PrintAs we learned previously, the demand for electricity varies throughout the day and year, and so does solar irradiance. For example, the residential electricity demand rises in the morning to peak just before noontime, and then it levels out up until the evening peak, when everyone gets home from work and starts using electricity. And that pattern repeats itself over and over with some variations between summer and winter seasons, as seen in the left curves on Figure 12.1. We can also see that this curve is location dependent. There are key characteristics to this daily demand profile, such as the two daily peaks and then a base load demand.
As we said earlier, utilities became experts at predicting these values to better trade their electricity, and also, more importantly, to plan the operating schedule for the power plants. This planning helps optimally and economically operate their power plants to meet the base loads (usually coal or nuclear) and the additional capacity to meet the peak demands (such as Natural gas).
The load demand had been under control up until the distributed generation sources got introduced to the grid, which are variable and unexpected. Although the idea of meeting the peak demand is very appealing and is actually beneficial, excessive addition of these resources such as solar will change the load profile in such a way that utilities have to get out of their comfort zones and address these changes by meeting the new demand profiles.
Since our class focuses on solar systems, let’s take the solar effect as an example: Integrating a small amount of PV capacity doesn’t raise any technical issues to the grid, as long as the PV capacity is not concentrated in areas where the grid is weak and demand is low. However, when adding PV capacity in larger scales, the main concern from the grid and utilities point of view will be the supply and demand balance. One of the main issues that the solar arrays have are the inability to schedule its operating as compared to traditional coal plants, for example. The sun may shine as predicted, or it might not shine at all. In addition, solar only contributed in the best scenario to the daytime demand profile rather than the daily profile, and that contribution lowers the base load on the utility demand, but it disappears in the evening time.