FarmData: Data set for wind farm layout optimization.

In wflo: Data Set and Helper Functions for Wind Farm Layout Optimization Problems

Data set for wind farm layout optimization.

Description

This list object contains four matrices covering adjusted yield, wind speed, wind direction and standard deviations of wind directions in Germany.

Usage

FarmData

Format

A list object containing seven matrices, each containing 25 x 25 values at a raster resolution of 200 x 200 m (note that for the larger data set downloadable using AcquireData, each matrix contains 4400 x 3250 values):

$AdjustedYield: Yield is average annual energy production (AEP). According to FGW technical guidelines, AEP is adjusted due to different location qualities to obtain a better guess at the marketable energy output. Interpret these values directly as 'megawatt hours per year'.

$WindSpeed: Average wind speeds in meters per second.

$WindDirection: Average wind directions in degrees (azimuth system).

$SDDirection: Standard deviations of wind directions in degrees (azimuth system).

$Elevation: Terrain relief (elevation in meters).

$Slope: Terrain slope in degrees.

$SlopeDirection: Direction of hillside in degrees.

Note

If the full mode data set is present, it is loaded into the environment e. The built-in data set FarmData contains matrices of dimension 25 x 25, while the full data set e$FarmData consists of 4400 x 3250 matrices.

Author(s)

Carsten Croonenbroeck
David Hennecke

Source

DWD Climate Data Center (CDC): ftp://opendata.dwd.de/climate_environment/CDC/grids_germany/multi_annual/wind_parameters/resol_200x200/

FGW Technical Guidelines: https://wind-fgw.de/shop/technical-guidelines/?lang=en

Croonenbroeck, C. & Hennecke, D. Does the German renewable energy act provide a fair incentive system for onshore wind power? - A simulation analysis, Energy Policy, 2020, 114, 111663, 1-15, https://doi.org/10.1016/j.enpol.2020.111663

Examples

# 'Profit' uses this data set internally:
NumTurbines <- 4
set.seed(1357)
Result <- optim(par = runif(NumTurbines * 2), fn = Profit, method = "L-BFGS-B",
  lower = rep(0, NumTurbines * 2), upper = rep(1, NumTurbines * 2))
Result
PlotResult(Result)

wflo documentation built on Jan. 15, 2023, 5:10 p.m.