An international research group has conducted a comprehensive analysis of the bidding strategies that are adopted by bidders in renewable energy auctions based on the constructed preemption game model, which combines game theory with “real options theory.”
While game theory is concerned with analyzing strategic interactions among rational decision-makers, real options theory deals with evaluating investment decisions in uncertain or dynamic environments.
“There are two reasons why combining game theory with real options theory for modeling,” the researchers said. “Firstly, the auction decision is an investment decision. The real options theory is an important theory for investment decisions. Secondly, investors need to consider the behavior of potential competitors in their auction decision-making. Thus, adopting game theory to guide auction decision-making is also necessary.”
In preemption games, players decide a time to stop and trade off the strategic costs derived from outlasting other players and the gains offered by the passage of time.
“Under the preemption competition, the investor loses all gains if competitors seize the opportunity,” the scientists said. “To avoid losing out to competitors and gain as much investment income as possible, the investor chooses to invest at a smaller investment income than they would have if there are no competitors.”
The academics examined two types of subsidy auctions – one based on production quantity and required subsidy rates, and another with a fixed subsidy amount, with participants competing to provide the best terms. They found that higher subsidy levels in the auctions result in lower final prices.
The two auction forms were modeled under three scenarios. In the first, the bidder has no competitors; in the second, they do have competitors, but they lack information about their investment income; and in the third, they lack information about the competitors' investment costs. The modeling was based on cost, interest rate, and the variability of investment costs, among other parameters.
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“It can be found that when there are no competitors, as the investment cost increases, the investor will necessarily choose to invest when they can obtain greater investment income,” the academics said about the first case. “As the safe interest rate increases, the investor likewise chooses to invest at greater investment income. Furthermore, with the same investment cost, as the safe interest rate increases, the investor tends to invest when they can obtain greater investment income.”
For the second and third scenarios, the researchers said that the overall trend of triggering investment is similar to the no-competition scenario.
“This indicates that when the investor does not have access to information on competitors' investment income or investment cost, it can refer to the bidding strategy of the absence of competitors to guide decisions,” they explained.
The researchers also concluded that in the fixed-subsidy auction, the annual power production after the project investment has the most effect on bidding strategies. That is due to the additional steps that have to be done in this strategy to find the investment trigger point.
“The investor can refer to the investment trigger point under the volume-based subsidy form for initial decision-making. Then, by estimating the annual power production after the investment and combining it with the subsidy level under the fixed amount subsidy form, the approximate subsidy level per unit of power generation can be obtained,” the researcher said. “Then, according to the relationship between the subsidy level per unit of power generation under two subsidy forms, a specific bidding decision can be made.”
In both auction formats, the researchers said that higher government subsidies led to lower investor bidding prices and increased investor participation. They presented their findings in “The bidding strategy for renewable energy auctions under government subsidies,” which was recently published in Renewable Energy. The group includes academics from the Shandong University of Finance and Economics and Tongji University in China, as well as from the Technical University of Denmark.
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