RTI uses cookies to offer you the best experience online. By clicking “accept” on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI uses cookies and how to manage them please view our Privacy Policy here. You can “opt out” or change your mind by visiting: http://optout.aboutads.info/. Click “accept” to agree.

To combat climate change, countries around the world are introducing national renewable energy development plans and carbon neutrality goals to overhaul their energy sectors. High, middle, and low-income countries are all aiming to increase solar and wind generation and decrease dependence on coal. Yet the total costs of these ambitious multi-year plans are often difficult to predict, and their impacts on energy affordability and low-income households are not always known.

Different types of economic and engineering tools are used to help policymakers better understand the best course of action to meet these national goals. These include models that represent the entire economy down to those that characterize only the electric sector. Typically, these tools consider the physically-based and engineering relationships between decision options as well as the economic costs and benefits of the outcomes. For example, if a government or utility wants to understand whether to invest more in solar or wind technology, it might employ a decision-making tool that estimates how many kilowatt-hours of power can be obtained in a region given the availability of solar resources relative to wind resources. Next, the tool might assess how much each technology costs to deploy, which informs the utility whether solar or wind is best suited for their needs.

Despite how commonplace such models are, the tools used to guide policymaking are often not designed to consider difficult-to-quantify aspects such as equity and equality. Complex social questions like “will increasing renewable energy penetration increase electricity costs for low-income households” and “will building solar farms in an area impact the economic well-being of nearby communities” are not typically included in the decision-making process of these models. Nevertheless, they are important questions that have real impacts on people around the world.

An example of the need for climate justice from Guatemala

To better understand the real-world impact, we conducted a case study in Guatemala focused on how to incorporate equity considerations into traditional techno-economic modeling. This effort included integrating a levelized cost of electricity model with a socioeconomic household survey to estimate how a nationwide mandate on renewable generation might impact the affordability of electricity for the lowest income households.

Findings showed that without additional government subsidies, renewable energy mandates would most adversely impact already energy-poor households in Guatemala, due to the spatial distribution of solar and wind resources across the country. These results highlight how important it is for governments to pay close attention to lower income households when implementing and passing renewable energy mandates. Implementing assistance programs, like subsidies, in tandem with energy mandates could be one way to help underserved households and communities.

Energy equity and future planning

The need for ambitious renewable energy policies stems from the fact that electricity and heating sectors account for 25% of greenhouse gas emissions—a substantial amount. We must address emissions from these sectors if we want to mitigate climate change. As we work toward a more sustainable future, our climate solutions should include renewable energy solutions that will inherently incorporate energy poverty and equity to achieve climate justice.

Read the full publication, How will renewable energy development goals affect energy poverty in Guatemala, to learn more.

Disclaimer: This piece was written by Candise Henry (Senior Energy Specialist), Andrew "AJ" Kondash (Research Environmental Scientist), Justin Baker (Senior Economist), Christopher Wade (Research Economist), Benjamin Lord (Environmental engineer), George L. Van Houtven (Director, Ecosystem Services Research), Jennifer Hoponick Redmon (Senior Director, Environmental Health and Water Quality), Brooke Shaw, Edwin Castellanos, and Benjamin Leiva to share perspectives on a topic of interest. Expression of opinions within are those of the author or authors.