Specifying An Efficient Renewable Energy Feed-in Tariff

Abstract

This paper derives efficient pricing formulae for renewable energy Feed-in Tariff (FiT) designs that incorporate exposure to uncertain market prices by using option pricing theory. Such FiT designs are presented as a means to delineate market price risk amongst investors and policymakers when designing renewable energy support schemes. Sequential game theory provides the theoretical framework through which we model the strategic interaction of policymakers and investors during policy formulation. This model is solved using option pricing theory when a FiT is comprised of market prices combined with a guaranteed element. This solution also allows for an analytical formulation of the policy cost of subsidisation. Partial derivatives characterise sensitivity of policy cost and investor remuneration to deviations in market conditions beyond those expected. Analytical derivations provide a set of tools which may guide more efficient FiT policy and investment decisions. Numerical simulations demonstrate application for a stylised Irish case study, with a scenario analysis providing further insight into the relative sensitivity of policy cost and investor remuneration under different market conditions.

An auction framework to integrate dynamic transmission expansion planning and pay-as-bid wind connection auctions

“…Table 4 displays cost and bid parameters values for each site while Table 5 shows how internal generation costs vary depending on which node/bus they are associated with 7 . The generation cost parameters follow those from Doherty and O'Malley (2011) and Farrell et al (2013). For a more detailed discussion on the levels for the parameters associated with the probaility of acceptance (λ, β and n) see Farrell and Devine (2015).…”

Optimising feed-in tariff design through efficient risk allocation

“…Although they suggest that the current Irish FiT over-remunerates investors, they do not compare FiT choice amongst efficiently specified options, nor do they consider consumer and investor attitidues to market price risk. Farrell et al (2017) provide a model with which different FiT regimes may be efficiently defined using option pricing theory. For each design, cost and remuneration are equal in expectation.…”

“…Precisely identifying the most efficient point in this trade-off has not been carried out by the literature to date. Farrell et al (2017) discuss the concept of risk-sharing when choosing between designs using a bi-level model similar to that considered in this work. In particular, they discuss the Valueat-Risk (VaR) associated with different policies ex-post any FiT level decisions made.…”

“…The market price received by the renewable investor varies by jurisdiction. For the purpose of this analysis, we choose an Irish case study and thus consider annual Volume Weighted Average Prices (VWAP) (Farrell et al, 2017). This is the annual average electricity price weighted by the volume of electricity generated through renewable sources and is used in certain jurisdictions such as Ireland to calculate wind remuneration (Doherty and O'Malley, 2011;Farrell et al, 2017).…”

“…Often, a policymaker incurs this aggregate risk in the first instance, which is then transferred to electricity consumers through additional charges on consumption (Farrell and Lyons, 2015;Gross et al, 2010). Different FiT designs apportion this risk in different ways (Couture and Gagnon, 2010;Kim and Lee, 2012), with zero, partial or full transfer of market price risk possible (Farrell et al, 2017). Although the literature has acknowledged that appropriate risk transfer is central to successful renewables policy (Klessmann et al, 2013), the optimal division of risk has not been analysed.…”