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Energy supply and consumptionElectricity consumption and generationElectricity generation by renewable sourceProduction and consumption of gas and fuel type
Visual encoding
Visual encoding
Visual encoding
Visual encoding
Visual encoding
Data Visualisation: Australia’s energy crisis and renewable energy
1. Background and motivation
Currently, the energy problem is considered as a serious issue in many countries including Australia which is one of the major energy producers in the world market. In June 2022, Australia faced an energy crisis with energy prices spiked and significant unplanned outages. From this case, it conducts a struggle on Australia's energy crisis and many people might not have a well understanding of the existing situation. In addition, renewable energy has become a sustainable and alternative way for this issue. From all mentioned reasons, which are the strong motivation of this project to gather all data about Australia's energy to support people's understanding and to increase their awareness.
2. Visualisation Tool
3. Data Source
This project's data originates from statistics data on energy.gov.au, which is government-provided public data contained in an Excel file. The attribute includes categorical data such as year and month, fuel type, and state, in addition to ratio/quantitative data of energy or electricity production and consumption statistics number.
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4. Visualisation Design
Energy overview balance and Energy consumption (%)
The page Energy Overview Balance which is combine 2 data visualisations in the same page. The first and second figure, it demonstrates energy productivity and energy index compare with GDP, the second figure shows energy production compare with energy consumption.
The dataset type of this visualisation is line graph to show the data trend along recorded years. So, the x-axis is year record data, for the y-axis, there are numerical data about energy index and energy balance.
As every row is encoded in a single point on the chart connected with line to show trend along year record. The value of year determines the horizontal position of the point, and the value of energy index and energy balance determines its vertical position.
According there are few data category in each graph, these figures also use colour hue as channels to express the data categories.
Energy production and Energy consumption plots with Fuel type
The page Energy production with fuel type and Energy consumption with fuel type have similar design. The dataset type of this visualisation is bar chart to demonstrate the data trend which is numerical type by yearly record.
For this visualisation, it is expected to show data trend change over the time and show the change of composition (this case is the portion of fuel type category). So, stacked bar chart is suitable to be implemented for this figure.
This visualisation is encoded with the length of chart to determine the energy level. Additionally, it uses colour hue to identify fuel type categories.
Energy mix by state
The visualisation Energy mix by state with fuel type is also stack bar chart to identify the consumption (%) of energy of each state categorised by fuel types.
The stacked bar chart is implemented for this data due to it can show the change of composition (fuel type) compared to other state easily.
This visualisation is encoded with the length of chart to determine the percentage of energy consumption and colour hue is used to demonstrate fuel type categories
Electricity generation and Electricity by Fuel
The first figure, this visualisation of electricity generation compares renewable energy-generated electricity to other types of power generation. For this visualisation, data trend changes over time relative to the category is indicated. Therefore, an area chart is one of the suitable chart types for this figure. This visualisation is encoded with the area underneath the chart to display the electricity level, and colour is also utilised to identify fuel type categories.
The second figure, this visualisation is used to demonstrate electricity generation categorised by fuel type that change along the year. So, the stack bar chart is utilised for this figure which bar length encode the numerical data, and colour hue encode the categorical data.
Electricity generation by renewable energy
For this visualisation, it aims to demonstrate the value of electricity generated by each renewable energy. On the left is a stack bar chart with the same concept as the prior chart; the user can see the change of the overall trend over time. On the right is a pie chart that displays the same data but allows the user to specify a single year to illustrate the portion of electricity generation by different renewable energy in each year.
This pie chart uses area as a mark, and it also use area as channel to encode the amount of electricity generated by each renewable energy type which is quantitative attribute. In addition, it uses colour hue to encode categorical data that is renewable energy type.
5. Conclusion
The project, which is intended to demonstrate an overview of Australia's Energy and Electricity through visualisation, demonstrates how to accomplish an interactive visualisation project. To guide further project development, it is necessary to identify the project's objectives first. Following this, the data sourcing and requirement planning is the next key step which is helps to identify the right metrics and key feature for visualisation. Then, developing data story form cleaned data source and select the appropriate visual that follow the story and can provide the answer to project objective. Finally, adding visualisations and some relevant elements to the dashboard to be benefit for the users.
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