Curves & grids: the space-time dance of flattening loads for full electrification
The new electric world
A world without fossil fuels will be primarily electric. Several sectors, previously powered by fossil fuel combustion, progressively pivot to electricity.
An easy enough example to observe is transportation. Cars, vans, and trucks progressively turn electric. Boats and planes will follow.
Homes provide another example. Heating will follow cooling and become electric-powered, as water heating and cooking appliances.
The pivot toward electric energy changes the electric grid, which entails two consequences.
More demands for the grid
First, both generation and grid must grow significantly. The power previously supplied by fossil fuels turns into electricity, resulting in a need for more power lines. Secondly, the “behavior” of the grid may change.
The demand for power in the grid varies daily and seasonally because our energy needs change throughout the hours and the months. At night, we consume less energy than during the day.
Some months will require more power than others. Cold regions need more energy in the winter for heating. Warm places need more energy to cool during the summer.
Hence, when new demands join the grid, its behavior can change.
Car charging
As more cars turn electric, the hours at cars charge can shift power demand curve.
If most car owners decide to charge at peak demand, then peak demand will grow. In this case, grid operators must plan to build more power plants. Conversely, if policies make car owners charge during hours of low demand, grid operators can better use existing power plants. The latter is better than the former.
It’s better to have fewer power plants working at all hours than multiple plants that work sporadically. It’s expensive to build power plants with fewer opportunities to sell energy to pay for construction. It’s more economical to make fewer power plants, selling their energy most of the time.
Cars are an excellent practical example. Figure 1 shows the total daily energy demand share by the hour, comparing the data of 2019 (blue line) with two estimates for 2070 (yellow and green) when electric vehicles will be dominant.
In the yellow line scenario, EVs charge without any policy to address their added loads. Charging loads concentrate at the beginning and end of the day. In the green line, there are policies in place to address the added loads from EVs.
By comparing the blue and yellow lines, you can see what can happen when policies don’t account for the EV loads. Car charging increases peak loads and leads to more power plants with more idle time, a bad result.
When comparing blue and green lines, you see the advantages of managing EV charging loads. The curve flattens. The grid is more balanced since there are fewer differences between power demands during the day. EV charging loads shift to the night, leading to fewer power plants producing energy more frequently: a better result.
Beyond EVs, the electrification of space, water heating, and cooking appliances also affect the grid. The grid’s overall demand increases, as do the peak loads. But there are some caveats, as the new technologies are more efficient than those they replace.
A study for ERCOT, the Texas grid, simulated the effect of replacing heating furnaces for heat pumps in residential buildings.
The study found that the power demand for the residential sector could increase as much as 36% (an extra 12 GW). The ERCOT grid would have to add 10 GW in new power plants to meet the winter peak from residential heating.
However, the average domestic energy consumption would remain approximately the same. Heat pumps can work both for heating and cooling and are more efficient than air conditioners they would replace.
A similar study for Italy included electric water heating and cooking and heat pumps for space heating. From a baseline, it created four different scenarios.
The first scenario changed cooking appliances to electric ovens and induction cooktops. In the second scenario, heat pumps provide space heating. Heat pumps deliver water heating in the third scenario, while the fourth scenario combines the previous three.
Figure 2 shows the result.
Predictably, scenery 4 displays the highest energy consumption and peak. You can also see how peak power varies and shifts with different technology.
Peaks also depend on use rather than solely the technology itself.
Scenario 1, the one with electric cooking appliances, is a great example.
People cook more at home during lunch and dinner. Hence, scenario 1 shows two marked peaks around lunch and dinner. Since more people dine at home than at lunch, the major peak happens between 18h and 21h.
Space heating use is less concentrated. On cold days, people need heat while at home. However, since a significant share of people leaves home for work, heating power demand is higher at the beginning of the day before leaving home and at the end of the day when returning at night when the temperature drops further.
The case of hot water, in scenario 3, is another example of how the mix between technology and use affects performance. An induction cooktop draws much power when in use but non when switched off.
Other appliances have a more spread energy consumption during the day, like a refrigerator that must always be on to perform its task. Most water heat pumps are like refrigerators but throw the heat into a water tank instead of the outside air.
It’s easier and cheaper to balance a grid with a flatter demand curve than one full of ups and downs. So refrigerators and water heat pumps are more friendly to grid operators by helping with flatter curves.
It is also important to stress that electrification does increase energy consumption; it lowers it. It shifts it all to electricity, so you use more electricity, not more energy.
Before full electrification, there were electric and natural gas bills. Once you go full electric, you have only an electric bill for everything. But compared the energy spending, electric appliances are more efficient than gas alternatives, resulting in less energy and emissions.
