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Assessing PV and wind roadmaps: Learning rates, risk, and social discounting

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  • Mauleón, Ignacio

Abstract

Methods to assess global renewable energy investment plans are presented and applied to photovoltaic and wind energy roadmaps recently published by international organizations. Price learning rate effects, uncertainty and derived risk, social discounting, investment depreciation, cost of capital and other factors are dealt with in detail. Some significant empirical results are: a) the roadmaps are market competitive globally, and also economically efficient from an environmental point of view; b) the volume of funds required is significant, but the investments can be financed with moderate carbon taxes; c) more expansive roadmaps yield enhanced results regarding both competitiveness and environmental efficiency; d) risks derived from the uncertainty in estimated Learning Rates may be significant and measures to control them are presented.

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  • Mauleón, Ignacio, 2019. "Assessing PV and wind roadmaps: Learning rates, risk, and social discounting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 71-89.
    • Handle: RePEc:eee:rensus:v:100:y:2019:i:c:p:71-89
    DOI: 10.1016/j.rser.2018.10.012
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    4. Ignacio Mauleón, 2020. "Economic Issues in Deep Low-Carbon Energy Systems," Energies, MDPI, vol. 13(16), pages 1-32, August.
    5. Ignacio Mauleón, 2019. "Assessment of Renewable Energy Deployment Roadmaps," Energies, MDPI, vol. 12(15), pages 1-15, July.
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    7. Olubayo M. Babatunde & Josiah L. Munda & Yskandar Hamam, 2020. "Exploring the Potentials of Artificial Neural Network Trained with Differential Evolution for Estimating Global Solar Radiation," Energies, MDPI, vol. 13(10), pages 1-18, May.
    8. Ignacio Mauleón, 2021. "Aggregated World Energy Demand Projections: Statistical Assessment," Energies, MDPI, vol. 14(15), pages 1-13, July.

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