Abstract
In an electricity market, a feed-in tariff promotes attainment of a so-called “green quota” through a system of subsidies designed to ensure renewable energy investors a “normal rate-of-return”. However, the subsidies should track technological advances closely with the expectation that they will be phased out when the renewable technology reaches an appropriate “maturity threshold” (i.e., grid parity). Grid parity is typically defined as the point where the levelized cost of electricity equals the price of purchasing electricity from the grid. However, it has been recognized that this definition of grid parity is flawed due to the intermittent nature of many renewable resources. We propose a definition which allows us to distinguish between grid parity and least-cost grid parity. We demonstrate that under a green quota and an emissions cap, welfare may be higher if the policy maker forgoes least-cost grid parity and phases out the feed-in system sooner rather than later. We show that while green producer cost reduction incentives under the feed-in tariff are perverse, they can be restored by offering a “menu” of values of the policy variables and allowing full discretion in terms of the decision to engage in cost-padding, pure waste, etc.
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Notes
As noted by Meneguzzo et al. (2015), it is significant that in some cases large-scale energy storage is becoming technically and economically feasible. For example, in the case of solar photovoltaics (PV), the cost of lithium-ion battery packs fell by 8% annually between 2007 and 2014 reaching a low of $300 per kWh for packs employed by leading electric vehicle producers.
A sectoral cost function may be defined as follows. Suppose the sector consists of n-producers with cost functions c i (y i ) with \( {c}_i^{\prime }>0,{c}_i^{\prime \prime }>0 \). Then the sectoral cost function is \( C(y)\equiv \min \left\{{\sum}_1^n{c}_i\left({y}_i\right)\left|{\sum}_1^n{y}_i=y\right.\right\} \).
We ignore uranium-based nuclear energy due to its potential for highly uncertain environmental externalities.
Alternatively, the price of electricity could be a regulated price sufficient to ensure RE developers a “normal” rate of return. As an example, the Public Utility Regulatory Policies Act of 1978 requires utilities to purchase electricity from “qualifying facilities” (e.g., small RE producers) at rates equal to the utilities’ avoided cost.
Strictly speaking, the backup technology could involve GHG emissions as well. For simplicity, we ignore this possibility.
RE investors may be reluctant to make investments if future market conditions are highly uncertain. The profit guarantee mitigates against this uncertainty.
For some assessments of minimum attainable cost in solar PV, see International Renewable Energy Agency (2012).
There may be no solution as well, but we ignore this possibility and assume that the policy maker has chosen to support a RE project for which grid parity is attainable.
Obviously, there may be political and/or institutional constraints on the values of the green quota and the emissions constraint.
This is consistent with the current practice of setting various intermediate RE targets along the way to grid parity (Mendonça et al. 2009).
It has in fact been argued that the pursuit of incentives can become the principal entrepreneurial activity, rather than improving efficiency. See Schmitz et al. 2013 for an excellent discussion of rent-seeking in RE and Bergek and Jacobsson (2010) for an analysis of rent generation in the Swedish ‘green certificate’ system.
Here, ∇f denotes the gradient of f, the vector of partial derivatives of f.
Simon and Blume (1994), Theorem 21.19, page 530.
In our model, the cost function may be interpreted as the cost of producing x units of output with certainty. A more general analysis could explicitly distinguish between the components of cost that reflect knowledge/experience in RE generation and those that reflect storage costs. For an example, see Schneider et al. (2015) for an inventory modeling approach to energy storage.
This is another case of green promotes the dirtiest (Böhringer and Rosendahl 2010). It is a consequence of the green regulation itself. After the green quota is eliminated and the FIT phased out, cost reductions by green producers reduce dirty producers profit as expected.
Note that since ∇π x > > 0, ceteris paribus increases in α, c and E will increase green profit. However, this does not hold globally.
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Acknowledgments
The authors wish to thank Donna Anderson and the participants in the “Ecosystems, Electricity and Sustainability” session at the International Atlantic Economic Conference in Montréal, Canada, October 5-8, 2017, for insightful discussion. We are also deeply indebted to an anonymous referee for a number of extremely useful comments and suggestions on an earlier version of this manuscript.
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Currier, K.M., Rassouli-Currier, S. Grid Parity and Cost Reduction Incentives for “Green Producers” in Electricity Markets. Int Adv Econ Res 24, 65–78 (2018). https://doi.org/10.1007/s11294-018-9667-y
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DOI: https://doi.org/10.1007/s11294-018-9667-y