Read Me
Overview
EnergyApp serves as a predictive tool, enabling users to forecast
energy production and model CO2 emissions based on their energy policies.
The platform offers insights into five interconnected domains:
Energy,
Sankey,
Added Capacity,
Emissions,
Investment Cost
. Navigate to each
domain using the sidebar panel on the left.
This page showcases two charts:
Primary Energy
and
Useful Energy
, along with three tables:
Useful Energy Growth by Year
,
Growth Parameters
, and
Energy Parameters by Sector
. Here's how to utilize them:
- Start by selecting your desired country from the
Select Country
dropdown in the sidebar. Then, click on
Plot Data
and allow approximately 8 seconds for the data to load.
- The
Primary Energy
chart displays energy consumption
for the chosen country from 1965 to 2022. This data is sourced from the
Energy Institute
. Interact with the chart by toggling the legend or zooming into specific areas.
- The
Useful Energy
chart projects energy consumption
based on growth hypotheses by energy type and sector. Adjust energy use
efficiency by sector via the Sankey diagram. Sector details are
elaborated in the
Sankey Diagram
section.
To alter growth rates, double-click a value in the
Energy Parameters by Sector
table. The growth functions
employed are detailed bellow. The
Total Simulated
curve is derived using a growth function that considers the
Country Growth Init
Country Growth Final
and
Time constant
values from the
Growth Parameter
table.
The
Total
curve sums up all useful energy, aiming
to align total useful energy with total simulated.
- The
Useful Energy Growth by Year
table presents the growth rates of individual energy types and
the overall growth of useful energy. By default, calculations
span the past decade, but you can adjust this range using the
Growth Calculation from X Years
parameter.
- After making adjustments, click
Plot Data
to view the changes.
To preserve your modifications, use the
Download
option in the sidebar. Import saved data by selecting
Browse
.
- The
growth model employs the equation:
World example classical growth
World example fast growth
France example classical growth
Primary energy
Useful energy
Useful energy growth by year
Growth parameters
Energy parameters by sector
Read Me
Overview
The Sankey diagram provides a visual representation of energy flow. By adjusting the
Select Year
option in the sidebar, you can view projections
of future energy flows. For these calculations, we have assumed that
the proportion of final useful energy consumption remains consistent with 2022 figures.
To construct this, we referenced the Sankey diagram provided by
IEA
. Using
this data, we introduced the
Share
column in the
Energy Parameter by Sector
table. We incorporated data from
Lawrence Livermore National Laboratory
and other sources to create the
Neta
column,
representing the efficiency of energy utilization across various sectors.
You have the flexibility to modify any parameter within this table.
Following the IEA's structure, we have categorized energy use into four primary sectors:
-
Indus
: Denotes industrial energy consumption.
-
Trans
: Pertains to energy consumption in transportation.
-
Other
: Covers energy use in both commercial and residential sectors.
-
NEnU
: Represents non-energy use, which we assume
gets converted into objects or waste without CO2 emissions.
-
Elect
: Refers to electricity energy consumption.
Sankey diagram
Pie chart primary energy in twh
Pie chart useful energy in twh
Energy parameter by sector
Read Me
Overview
This section showcases twelve charts. Here's a breakdown:
-
Capacity Added
: Represents the absolute utility
added in a specific year. It's derived by dividing the new energy
produced in that year by 8760 hours (total hours in a year).
-
Capacity Added with Charge Factor
: Uses data
from 'Capacity Added' and divides it by a charge factor. This
helps determine the actual capacity added. Adjust the charge
factor for Nuclear, Solar, or Wind in the
Parameters
table.
-
Total Capacity with Charge Factor
: Calculates
the cumulative capacity by adding the previously installed capacity
to the new capacity for a specific year.
-
Nuclear surface yearly, Solar panel surface yearly, Wind turbine surface yearly
: Indicates the surface required for installation yearly. Modify
these values in the
Parameters
table.
-
Nuclear reactor number, Solar panel number, Wind turbine number
: Indicates the number of units required for installation. Modify
these values in the
Parameters
table.
-
Nuclear surface, Solar surface, Wind surface
: Indicates the surface required for installation. Modify
these values in the
Parameters
table.
Capacity Added
Capacity Added with charge factor
Total capacity with charge factor
Nuclear surface yearly
Solar surface yearly
Wind surface yearly
Parameters
Nuclear reactor number
Solar panel number
Wind turbine number
Nuclear surface
Solar surface
Wind surface
Read Me
Overview
In this display, the primary chart features a line on the left
illustrating CO2 emissions over time, and on the right, a line
representing the absolute CO2 budget.
Within the table
CO2 Parameters
, you have the flexibility to adjust
each parameter except for fossil fuels. The parameter
CO2 Max World
denotes the CO2 budget as of 2020. To ensure global warming remains below 1.5°C,
our carbon budget was set at 800 GT CO2 in 2020.
To determine CO2 emissions, we solve the following equation
either per country or globally:
We then apply our coefficients to the primary energy data to calculate CO2 emissions. These coefficients can be viewed in the CO2 Parameters table. Within this table, you also have the option to modify CO2 emissions for different energy sources. By default, these values are set to zero, reflecting our focus on primary energy.
Source
CO2
CO2 budget
CO2 parameters
CO2 per personae in MtCo2/pers
Population in billion
Read Me
Overview
In this section, you'll find three charts:
-
Annual cost
represents the expense for new capacities.
-
Cumul cost
reflects the expense of capacities added since 2022.
-
Cost
denotes the cost per watt
of various energy sources at a given time. To project future prices,
we use an experience coefficient. Whenever the installed capacity
doubles, we estimate:
new price = old price X Expérience coefficient
You can adjust the experience coefficient in the
Experience coefficient
table
and energy cost in the
Energy cost
table.
One constraint of our current analysis is the omission of energy storage costs.
We aim to incorporate this aspect in upcoming iterations.