Impedance Scan Approach: Preprint

This paper presents an impedance scan study on the real-world power system in Australia that has observed 17 to 20 Hz intermittent subsynchronous oscillations. Through the impedance scan of each of the IBRs, both individually and collectively, potential resonance modes are identified. The impedance scans were carried out using electromagnetic transient PSCAD models of the network. The network comprises of site-specific, black-boxed models of IBRs supplied by the generators. The impedance scan approach was divided in three major steps: (1) the first step is to identify IBRs where impedance analysis needs to be performed based on the magnitude of oscillations observed at their points of interconnection (POIs); (2) the second step focuses on performing impedance scans at selected IBRs in single-machine infinite-bus (SMIB) configuration to identify internal resonance modes of an IBR and to evaluate if any of these modes become unstable under certain grid conditions; (3) the third step performs impedance scans at a few selected IBRs while connected to the wider network model to obtain the impedance response of both the IBR and the grid - this step evaluates control interactions among IBRs. The impedance scan study found that a few IBRs have an underdamped resonance mode at around 17 Hz, which becomes unstable under a certain operating condition. Another interesting finding was that certain IBRs increase the effective grid impedance seen by another IBR in proximity for a particular operating condition. Under this operating condition, the resulting subsynchronous oscillation mode is more pronounced due to a combination of control interactions among IBRs through the transmission network under study and a resonance mode inside the IBRs.

control interactions↗
DOE OSTI2024

Adaptive Narrowband Damping for Improving Harmonic Stability of Modular Multilevel Converter: Preprint

Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To resolve it, this paper proposes an adaptive narrowband damping control that automatically programs, adds and adjusts damping around the oscillation frequency when detect the oscillation. The paper first presents a low-pass filter design for MMC control loops, which pushes all negative damping of MMC impedance down to the medium frequency range (< approximately 1000 Hz). This makes narrowband damping can be more targeted and easier to design because multiple harmonic oscillations are avoided. An adaptive damping control that uses online oscillation detection is then proposed, which can automatically configure the narrowband damper to provide damping to the MMC at the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper adjusts the damping gain (e.g., to zero when system resonance disappears) and the width of the damping range automatically based on continuous monitoring of system resonance conditions. Electromagnetic transient (EMT) simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.

active damping↗
DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems: Preprint

For the development of multi-terminal high voltage DC (MTDC) transmission, it is critical to design the protection system that can selectively isolate the faulty area from the healthy part of the dc grid using DC circuit breakers (DCCBs) while ensuring continuous operation of converter stations in the healthy part. However, because of the lack of fault current blocking capability in half-bridge (HB) modular multilevel converters (MMCs), when a dc fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of MMCs in the healthy part. Large DC reactors are often considered in series with DCCBs to reduce the rate of rise of fault currents and prevent blocking of MMCs in the healthy part of the grid. However, large DC reactors can prohibitively increase the cost of the system, particularly when they are considered in an offshore environment, for instance in offshore wind projects. Large dc reactors can also introduce stability issues and create post-fault oscillations. This paper presents an adaptive fault current limiting control method for MMCs to avoid their blocking and enable continuous operation of MTDC systems. It contains two parts: The first part is based on circulating current feedforward control that emulates virtual reactors in each arm of an MMC, which is immediately activated when the fault current starts to increase, to reduce the rate of rise of the fault current; the second part is triggered when the fault current exceeds a preset threshold by temporarily bypassing the SMs, serving as a complement to the fault current limiting effect of the first part. Both parts do not require fault detection signal and they are activated automatically during faults. Simulation case studies of a four-terminal bipolar MMC-HVDC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗
DOE OSTI2024

Distributed Wind and Impacts of FERC Order No. 2222 Implementation

In September of 2020, FERC issued Order No. 2222, directing ISOs to adjust their long-standing tariffs and participation models to enable the operation of distributed energy resource (DER) aggregators in wholesale energy markets. The rule sought to bring wholesale markets under its jurisdiction up to speed with existing expansion of DERs across the United States and to capture the potential benefits that these technologies can provide. This report describes the implementation of FERC Order No. 2222 and the compliance plans that have been submitted so far, attempt to understand the potential impact the rule may have on distributed wind, and provide opportunities for future work to analyze and encourage deployment under these policy conditions. There is an information gap for the type of market interactions distributed wind may have or how it could be best deployed in DER aggregations under future market conditions. There is significant potential for profitable deployment of distributed wind in states that are served by ISOs and covered under Order No. 2222. Distributed wind and other DERs provide local energy that does not need to travel those distances and avoids the losses typically associated with long-distance energy transmission. Deployment of distributed wind can benefit communities that exist away from large load centers by providing local, clean, and affordable energy. Aggregating DERs that include distributed wind could provide these benefits across multiple far-ranging communities if they have access to participate in wholesale markets. A new baseline valuation of distributed wind in areas covered by Order No. 2222 is required to accurately gauge where it is profitable and how it can compete or complement existing or future DER deployment, including as part of an aggregate.

17 WIND ENERGY↗
DOE OSTI2021

Cybersecurity Guide for Distributed Wind Presentation

This presentation communicates information about the MIRACL project Resilience Metrics report and Resilience Framework report. It was created for the 2021 MIRACL advisory board meeting. Distributed wind sits at the intersection of grid-connected, off-grid and behind-the-meter cyber-physical electrical energy systems. The unique physical properties and communications requirements for distributed wind systems mean that there are unique cybersecurity considerations, but there is little to no existing guidance on best practices for cybersecurity. This presentation is intended to be a starting point for distributed wind stakeholders including manufacturers, installers and integrators, and operators (facility, aggregator, or utility). A holistic threat perspective is used to describe the adversaries, threats, and potential impacts of cyberattacks, with special emphasis on what sets distributed wind systems apart from other distributed energy resources (DER). We present the recommendations for cybersecurity, both in terms of needs of the system and roles that specific stakeholders should fulfill. Distributed wind systems can come in a variety of architectures and applications, so there is no one-size-fits-all approach to cybersecurity. However, this document contains the relevant information for stakeholders to identify the cybersecurity needs of their system, refer to relevant standards, and apply best practices in a manner most consistent with their security and operational goals.

17 WIND ENERGY↗
DOE OSTI2021

Cybersecurity Guide for Distributed Wind

Distributed wind sits at the intersection of grid-connected, off-grid and behind-the-meter cyber-physical electrical energy systems. The unique physical properties and communications requirements for distributed wind systems mean that there are unique cybersecurity considerations, but there is little to no existing guidance on best practices for cybersecurity. This document is intended to be a starting point for distributed wind stakeholders including manufacturers, installers and integrators, and operators (facility, aggregator, or utility). We discuss common distributed wind architectures and describe their role in the larger power system, pointing out some of the key connections to be aware of. Cybersecurity cannot exist in a vacuum, but rather must consider all the system and all its connections holistically. The role of distributed wind and the functions it can serve are described to gain understanding of the full range of capabilities. The purpose and application of relevant standards that may apply to certain distributed wind systems is presented. These standards may not apply to all installations, but even for systems that are not required to meet these standards they can be a good reference for best practices. A holistic threat perspective is used to describe the adversaries, threats, and potential impacts of cyberattacks, with special emphasis on what sets distributed wind systems apart from other distributed energy resources (DER). Finally, we present the recommendations for cybersecurity, both in terms of needs of the system and roles that specific stakeholders should fulfill. Distributed wind systems can come in a variety of architectures and applications, so there is no one-size-fits-all approach to cybersecurity. However, this document contains the relevant information for stakeholders to identify the cybersecurity needs of their system, refer to relevant standards, and apply best practices in a manner most consistent with their security and operational goals.

17 WIND ENERGY↗
DOE OSTI2021

Deliverable D11 – Data Sharing, Storage, Security Protocols, and a Specification of a Potential Data Sharing Portal

Pacific Northwest National Laboratory (PNNL) and Technical University of Denmark (DTU) completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research for the International Energy Agency (IEA) Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future. As part of the work plan, Deliverable D11 requires the development of data sharing, storage, and security protocols for metadata to be stored on the platform, if needed. The specification of a potential data sharing portal that expands on the catalog is also required.

17 WIND ENERGY↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
DOE OSTI2020

Tools Assessing Performance

For the distributed wind industry, it can be challenging to accurately predict the performance and annual energy production of projects prior to their installation. The U.S. Department of Energy’s Tools Assessing Performance (TAP) project aims to improve wind resource characterization, thereby reducing the uncertainty of project performance and financing costs, increasing consumer confidence, and lowering the levelized cost of distributed wind energy. A collaborative effort among DOE National Laboratories, TAP will create a computational framework that provides the distributed wind community with access to newly developed wind resource data and modeling capabilities. These capabilities will allow users to perform timely and accurate performance assessments for distributed wind projects at locations across the United States.

wind, distributed, tools, performance↗
DOE OSTI2023

2022 Prototype Installation and Testing Awardee: Windward Engineering

The 60-kilowatt (kW) Zephyr 21/60 wind turbine from Windward Engineering uses a low-cost, full-span independent pitch system that can act as a redundant aerodynamic braking system. This design uses a relatively simple pneumatic rotary vane actuator, allowing each of the turbine's three blades to be pitched independently and any single blade to activate emergency braking for the entire turbine. A previous Competitiveness Improvement Project (CIP) funding award enabled Windward Engineering to design and develop the Zephyr 21/60 wind turbine's aeroelastic model and pitch system. At the end of this current Competitiveness Improvement Project award, a fully validated aeroelastic model will make it possible to certify Windward Engineering's Zephyr 21/60 design and quantify the technology's levelized cost of energy in preparation for certification and entry into the distributed wind market. The Zephyr 21/60 will feature an attractive levelized cost of energy, improved reliability, and a full-span pitch system for safe and redundant protection against rotor overspeed (which occurs when the rotor turns beyond its design limit).

CIP↗
DOE OSTI2021

2020 System Optimization Awardee: Carter Wind Turbines

With support from the Competitiveness Improvement Project's System Optimization Award, Carter Wind Energy aims to lower the cost of distributed wind technology and expand deployment. To do so, the company will improve the cost-effectiveness and reliability of midsize wind turbines for remote, off-grid power applications, creating new wind energy deployment opportunities worldwide. This fact sheet provides an overview of Carter Wind Energy's project, how the company will achieve the goals of the award, and how the project fits within the overall Competitiveness Improvement Project.

CIP↗
DOE OSTI2024

Distributed Wind for Commercial Loads

Distributed wind can help meet on site energy and resilience needs for a wide variety of commercial loads .While it is a variable resource, it has predictable daily and annual production trends. The presence of on-site renewable generation can enhance resilience, supplying power for long periods of time without worrying about conserving fuel supply. The addition of properly sized storage or complementary solar resources can further reduce the challenges of intermittency and reduce the need for fuel-limited backup power during outage situations. This fact sheet explores further the energy and resilience requirements of commercial loads and how distributed wind may be a good match to meet their load needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Distributed Wind for Commercial Loads

Distributed wind can help meet on site energy and resilience needs for a wide variety of commercial loads .While it is a variable resource, it has predictable daily and annual production trends. The presence of on-site renewable generation can enhance resilience, supplying power for long periods of time without worrying about conserving fuel supply. The addition of properly sized storage or complementary solar resources can further reduce the challenges of intermittency and reduce the need for fuel-limited backup power during outage situations. This fact sheet explores further the energy and resilience requirements of commercial loads and how distributed wind may be a good match to meet their load needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Proof-of-concept of a reinforcement learning framework for wind farm energy capture maximization in time-varying wind

Here, we present a proof-of-concept distributed reinforcement learning framework for wind farm energy capture maximization. The algorithm we propose uses Q-Learning in a wake-delayed wind farm environment and considers time-varying, though not yet fully turbulent, wind inflow conditions. These algorithm modifications are used to create the Gradient Approximation with Reinforcement Learning and Incremental Comparison (GARLIC) framework for optimizing wind farm energy capture in time-varying conditions, which is then compared to the FLOw Redirection and Induction in Steady State (FLORIS) static lookup table wind farm controller baseline.

17 WIND ENERGY↗
DOE OSTI2022

Aeroelastic Modeling for Distributed Wind Turbines: March 11, 2021 - November 10, 2021

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine whereby providing an understanding of the impact of design parameters on its loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the Distributed Wind Technology (DWT) sector is limited, especially within the less established manufacturers. This project represents an in-depth assessment of the status of AM and its role within the Standards for the DWT industry. The study gathered input and feedback from a large number of national and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed recent industry workshops' and meetings' minutes, collected publicly available AM templates, and provided an evaluation of the existing AM codes. The study achieved several goals including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation (V&V), which includes discussions of measurement requirements and a sample test-plan useful for future V&V campaigns and design standard development. This document summarizes the different tasks conducted in the course of the project and highlights the steps required to improve the AM adoption based on a multifaceted approach that encompasses: 1) augmenting AM software capabilities, 2) publishing AM best-practices and design-basis, 3) creating new model templates, 4) providing guidance for V&V of codes and specific turbine models leveraging field testing best-practice, and 5) addressing weaknesses in the current standards. Many of the future objectives identified in this study could leverage NREL's upcoming testing campaigns of three modern distributed wind turbines. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool resulting in a more efficient design process, an easier path to certification, and overall better and more distributed reliable wind turbine products.

17 WIND ENERGY↗
DOE OSTI2023

Setting the Baseline: The Current Understanding of Equity in Land-Based Wind Energy Development and Operation

As discussions about economic equity and environmental justice have become more prevalent in recent years, the related concepts of "energy justice" or "energy equity" have received increasing attention from policymakers, industry, nonprofits, and academics. According to the Initiative for Energy Justice (2019), energy justice is defined as "The goal of achieving equity in both the social and economic participation in the energy system, while also remediating social, economic, and health burdens on those disproportionately harmed by the energy system" The state of equity as it applies specifically to wind energy, however, remains relatively unexplored and isolated to academia. As a result, the National Renewable Energy Laboratory's Wind Energy Equity Engagement Series aims to better understand equity in wind energy through engagement with experts and communities, including representation in decision-making around new developments, potential impacts to communities near wind energy installations, and community-level distribution of the benefits and burdens of wind energy. This report covers the first three phases of the series.

17 WIND ENERGY↗
DOE OSTI2021

Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) Research: Controls

Advanced Turbine Control for Distributed Wind Deployments: The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) research initiative is funded by the U.S. Department of Energy’s Wind Energy Technologies Office and led by researchers at the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia). The initiative’s controls research seeks to expand the benefits from distributed wind energy assets beyond solely providing low-cost power directly to consumers. To make these turbines operate more effectively, there is a need for more advanced ways to control them—allowing power companies, businesses, and energy consumers to take advantage of some of the unique technical characteristics of wind energy.

wind, Microgrids, Infrastructure, Resilience, Adva↗