Efficient design and optimal application of tax incentives to promote investments in renewable energy technologies

ABSTRACT : Governments are interested in maximizing the capacity of Renewable Energy Technologies (RET) to support the energy transition. They can attract investments in RET—like solar photovoltaic, onshore and offshore wind, green hydrogen, enhanced geothermal systems, Etc.—by enacting tax incentives granted to potential investors generally known as generation companies (GENCOs) that would invest in those projects motivated by the income tax reductions. The purpose of this research is focused on analyzing fiscal policies to promote RET. At the company level, we have analyzed the financial performance of GENCOs willing to invest in RET projects. Special attention has been paid to obtain optimal tax management decisions–of GENCOs owning not only a RET project but also a portfolio of energy projects—to minimize income taxes. To that, we have developed a tax optimization model that strategically manages depreciation, Tax Losses Carryforward (TLC), and Investment Tax Allowances (ITA) use. One of our key findings is that optimal tax-related decisions strongly depend on GENCOs’ revenues from electricity sales. When revenues are not significantly high, GENCOs need to be strategic and implement the optimal levels of annual depreciation, TLC, and ITA as the proposed model suggests in order to minimize its income tax. Moreover, we adapt the latter approach by including debt parameters like debt ratio and loan interest rates. A detailed case study was carefully constructed involving four (4) types of RET, twelve (12) realistic Colombian GENCOs—–that hypothetically are willing to invest in a RET project, and four (4) electricity price scenarios. Based on these results, we find that the longer the GENCOs take to implement ITA, the more necessary it will be to use a tax optimization model to determine the optimal debt ratios. The fact that tax incentives application may depend on the level of GENCOs revenues has strongly motivated the development of a tax optimization model under electricity price uncertainty. To that, an exact probability distribution model of Net Present Value (NPV) is constructed to assist RET investors in the decision-making process. Two investors’ perspectives were evaluated: a developer that only owns a solar project; and an existent Generation Company (GENCO) that owns a portfolio of projects. The likelihood that the GENCO ends up with a positive NPV is greater than the likelihood for the developer. That is why the ownership of additional projects enables the GENCO to take fully ITA in short periods. At the government level, a theoretical method was constructed to support the efficient design—from the government’s perspective—and the optimal application—from the GENCOs’ standpoint—of tax incentives that promote RET investments. The problem when considering both GENCOs and governments is much harder to engage given that the government objective is subject to the GENCOs optimization problems. In particular, our method is focused on designing optimal tax rates for a government that maximizes RET investments subject to a set of GENCOs that maximizes their net present values. That is why the government should learn more about optimal tax strategies (best responses) of GENCOs. In conclusion, under certain conditions, optimal tax rates were identified.

• Autores: Castillo Ramírez, Alejandro
• Tipo de recurso: Doctoral thesis
• Fecha de publicación: 2024
• Institución: Universidad de Antioquia
• Repositorio: Repositorio UdeA
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.udea.edu.co:10495/39217
• Acceso en línea: https://hdl.handle.net/10495/39217
• Palabra clave: Recursos energéticos renovables; Renewable energy sources; Análisis financiero; Financial analysis; Precios de la energía; Tax incentives; Incentivos tributarios; Optimization methods; Método de optimización; Renewable energy technologies; Tax optimization models; Financial performance analysis; Electricity price uncertainty; Optimal governmental tax rate; http://aims.fao.org/aos/agrovoc/c_5372
• Rights: embargoedAccess
• License: https://creativecommons.org/licenses/by-nc-sa/4.0/