Sun Duck Curve: Why Fix the Cause, Not Just the Symptoms

In recent years, the adoption of rooftop solar for household electricity generation in Australia has been nothing short of remarkable.

Driven by high levels of solar radiation, falling PV (photovoltaic) costs, attractive feed-in tariffs and now climate change, rooftop solar has seen spectacular success. It is claimed that Australia is now the world leader in the use of rooftop solar energy.

This may seem like great progress, however, excess electricity generated by rooftop solar and exported to the grid creates major grid problems, as evidenced by the so-called duck curve.

Occurring primarily on clear days when excess household electricity significantly exceeds underlying load demand, distributable electricity generation is significantly reduced during daylight hours.

As sunset approaches, the dispatchable power must be rapidly increased to replace solar power, causing the shape of the net power curve to resemble that of a duck.

Identified in 2008, the duck curve was tagged the biggest problem facing photovoltaic power generation. The cause is the virtually uncontrolled generation of excess solar energy from domestic roof systems during the day on a clear day.

AEMO data for dispatchable and rooftop solar power generation for five consecutive clear days in mid-October 2020 for Western Australia is shown in Figure 1.

Fig 1: Network power flow

The data clearly shows that rooftop solar displaces other energy sources during the day by up to 50%. In the late afternoon, slow-to-react generators, especially coal, must be quickly revved up to replace dwindling solar power as the sun approaches.

The ramp-up must also meet the increase in underlying household load demand in the late afternoon, which puts additional pressure on the system.

Figure 2 illustrates the origin of the duck curve at the household level. Clear weather energy flows in a household with a rooftop solar installation are shown. It is assumed that the domestic load is 20 kWh per day and that a 4 kW photovoltaic generator has been added.

The load curve shows morning and late afternoon/evening peaks typical of home energy consumption. The PV power generated by the rooftop generator peaks at noon and totals 23.6 kWh over the day.

Roof power is supplied at home behind the meter (BTM) and is not directly metered by the retailer. The rooftop power significantly exceeds the household load during the day, eliminating the need for grid backup power during this time. Excess energy (negative values) equals 16.1 kWh, or 68% of the roof’s energy that day.

Excess energy is exported to the grid in front of the meter (IFM), attracting a small feed-in tariff (FiT) for the household. Backup energy equal to 12.5 kWh is still needed to meet the daily load after sunset and until the sun rises the next day.

Fig 2: Domestic energy flow in clear weather.

The IFM power curves for the house before and after the addition of a 4 kW PV array are shown in Fig 3. With no rooftop grid, the IFM power is in one direction only, from the grid at home. With the grid on the roof, the excess power exported from the house to the grid causes the duck-shaped profile (dashed red line in Fig. 3).

Fig 3: in front of the meter Energy flow (import/export) on a clear day.

As shown in Figures 2 and 3, the root cause of the duck curve problem is the large excess energy exported on clear days by households. During the day, this energy replaces the production of coal and other fossil fuels.

As sunset approaches, distributable generators that have been idle all day must be ramped up to compensate for the loss of PV output. Rapid ramp-up, especially of older coal-fired generators that were never designed for this purpose, is a major problem.

Grid-level solutions to the problem have focused on treating the symptoms rather than the cause.

For example, some states now have regulations in place allowing the competent authority to disable rooftop solar export (reduction) whenever major stability issues arise. With the continued growth of rooftop solar and the need to reduce carbon emissions, this solution is clearly not sustainable.

It is well recognized that large batteries can solve the problem by storing excess solar energy generated on the roof during the day to meet the peak domestic load in the evening.

However, to date, large batteries have not focused on energy storage, but rather on providing higher value ancillary services such as FCAS to the grid.

Since the problem starts at the bottom (households), it makes more sense to solve the problem there, using a bottom-up solution.

The solution to the problem is to reduce the export of excess domestic energy to the grid to manageable levels without reducing solar energy production and self-consumption. This can be achieved by storing excess energy using household batteries and other storage such as hot water.

An example of a home storage solution is adding an approximately 16 kWh battery to the home PV system shown in Fig. 2. This level of battery storage allows the household load to be fully satisfied that day without excess energy being exported to the grid. The IFM power flow is reduced to zero for the entire day, eliminating any household contribution to a duck curve problem.

However, without battery charge control, adding less storage can have a significant effect on the export energy profile.

Figure 4(a) shows the IFM curve from the previous example after adding 6 kWh of storage, enough to meet the household load during the peak ramp-up period from 3:00 p.m. to 9:00 p.m. If no battery monitor is in place, battery charging begins in the morning when PV power exceeds charging and ends when the battery is fully charged (on a clear day at 11:45 a.m.).

During this period, there is no power export to the grid as all available excess power is used behind the meter to charge the battery. Once the battery is fully charged, the power exported to the grid returns to its value without battery storage.

Later in the day, the stored energy feeds the peak period domestic load. However, the energy stored in the morning has no effect on the export of excess household electricity to the grid during the critical late afternoon period.

The solutions to this problem are to delay the start of charging later in the day or to control the charging current to spread the charge over a longer period. Figure 4(b) shows the IFM power curve for the afternoon load starting at 12:00 p.m.

It is seen that delaying the start of the load to noon removes both the afternoon excess energy exported to the grid and the load during the peak ramp-up period. IFM power flow is zero for an entire 9 a.m. period from noon to 9 p.m., solving many problems otherwise caused by the rapid ramp-up of dispatchable generators in the late afternoon.

Fig 4: Effect of battery charge period on excess energy export to the grid; (a) morning charge; (b) afternoon charges.

Our annual calculations using Perth radiation data confirm that the time of day, morning (AM) or afternoon (PM), at which battery charging is performed has a significant effect on the distribution of energy exported during the day. Figure 5 compares the afternoon energy export for the AM load with that for the PM load.

While increasing battery capacity decreases afternoon energy export for AM and PM charging, PM charging significantly reduces afternoon energy export.

With sufficient battery capacity, in this case 12 kWh, PM charging eliminates the export of domestic energy to the grid in the afternoon. These results show that controlled storage of home batteries can provide significant grid stabilization. No new infrastructure outside of batteries and controls is needed.

Fig 5: Effect of storage capacity and charging period on domestic energy exported to the grid during the afternoon.

Australia leads the rest of the world in the generation of rooftop solar panels. However, the same cannot be said for the use of household batteries.

For example, in Germany, around 70% of solar home systems had battery storage in 2020, with an average storage capacity of 8.5 kWh. In Australia in 2021, only ~2.8% of new PV installations included batteries.

Strong government incentives are now needed to significantly increase the adoption of household batteries. In its current form, the Small Scale Renewable Energy (SRES) program exacerbates the duck curve problem by incentivizing households to generate a large surplus of energy while at the same time no incentive is available. for home batteries to store and use excess energy.

Now is the time for the SRES to add effective incentives for home batteries. State and federal governments must lead the transition to home batteries, as was originally done with rooftop solar. Additionally, planning must begin for the day when household batteries provide a significant fraction of household energy needs.

Paul McCormick is Emeritus Professor of Mechanical Engineering at the University of Western Australia

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