Efficient Feed-In-Tariff Policies for Renewable Energy Technologies

Abstract

Feed-in-tariff (FIT) policies aim at driving down the cost of renewable energies by fostering learning and accelerating the diffusion of green technologies. Under FIT mechanisms, governments purchase green energy at tariffs that are set above market price. The success or failure of FIT policies, in turn, critically depend on how these tariffs are determined and adjusted over time. This paper provides insights and guidance into designing effective and cost-efficient FIT programs such as these. To that end, we propose a dynamic optimization modeling framework that captures the key network externalities contributing to the technology evolution path. We show in our framework that the investments' profitability guaranteed by the tariffs should either always increase or always decrease as time progresses. This is in contrast with the current practice of FIT-implementing jurisdictions which typically try to maintain the same level of profitability across the policy horizon. Further, we determine how the structure of the optimal policy (ascending vs. descending profitability) changes with technology and market characteristics as well as with the policy objectives. In particular, when the policy horizon is endogenous and the policy goal is a target on the technology cost reduction, our results reveal that the investors' profitability should increase (resp. decrease) over time for low (reps. high) values of learning rates or penetration speeds. We also demonstrate that the annual capacity installation should not always increase over time as existing FIT implementations sometime suggest.

The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption

“…The paper shows evidence that the current feed-in-tariff system used in Germany might not be efficiently using the positive network externalities of early adopters. Alizamir et al (2013) also tackle the feed-in-tariff design problem, comparing strategies for welfare maximization and adoptions targets.…”

“…For the most part, the subsidy design literature in green technologies has not studied demand uncertainty (see for example, Benthem et al (2008), Atasu et al (2009), Lobel and Perakis (2013) and Alizamir et al (2013)). In practice, demand uncertainty has also often been not considered.…”

What Do Capacity Deployment Rates Tell Us about the Efficiency of Electricity Generation from Renewable Energy Sources Support Measures in Greece?

“…For example, Germany's Renewable Energy Source Act is established based on an approximate 7% rate of return for well-operated installations [14]. The target profit margins in France are based on a profitability index (PI), defined as the ratio between a project's overall discounted payoffs and its total discounted cost [15]. This leads to a tariff structure that decreases over time, so as to reflect anticipated cost reductions.…”

Optimal Subsidy and Tax Policies for Green Product with Consumer Environmental Awareness

“…For example, the U.S. government passed the American Recovery and Reinvestment Act (ARRA) of 2009, which granted a tax credit to consumers who purchased electric vehicles [8]. FeedIn-Tariff is a policy instrument to attract investments in renewable energy by offering long-term guaranteed purchase agreements to green power producers to sell their electricity into the grid [2,12,15]. Gasoline taxes and carbon tax are added in the fuel price considering that greenhouse gas emissions from human activities in particular carbon dioxide (CO 2 ) are responsible for the current observed global warming [1].…”

“…For example, in 2012, Honda Fit EV model was quickly sold out in Southern California after offering sizable leasing discounts [11]. Feed-In-Tariffs attracts a wide range of manufacturers to invest in renewable energy (such as PV) [2]. Manufacturer will introduce green product based on the ordinary product line with stricter environmental emission standard, given the green product subsidy or ordinary tax set out by the government [7,18,20].…”