Market price and solar: a simple model

Presentation of a simple model to predict future capture prices of renewables

This post presents a method to assess the capture price of solar. It is a bit more technical and “energy-geeky” than the previous posts.

Renewable energy sources, spearheaded by the expansion of wind and solar power, are poised for remarkable growth in the foreseeable future, spanning both years and decades. Of particular note is the current rise of solar energy, as extensively explored in our previous discussions. This surge in solar power is exerting a profound influence on the electricity market, as detailed in our prior examinations of market volatility and the phenomenon of price cannibalization.

In this post, we are going to explore how electricity prices¹ will develop in the coming years. Of course, our certainty is limited to events that have already transpired, and predicting future prices remains an intricate challenge. Nonetheless, in this endeavor, we aim to outline a straightforward model that may offer some insights into potential developments.

Let’s dig in together.

Germany in 2030

In this article, our focus shifts to Germany. As of the present, the installed capacity of solar, onshore wind, and offshore wind stands at 63 GW, 58 GW, and 8 GW². Notably, the Easter Package, approved in 2022, envisions a future landscape featuring 215 GW of solar, 115 GW of onshore wind, and 30 GW of offshore wind. This ambitious plan effectively signifies a near-doubling of onshore wind capacity and a remarkable tripling of both solar and offshore wind capacity within a mere 8-year span.

Furthermore, as electric vehicles become more prevalent, heat pumps gain traction and industrial processes increasingly transition to electricity, we anticipate a surge in electricity demand. In 2022, total electricity consumption reached 484 terawatt-hours (TWh), and our projections indicate a substantial one-third increase, bringing it to 644 TWh. This translates to an average load of 73.5 gigawatts (GW).

Residual load and the models used

The models we employ use the notion of residual load, which is essentially the difference between the load and the combined generation from wind and solar sources. The day-ahead market price is intricately tied to this residual demand, a connection depicted in the graph below.

Within this post, we introduce two formulas that establish a connection between the residual load and the market price:

1. Formula 1: A linear correlation.

2. Formula 2: Constant for any positive residual load.

Both of these formulas are visualized in the graph below. The similarity between them lies in the fact that market prices are consistently zero when dealing with negative residual demand. Importantly, it's worth noting that both formulas yield the same average market price when applied to the data from 2022.

Metrics used

Through simulating the model for each hour of the year, we derive comprehensive data on total wind and solar generation alongside their respective market prices. The product of these values yields the market value of the generated electricity. Subsequently, we can deduce the annual capture price for wind and solar.

Our focus lies on solar energy, thus the installed solar capacity is the pivotal variable in our simulations. In the case of wind energy, we assume that the ambitious 2030 targets may not be fully achieved³. We anticipate a 60% growth in onshore wind capacity, reaching 93 GW, while offshore wind capacity is projected to double, reaching 16 GW.

Results

The initial and logical outcome suggests that as solar penetration rises, the average market prices tend to decline. These results have been normalized based on the value corresponding to the lowest solar capacity, which currently stands at 70 GW.

The solar capture rate, which serves as an indicator of the cannibalization effect, likewise exhibits a decreasing trend as the installed solar capacity increases.

The solar capture rate is determined based on the average market price, and, as previously observed, this rate diminishes with increasing solar capacity. When considering the cumulative impact, we can describe it as the solar value relative to a situation with "low solar penetration," which corresponds to the current installed solar capacity. This can be regarded as the anticipated value that solar energy will capture in the future when compared to the present installed capacity. Our findings indicate a 21% capture rate with the linear correlation (formula 1) and a 41% capture rate with the constant relation (formula 2) for the 2030 target.

Perhaps even more surprising, the total solar value—representing the cumulative market value of all solar power generation—increases until it reaches a peak, after which it begins to decline. This intriguing phenomenon implies that, beyond this peak, the addition of more solar panels leads to a decrease in the overall market value of all the combined solar panels. Notably, both of these peak values are expected to be attained prior to the 215 GW target set for 2030.

The high concentration of solar

Solar energy exhibits a significantly higher concentration compared to wind energy. The graph below illustrates the relationship between the total energy produced (y-axis) and the number of hours⁴ (x-axis). Strikingly, within a mere 1000 hours, half of the solar energy output is generated, and it takes less than 2000 hours to account for 80% of the total solar generation. This clear contrast in concentration between solar and wind energy is evident in the graph.

As solar capacity expands, a natural consequence is the rise in the occurrence of negative residual loads. For instance, with a solar capacity of 180 GW, we would observe approximately 1000 hours characterized by negative residual loads. This period accounts for roughly 50% of the total energy generated by the solar capacity.

Direct consequence

As capacity expands, the economic incentive to invest in additional capacity naturally diminishes. In general, this market price risk is transferred to another entity, which can be either the government when direct support mechanisms such as Feed-in Tariffs or Contracts-for-Difference are in place or a buyer with a corporate Power Purchase Agreement (PPA).

With a substantial share of renewables, the scenario unfolds as follows:

1. Corporate Off-Taker Perspective⁵: Procuring electricity from a solar power plant may become less appealing for corporate off-takers, as alternative options in the market might offer more attractive terms.

2. Government Perspective: Supporting renewables through fixed-income models like FiTs or CfDs would become increasingly more expensive. This is because the captured value in the market diminishes, even though the payments to producers remain constant. This issue becomes particularly pronounced after the maximum total solar value, as adding more solar capacity leads to a lower total market value⁶.

To provide a concrete illustration, let's consider a scenario that falls midway between the two formulas. In this case, the value of solar would amount to approximately 31% of its current value if the 215 GW target is achieved. Assuming that future electricity prices in the coming years hover around 125 €/MWh⁷, solar would capture approximately 39 €/MWh under similar circumstances.

Limitations

Evidently, this simple model has various limitations. Here are a few of them:

1. Exchanges with neighboring countries

While Germany is not in isolation and has the potential to export energy surplus, the feasibility of exporting surplus solar energy appears limited. This is primarily because many neighboring countries are following a comparable trajectory in solar energy adoption. The correlation factor⁸ between Germany and its neighboring countries regarding solar energy is notably high, signifying that instances of solar surplus in Germany often align with similar situations in neighboring nations.

2. Storage

The emergence of large-scale energy storage solutions presents a promising means to store excess energy, and notably, the cost of batteries is steadily decreasing. Nevertheless, while batteries are a valuable addition to the energy system, it's important not to overstate their impact. Indeed, batteries may not produce significant value above 0 €/MWh for negative or low residual load, as they necessitate a substantial price spread to be economically viable. Currently, large-scale batteries are primarily deployed for power reserve rather than energy arbitrage, further emphasizing their specific role within the energy ecosystem.

3. Consumer behavior

The load component plays a pivotal role in this model, and it's worth considering the potential for consumers to shift their consumption patterns. While this prospect is indeed real, it's essential not to overstate its scope, as several significant barriers exist. These barriers include the inflexibility of certain consumption practices, the lack of compelling incentives⁹, and the absence of suitable technologies, among others. Moreover, in our projections, we have already displayed optimism regarding demand growth, anticipating a one-third increase within a mere eight-year span.

4. New load - hydrogen

The hours with negative residual load could also be used by electrolyzers. Similarly, to energy storage, these electrolyzers might not produce a much higher market price as they would be willing to purchase the energy at very low prices. In addition, it has to be seen how much electrolyzer capacity there would be in 2030.

In a nutshell

Our analysis for 2030 in Germany was based on calculating the residual load, a result of straightforward projections involving wind and solar generation along with the load. Subsequently, we introduced two distinct formulas to establish a connection between residual demand and market prices.

The first formula, which exhibits a linear correlation, leans towards a more unfavorable stance for renewables, potentially providing a lower-bound scenario. On the other hand, the second formula, with its more favorable outcome for renewables even under low residual load conditions, could be considered an upper-bound estimate. In practice, the actual scenario may likely fall somewhere in between these two extremes, and as the model shows, we should expect the capture value of solar to decrease quite substantially by 2030.

1. Not the retail prices but the prices on the day-ahead market, or wholesale market.

2. According to https://transparency.entsoe.eu/.

3. We anticipate the non-fulfillment of the targets for wind as a result of the recent difficulties of the wind industry.

4. There are 8760 hours per year.

5. For corporate self-consumers, the situation might be slightly different as consuming local generation can also diminish transmission and distribution costs.

6. Of course, it is not intrinsically negative as consumers would enjoy cheaper electricity.

7. Close to the current future prices for German baseload in 2024 and 2025.

8. See the correlation table in this post.

9. See this post for more on that matter.