Abstract
This theory-building research intends to dig into the renewable energy industry and drawing from research on learning curves and energy polices, proposes a way to speed-up the energy shift from our fossil-fuel dependency to a green economy. Even though standard economic frameworks suggest that markets and not policy makers should decide winners and losers, we urge to accelerate renewable energy competitiveness, proposing that by limiting the number of maturing renewable technologies where resources are allocated to at government level, we reduce the time within which renewables will achieve technological price parity with fossil fuels. In turn, by analysing the energy demand and supply curves, the study suggests that this action will also mediate the relation between quantity and price, shifting only the supply curve, leaving the demand curve unaffected. It continues by proposing the standardization of a unique renewable energy supply chain model, defined as the SURESC model, relating the indirect effect of limiting the number of maturing technologies to allocate resources, to achieve renewable price-parity with conventional energy sources faster. This is a preliminary theoretical study intended to provide a holistic approach to a known problem.
Highlights
This theory-building research intends to dig into the renewable energy industry and drawing from research on learning curves and energy polices, proposes a way to speed-up the energy shift from our fossil-fuel dependency to a green economy
Let’s demonstrate this claim: Following Shayegh et al.[38] research, we find that investing in research and development (R&D) will diminish initial investment costs Ltot and will push our learning curve down
It’s important to underline the fact that there is no perfect solution to the energy transition, that any technology used will have its pros and cons, breakthroughs may come from excluded ones, and that economic frameworks strongly suggest a diversified portfolio of technologies to increase success rates
Summary
Learning curves play an important role to understand maturing industries such as renewables, as the sizes of the investment needed for a certain renewable technology to reach technological price parity (leaning investment) with fossil fuels may define the time to achieve this goal[38]. Where Ctot > 0, Ltot1 > 0 and n > 0 This function represents the total amount of learning investment required for a set of renewable energy technologies to reach fossil fuels price parity. We need to apply this find to demand and supply renewable energy curves and see how the market would react by increasing and decreasing the number of technologies n we allocate resources to.
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