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At least 253 records · Page 14

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

17 WIND ENERGY↗

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Climate impacts on hydropower in Colombia: A multi-model assessment of power sector adaptation pathways

There is uncertainty as to how climate change will affect hydropower generation in different regions of the world. In drying regions, impaired hydropower production could result in significant changes to the power sector implying new plants to be installed to make up for lost hydropower generation. In this article we apply two partial equilibrium models (TIAM-ECN and GCAM) and two general equilibrium models (Phoenix and MEG4C) to identify possible pathways of power sector adaptation for Colombia under climate change scenarios that reflect altered water inflow to hydropower reservoirs. Each model is run for two emissions policy scenarios and for a dry and moderate climate projection. Planned hydropower expansion for Colombia is insufficient to meet increased power demands as the country's economy grows; the contribution of hydropower to Colombia's power supply drops from ~65% currently to 30 - 50 % by 2050 depending on energy model and scenario. Climate change reduces this by a further 5 - 10 % under the dry climate projection. Climate-driven losses in hydropower will be compensated by an expansion of alternative technologies, which vary significantly across models. When climate policy is implemented, three distinct pathways emerge: expanding the electricity production from solar and wind energy (TIAM-ECN); reducing overall power demand hence exploiting savings and efficiencies (Phoenix and MEG4C); and expanding the use of fossil resources—primarily natural gas— complemented with carbon dioxide capture and storage (GCAM).

Arango, Santiago↗

Opportunities and Implications for Low-Cost Hydrogen Production from Water Electrolysis in a Decarbonizing Power Sector

Increased deployment of renewable power generation such as wind and solar photovoltaics along with electrification of transportation and other sectors are driving changes in the operation and economics of the electric power sector. Simultaneously, efforts to decarbonize other sectors of the economy such as steelmaking and heavy duty transportation will require significant amounts of electricity to drive electrons to molecules processes. Hydrogen production via water splitting electrolysis is a key near-term technology for decarbonization that interfaces between the power sector and decarbonization efforts in industrial sectors. This poster examines the implications for increased deployment of water electrolyzers in a rapidly evolving energy system. The economic opportunities for low-cost hydrogen production from electrolysis that are facilitated by highly renewable grids will be examined and discussed. Durability, cost, and operational strategies for electrolyzers interacting in these future energy systems are key to enabling hydrogen at scale. This poster will overview these considerations and ongoing work within the U.S. Department of Energy’s H2NEW consortium that is focused on addressing them.

electrolysis↗

Validation of Wind Power Plant Modeling Approaches in Complex Terrain: Preprint

The effect of terrain on wind-plant aerodynamics is often neglected due to the complex dynamics that make up terrain-atmosphere-turbine interactions and the computational effort required to adequately resolve the relevant physics. In this work, a comprehensive set of measurements (from the Wind Forecast Improvement Project 2) and two distinct modeling approaches are used to investigate the effects of topography on plant performance. The first approach consists of high-fidelity large-eddy simulations conducted for a one- hour period on a terrain-resolving mesh, and producing unsteady, heterogeneous flow that is sensitive to the local topography. The second approach makes use of a steady-state engineering model that has been modified to account for terrain effects. In situ and remote- sensing measurements upstream of the wind plant are used to prescribe initial and boundary conditions to the models, while wind turbine power measurements are used to assess the ability of the different models to capture the effects of terrain on turbine wake dynamics and therefore power production. The full paper will quantify the degree to which our high-fidelity and engineering models are able to capture realistic wind plant aerodynamics in complex terrain, and through improved understanding of the underlying physics, inform our model development efforts.

17 WIND ENERGY↗

MOD-2 wind turbine development

The development of the Mod-2 turbine, designed to achieve a cost of electricity for the 100th production unit that will be competitive with conventional electric power generation is discussed. The Mod-2 wind turbine system (WTS) background, project flow, and a chronology of events and problem areas leading to Mod-2 acceptance are addressed. The role of the participating utility during site preparation, turbine erection and testing, remote operation, and routine operation and maintenance activity is reviewed. The technical areas discussed pertain to system performance, loads, and controls. Research and technical development of multimegawatt turbines is summarized.

Gordon, L. H.↗

Modelling and control coordination scheme of a wind‐to‐hydrogen set for future renewable‐based power systems

New challenges regarding system stability and efficiency arise when power systems operate with a high penetration level of inverter‐based renewable sources (IBRSs) and few synchronous generators. Since IBRSs have been on the rise, to secure the stable operation of future power systems, IBRSs will be required to support systems without having to rely on remaining synchronous generators. Also, to efficiently manage the uncertainty of renewable production, power‐to‐gas technology can provide the required flexibility. This study proposes modelling and a control coordination scheme (CCS) of a wind‐to‐hydrogen (W2H) set to optimise electricity production from a variable‐speed wind turbine generator (WTG) while helping balance between supply and demand in a system. To achieve this, a grid‐forming (GFM) inverter‐based WTG is modelled and a set of electrolyser and fuel cell is integrated at the DC circuit of a GFM‐WTG to be coordinated. Furthermore, the CCS offers an opportunity to reduce the investment cost for deploying a W2H set by utilising the control capabilities of a WTG and reducing the need for an additional device. The performance of the proposed W2H set with the CCS was verified considering the variations in system load and wind speed by using Power System Computer Aided Design (PSCAD)/ElectroMagnetic Transients including Direct Current (EMTDC).

Kim, Jinho↗

Land-Based Wind Market Report: 2022 Edition

Wind power additions in the United States totaled 13.4 gigawatts (GW) in 2021. Recent growth is supported by the industry’s primary federal incentive—the production tax credit (PTC)—as well as a myriad of statelevel policies. Long-term improvements in the cost and performance of wind power technologies have also been key drivers for wind capacity additions, even as supply chain constraints due to increased commodity and transportation costs and COVID-19 restrictions push costs higher.

17 WIND ENERGY↗

Stochastic Methods for Planning and Operating Power Systems with Large Amounts of Wind and Solar Power: Preprint

Wind and solar generators differ in their generation characteristics than conventional generators. The variable output and imperfect predictability of these generators face a stochastic approach to plan and operate the power system without fundamentally changing the operation and planning problems. This paper overviews stochastic modeling challenges in operations, generation planning, andtransmission planning, with references to current industry and academic work. Different stochastic problem formulations, including approximations, are also discussed.

17 WIND ENERGY↗

EVALUATING THE COMPETITIVENESS OF ENERGY STORAGE FOR MITIGATING THE STOCHASTIC, VARIABLE ATTRIBUTES OF RENEWABLES ON THE GRID

Energy storage has recently attracted significant interest as an enabling technology for integrating stochastic, variable renewable power into the electric grid. To meet the renewable portfolio standards targets imposed by 29 U.S. states and the District of Columbia, electricity production from wind technology has increased significantly. At the same time, wind turbines, like many renewables, produce power in a manner that is stochastic, variable, and non-dispatchable. These attributes introduce challenges to generation scheduling and the provision of ancillary services. To study the impacts of the stochastic variability of wind on regional grid operation and the role that energy storage could play to mitigate these impacts, Pacific Northwest National Laboratory (PNNL) has developed a series of linked, complex techno-economic-environmental models to address these key questions: a. What are the future expanded balancing requirements necessary to accommodate enhanced wind turbine capacity, so as to meet the renewable portfolio standards in 2020? Specific analyses are conducted for the four North American Electric Reliability Corporation (NERC) western sub-regions. b. What are the most cost-effective technological solutions for providing either fast ramping generation or energy storage to serve these balancing requirements? PNNL applied a stochastic approach to assess the future, expanded balancing requirements for the four western sub-regions with high wind penetration in 2020. The estimated balancing requirements are quantified for four sub-regions: Arizona-New Mexico-Nevada (AZNMNV), California-Mexico (CAMC), Northwest Power Pool (NWPP), and Rocky Mountain Power Pool (RMPP). Model results indicate that the new balancing requirements will span a spectrum of frequencies, from minute-to-minute variability (intra-hour balancing) to those indicating cycles over several hours (inter-hour balancing). The sharp ramp rates in the intra-hour balancing are of significant concern to grid operators. Consequently, this study focuses on analyzing the intra-hour balancing needs. A detailed, life-cycle cost (LCC) modeling effort was used to assess the cost competitiveness of different technologies to address the future, intra-hour balancing requirements. Technological solutions considered include combustion turbines, sodium sulfur (NaS) batteries, lithium ion (Li-ion) batteries, pumped-hydro energy storage (PHES), compressed air energy storage (CAES), flywheels, redox flow batteries, and demand response (DR). Hybrid concepts are also evaluated. For each technology, distinct power and energy capacity requirements are estimated. LCC results indicate that the most cost competitive technologies include electrochemical energy storage and Na-S and Li-Ion. This finding is consistent among the four sub-regions and is generally applicable to other regions.

arbitrage↗

Analyzing storage for wind integration in a transmission-constrained power system

High levels of energy from variable generation sources such as wind and solar photovoltaics (PV) can result in significant curtailment, in which the wind and PV energy cannot be used to serve demand. Adding transmission and energy storage can assist in reducing renewable curtailment, but the relative merits of each enabling technology individually or combined is not well understood. Thus, we compare the role of transmission and storage in reducing curtailment, as well as reducing generation costs from conventional sources. Using a high-fidelity model of the electric power grid, we examine a scenario in which the western portion of the U.S. and Canada reaches 37% energy from wind and 12% energy from solar PV. In the case studied, we find that transmission is generally more effective than energy storage in reducing curtailment, due to the curtailment patterns of wind. However, the interaction between transmission and energy storage shows that the two technologies act symbiotically, meaning that their combined energy value is greater than that of each individually. This analysis demonstrates that fully realizing the benefits of wind resources located far from demand centers will require an effective method to deliver wind power at the right times to the right locations.

17 WIND ENERGY↗

Voight variable speed drive

The variable speed drive transmission is mounted within the gondola and connected with the wind turbine blades and the hub. This unit is designed for the production of ac power. The turbine turns by means of the variable speed drive and a set of synchronous three phase generators. This motion is controlled automatically by two wind rosettes in such a way that the wind turbine always opposes the wind direction. The Voight variable speed drive is a mechanical variable positive drive gear transmission. It has an unlimited power and torque transmission, a constant ratio with high degree of accuracy, a speed variation over a wide range, and a nonslip drive.

Tompkin, J.↗

Dispatchability Maximization for Co-Optimized Energy and Reserve Dispatch With Explicit Reliability Guarantee

In this paper, we consider dispatchability as the set of all admissible nodal wind power injections that will not cause infeasibility in real-time dispatch (RTD). Our work reveals that the dispatchability of the affine policy based RTD (AF-RTD) is a polytope whose coefficients are linear functions of the generation schedule and the gain matrix of affine policy. Two mathematical formulations of the dispatchability maximized energy and reserve dispatch (DM-ERD) are proposed. The first one maximizes the distance from the forecast to the boundaries of the dispatchability polytope subject to the available production cost or reserve cost. Provided the forecast value and variance of wind power, the generalized Gauss inequality (GGI) is adopted to evaluate the probability of infeasible RTD without the exact probability distribution of wind power. Combining the first formulation and the GGI approach, the second one minimizes the total cost subject to a desired reliability level through dispatchability maximization. Efficient convex optimization based algorithms are developed to solve these two models. Different from the conventional robust optimization method, our model does not rely on the specific uncertainty set of wind generation and directly optimizes the uncertainty accommodation capability of the power system. The proposed method is also compared with the affine policy based robust energy and reserve dispatch (AR-ERD). Case studies on the PJM 5-bus system illustrate the proposed concept and method. Experiments on the IEEE 118-bus system demonstrate the applicability of our method on moderate sized systems and its scalability to large dimensional uncertainty.

17 WIND ENERGY↗

A Synthetic Nickel Electrocatalyst With a Turnover Frequency Above 100,000 s-1 for H2 Production

Increased worldwide energy demand will require greater use of carbon-neutral sustainable energy sources. The intermittent nature of solar and wind power requires storage of energy, so electrocatalysts that convert electrical energy to chemical bonds in fuels are needed. Platinum is an excellent catalyst, but it is of low abundance and high cost. Hydrogenase enzymes in Nature catalyze the evolution of H2 and use earth-abundant metals such as nickel and iron. We report that a synthetic nickel catalyst, [Ni(7PPh2NPh)2](BF4)2, (7PPh2NPh = 1,3,6-triphenyl-1-aza-3,6-diphosphacycloheptane) catalyzes the production of H2 using [(DMF)H]+OTf as the proton source, with turnover frequencies of 31,000 s-1 in dry acetonitrile and 108,000 s-1 in the presence of H2O (1.2 M), at a potential of -1.13 V (vs. the ferrocenium/ferrocene couple). These turnover frequencies exceed those reported for the [FeFe] hydrogenase enzyme by more than an order of magnitude, and are the fastest reported for any molecular catalyst for H2 production. This material is based upon work supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences.

17 WIND ENERGY↗

Analysis of the Effects of a Flexible Ramping Ancillary Service Product on Power System Operations: Preprint

The recent increased interest in utilizing variable generation (VG) resources such as wind and solar in power systems has motivated investigations into new operating procedures. Although these resources provide desirable value to a system (e.g., no fuel costs or emissions), interconnecting them provides unique challenges. Their variable, non-controllable nature in particular requires significant attention, because it directly results in increased power system variability and uncertainty. One way to handle this is via new operating reserve schemes. Operating reserves provide upward and downward generation and ramping capacity to counteract uncertainty and variability prior to their realization. For instance, uncertainty and variability in real-time dispatch can be accounted for in the hour-ahead unit commitment. New operating reserve methodologies that specifically account for the increased variability and uncertainty caused by VG are currently being investigated and developed by academia and industry. This paper examines one method inspired by the new operating reserve product being proposed by the California Independent System Operator. The method is based on examining the potential ramping requirements at any given time and enforcing those requirements via a reserve demand curve in the market-clearing optimization as an additional ancillary service product.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Kansas Wind Energy Consortium

This project addresses both fundamental and applied research problems that will help with problems defined by the DOE “20% Wind by 2030 Report”. In particular, this work focuses on increasing the capacity of small or community wind generation capabilities that would be operated in a distributed generation approach. A consortium (KWEC – Kansas Wind Energy Consortium) of researchers from Kansas State University and Wichita State University aims to dramatically increase the penetration of wind energy via distributed wind power generation. We believe distributed generation through wind power will play a critical role in the ability to reach and extend the renewable energy production targets set by the Department of Energy. KWEC aims to find technical and economic solutions to enable widespread implementation of distributed renewable energy resources that would apply to wind.

17 WIND ENERGY↗

Using Electric Vehicles to Mitigate Imbalance Requirements Associated with an Increased Penetration of Wind Generation

The integration of variable renewable generation sources continues to be a significant area of focus for power system planning. Renewable portfolio standards and initiatives to reduce the dependency on foreign energy sources drive much of the deployment. Unfortunately, renewable energy generation sources like wind and solar tend to be highly variable in nature. To counter the energy imbalance caused by this variability, wind generation often requires additional balancing resources to compensate for the variability in the electricity production. With the expected electrification of transportation, electric vehicles may offer a new load resource for meeting all, or part, of the imbalance created by the renewable generation. This paper investigates a regulation-services-based battery charging method on a population of plug-in hybrid electric vehicles to meet the power imbalance requirements associated with the introduction of 11 GW of additional wind generation into the Northwest Power Pool. It quantifies the number of vehicles required to meet the imbalance requirements under various charging assumptions.

24 POWER TRANSMISSION AND DISTRIBUTION↗