Wind and Solar Fuel Distribution Across Europe

Visual Design
#1

Guideline: Hi, I have used Tableau to use my data to generate a Geographic visualisation of Wind and Solar Fuel Distribution across Europe.
The reasoning for this plot have been inspired by articles [1] and [2] in an attempt to visualise patterns in the locations of these plants, and perhaps see if it is influenced by patterns in the jet stream and/or geographical location.
The visual design type was selected as a result of learning the advantages of Geo Maps from website [3].

Dash1
Dash1943×783 185 KB

Visual Design Type: Digital / Geographic Map
Name of Tool: Tableau
Country: Europe
Year: All.
Visual Mappings:

  • Detail - Name of Plant
  • Color - (Green = Wind, Red = Solar)

Data Source: http://datasets.wri.org/dataset/globalpowerplantdatabase
Data Preperation:

Filters

  • Primary Fuel - (Wind, Solar)
  • Country - (European Countries)

Information Source: Integration of wind and solar power in Europe: Assessment of flexibility requirements -
https://www.sciencedirect.com/science/article/pii/S0360544214002680 [1]
Jet stream wind power as a renewable energy resource: little power, big impacts - https://pure.mpg.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_1693453 [2]

https://www.idashboards.com/blog/2017/08/02/5-provocative-map-data-visualizations/ [3]

Question:

  • Do you feel like the visualisation clearly displays geographical trends in wind and solar plants?
  • Would you recommend any additional data to be marked to perhaps convey greater information to the user?
  • Is the use of color mapping optimal?
  • Would you recommend perhaps using an alternative visualisation technique that could display the desired patterns more clearly?

Thanks in advance.

#2

Hello, very nice visualisation!
To answer your questions:

  1. The visualisation clearly shows where plants are located, however there is some visible overlapping of data which may make it hard to tell if there are plants of the other variety in the same location.

  2. Where this overlap occurs the number of each plant could be indicated, also the amount of power plants produce could be included to more reliably represent the scale of fuel distribution within some area.

  3. I believe the colour mapping is indeed optimal, clearly showing the different classes of power plant.

  4. A cloreopathic map could be used with countries broken into their states, the map could then be colour mapped to represent class of plant. This would show us less precise locations for individual plants, however may more clearly indicate states preferences in fuel distribution.

#3

Thank you for your response, this is definitely advice I will apply when making future visualisations.