Performance Curves

Exceedance

Both

Currently, all exceedance performance curves, which define the loss and uncertainty of a given parameter, are specified by the user by setting mean and SD of a distribution or by importing a .CSV containing the distribution. Utilize the generated time series data to auto-generate all possible performance curves.

Moderate

IEC Uncertainty and Losses

Exceedance

Coding

A framework for estimating the loss and uncertainty of a pre-construction net energy estimate has been proposed in IEC 61400-15 (https://www.nrel.gov/docs/fy21osti/79631.pdf). While it may be argued that the exceedance performance curve approach is a better method, it would also be beneficial to show estimates generated using the more simplified approach presented in IEC 61400-15 compare. This project will require a new C# class to execute the various calculations and a new GUI to display results and receive user input.

Challenging

OpenTopo API

Input

Coding

Connect to OpenTopography API and download elevation Geotiff data for project's turbine and met layout.

Easy

Complete

NREL Wind Data API

Input

Coding

Connect to NREL's API to download 20-year wind dataset to use as 'pseudo met towers'

Easy

Met Data Reader Improvement

Input

Coding

Improve met data time series reader to be more flexible with headers

Moderate

LT Reference Datasets

LT Reference

Both

Incorporate other LT reference datasets (ERA6, Japan JRA, Australia BOM)

Challenging

Machine Learning in MCP

MCP

Both

Incorporate machine learning algorithm

Moderate

Paused

QC Flag Enhancement

Met Data QC

Coding

Allow for user specified filters Set filter metric (min/max/avg/sd) and min/max ranges Manually set filters (sensor and start/end dates)

Moderate

Wind flow model machine learning improvement

Model

Both

Improve how wind flow model coefficients are found using a more sophisticated ML algorithm

Moderate

Wake Loss modeling

Net Turbine Ests

R&D

Wake loss model parameters (function of terrain complexity, wind conditions, etc). Sensitivity on wake expansion, TI, wake combination method.

Easy

Extreme Shear user-defined bins

Site Conditions

Coding

Allow users to specify bins for shear stats

Easy

Extreme WS modeling

Site Conditions

R&D

R&D: Gust factors by WD, season, stability. WMO gust factor analysis/comparison

Moderate

Sound model time series

Site Suitability

Coding

Use hourly temperature data to calc atm absorption and predict sound level on time series.

Easy

Sound model improvement

Site Suitability

Both

Accounting for hub height and elevation changes in sound model. Revisit other contributing factors to sound propagation (terrain type, buildings, Etc)

Moderate

In Progress

Ice throw model

Site Suitability

R&D

R&D: How to model rotating bodies? Analyze shape, mass, cross-sectional area distributions and how they impact estimates.

Easy

Shadow flicker model

Site Suitability

Both

Add directional component (i.e. yaw) to shadow flicker estimates

Easy

Time based losses

Time Series Analysis

Both

Time series based losses. Use CDFs to describe downtime duration and frequency. Use start/end dates for seasonal losses (e.g. icing)

Challenging

Turbine siting optimization

Turbine

Both

Create function to found turbine layout which optimizes net energy production and minimizes shadow flicker (optional)

Challenging

Turbine WS/Energy uncertainty estimate

Uncertainty Analysis

R&D

Revisit/improve how uncertainty is estimated at turbine locations

Moderate