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Article

Optimizing Feed-In Tariffs to Boost Renewable Energy Production

Energy

Feed-in tariffs (FITs) are crucial tools to increase the adoption of renewable energy technologies. But setting them at the right level (price) is a balancing act. If they are poorly designed, they can backfire, stunting the industry and wasting public money. A duo of HEC researchers, along with a colleague from the University of Texas at Austin, have shown that, to set optimal FIT levels, regulators must take into account the behaviours all players affected, including technology manufacturers.

House on a hill with renewable energy - ALDECAstudio

In a world facing climate change, renewable energy sources offer clean alternatives to fossil fuels. As incentives to invest in renewable energy technologies, feed-in tariffs (FITs) have been widely adopted across the globe. FITs are support schemes offering customers long-term contracts for generating renewable electricity, whereby the government guarantees the purchase of renewable electricity that is fed into the grid at a particular price, or tariff, and typically for a guaranteed number of years. 

Feed-in tariffs are support schemes offering customers long-term contracts for generating renewable electricity.

FITs aim to drive down the cost of electricity, support innovation and allow for swift penetration of renewable technology. They have played an important role in the growth of the solar photovoltaic (PV) industry. Yet, FITs have not always been successful. When inappropriately designed, FITS have been swiftly terminated which in some cases has led to extreme stunting of some national PV industries. 

The success of a FIT lies in the level or price it is set at, and how this evolves over time - as the renewable technology innovates and develops.

The success of a feed-in tariff lies in the level or price it is set at.

On one hand, high FITs are good because they help kick start renewables penetration. On the other, a FIT program is only successful if it can be terminated without any risk for the renewable energy industry, i.e. when the industry is mature to survive without the FIT. Therefore, the pace at which FITs are decreased is key. To get this balance right, what do policy makers need to consider when they set a FIT? 

Why Feed-In Tariffs?

With a FIT, PV panel owners sell the excess energy they produce back to the grid. The FIT determines how much the grid operator pays for the unit of PV electricity. At least initially, this is set higher than the wholesale price of non-renewable energy as, when you take into account the investment required to develop and produce PV panels, PV electricity is more expensive than fossil fuels. So, the grid pays a premium for the renewable energy, but this is expected to reduce over time as the technology improves and penetrates the market further. Eventually, the FIT will become unnecessary, as the PV technology is competitive and widespread, as it now is in many markets.

Eventually, the feed-in tariffs will become unnecessary, as the photovoltaic technology is competitive and widespread, as it now is in many markets.

The key role of renewable manufacturers

Determining the FIT level and how much it should evolve over time is not straightforward and has led to issues in some countries. We realised that, when setting FITs, policy makers only look at the owners of the panels and the grid operators. They may sometimes neglect the important role of the PV manufacturer – and this may cause the FIT scheme to be less effective than originally planned.

 

renewable energy manufacturer - rh2010-AdobeStock
"Policy makers may sometimes neglect the important role of the PV manufacturer." (Photo Credit ©rh2010-AdobeStock)

For example, in Spain, a very generous FIT package hoped to achieve fast and extensive market penetration of PV panels and drive down the cost of PV electricity. It paid customers a lot for the electricity their panels produced, aiming to get more people to buy the panels. However, this ended with the panel manufacturers profiting, a lack of competition, unsustainable government expenditure and a retraction of FITs that eventually killed the Spanish PV industry. Why was this FIT so ineffectual?

Introducing game theory

To find the answer and help policy makers set effective FITs, we created a new, three-player model. This includes the PV owner (i.e. the agent purchasing PV panels to generate electricity), the grid operator and the PV manufacturer. The model can be used to find the best level to set a FIT at, and it determines how this level should evolve over time. It also looks at how a FIT might be affected by the number of competitors in the PV market. It is based on game theory and considers the complex interplay of the decisions of these three players. 

Our three-player model can be used to find the best level to set a feed-in tariff at.

Each player in the model can make different decisions. For example, the regulator sets FIT levels, customers decide whether to invest in a PV system, whereas the PV manufacturer decides the sales price per solar panel. The demand for PV panels affects the manufacturer, and the quantity of electricity then fed back into the grid affects the grid operator. The grid operator must always meet the overall electricity demand and also buy back all PV electricity at the price set by the regulator.

A competitive market is key for FIT success

Using our model, it becomes clear that there is a complex interplay between regulators, PV customers and PV owners. The role of PV manufacturers affects the impact of a FIT scheme, because the price PV manufacturers set for PV panels is instrumental to the effectiveness of a FIT policy. In turn, the level of a FIT can determine the price of a PV panel set by a manufacturer. 
With this in mind, we see that, if a FIT is too high, with governments offering to pay a high price for PV electricity, manufactures tend to charge a lot for their panels. High FIT levels may lead to augmentation of price by manufacturers which reduces the effectiveness of the FIT in promoting PM investment. However, if it is too low, with governments not offering to pay much for PV electricity, there will not be enough cash for manufacturers to invest properly in R&D and innovation. In both cases, the FIT will not achieve what it hoped to, and the uptake of renewables will be stunted. 

This effect is more pronounced in monopolistic markets (i.e. when there is only one PV manufacturer). Therefore, understanding the competitiveness level of the PV market is also key to determining the correct FIT level. In a monopoly, where a FIT is set high, the monopolistic PV manufacturer will have more leverage in increasing PV prices. So the PV manufacturer will make larger profits, but the government doesn’t get the benefits it hoped for. This effect is reduced in a competitive market. Here, PV technology innovation increases and so does uptake and use of PV panels.

Policy-makers need to consider the manufacturers 

Overall, it is clear that policy-makers need to consider the decisions of all players in the market.

Until now, technology manufacturers have been neglected in FIT calculations. To help ensure the money put into FITs isn’t turned into pure profit for the manufacturers but instead goes towards improving tech and reducing the price of renewable electricity, policy-makers need to ensure FITs are designed correctly. Due to the complex interplay of all the decision-makers, small diversions in behaviour can lead to counterintuitive effects. Our game theory model looks at all the decision makers, including technology manufacturers, and can help policy makers set optimal FIT levels. 

Cover Photo Credit: ©ALDECAstudio on AdobeStock

Methodology

Focus - Methodologie
We designed a game theoretic model that considers the strategic interactions and decisions between the three key players: the grid operator, the customer and the technology manufacturer. Then we examined how changes in various factors, from the price and amount of PVs on the market to retail prices and market structure - monopoly or oligopoly - in order to see how these affect the optimal choice of FIT, from each player's perspective. By looking at the interplay of the players decisions, together with some external factors, we can assess what impact this may have on the success of a FIT.

Applications

Focus - Application pour les marques
Our model can be used by policy makers to make better decisions when it comes to FITs. These policy makers must take into account the technology manufacturers and the level of competition in the renewable energies market. This will help them set FITs at a level that helps promote renewable technology uptake. Our results also provide yet another argument for allowing competitive technology market: it gives policy makers better leverage for implementing FIT policies. The model also allows tech manufacturers to decide on an optimal pricing strategy in relation to the FIT proposed. This is because the price of PV panels has an impact on the price of electricity and the competitiveness of the product. Although FITs are most commonly associated with PV technology, our model can be applied to other renewable sectors where FITs are in use. Find more about our model in our paper.
Based on an interview with Sam Aflaki and Andrea Masini (HEC Paris) and on their article, "Optimal Feed-In Tariff Policies: The Impact of Market Structure and Technology Characteristics," co-written with Shadi Goodarzi (University of Texas), in Production and Operations Management, vol. 28, No 5, May 2019.

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