9.6) Observing Cumulative Effects

In this plot we can see a sigmoid transition curve where PV installations had a slow start, then takes off but flattens out toward the end of the simulation run. With such a system dynamics it is important to know where on the time axis the take off phase is. Where the monitor gives us only the current value (usually the final one after a run), the plot indicates the speed of such an adoption curve. However, to measure that quantitatively we would like to know what happens below the curve, or to measure cumulatively how much energy is generated from solar panels. For that we need a new global variable called total-PV-generation and then sum up all the PV-output from all houses with PV every year.

• First, define the new variable total-PV-generation in the globals [], and set it to 0 in the setup
• Second, at the end of the go procedure sum up all the PV-output from all houses with PV and add it to the already existing value, as follows:

set total-PV-generation total-PV-generation + sum [PV-output] of turtles with [PV]

• Third, insert a monitor reporting the total PV generation. You can just use the total-PV-generation variable in the reporter. As this is in kWh, with many installations and over 50 years it will be a large number, so you might want to divide it by 1000 to display MWh or by 1000000 to get GWh.

This allows us now to assess different subsidy policies regarding the end goal after 50 years (PV fraction), the pattern of adoption (plot and view), and the cumulative effect (total PV electricity generation).