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Investment Opportunities in Latin America: Suitability Maps for Solar and Wind Projects

Core Content

This document outlines the IRENA Global Atlas for Renewable Energy, which provides suitability maps for grid-connected and off-grid solar and wind projects in Latin America. These maps are part of a broader effort to support the energy transition by identifying areas with high potential for renewable energy development.

Main Viewpoints

• Renewable Energy Potential: Renewable energy is seen as a key component in reducing greenhouse gas emissions and meeting global energy demands, as highlighted by the Paris Agreement.
• IRENA's Role: IRENA aims to help world leaders increase the share of renewable energy to 36% of global total final energy consumption (TFEC) by 2030.
• Suitability Analysis: IRENA uses a new opportunity-based approach to evaluate renewable energy potential, which is more detailed and nuanced compared to traditional exclusion-based methods.
• Technical Potential Estimates: The document provides technical potential estimates for both grid-connected and off-grid systems across Latin America, using a 60% suitability threshold and a 75 km grid distance.
• Spatial Resolution and Data Sources: Datasets used have 1 km resolution for wind and 3 km resolution for solar, with the grid distance data sourced from Open Street Map and validated using Google Earth.

Key Information

Overview of Suitability Maps

• The maps are high-resolution and GIS-compatible, offering a pre-feasibility assessment of renewable energy opportunities across the continent.
• They are available for download from the IRENA Global Atlas at http://irena.masdar.ac.ae/?map=2012.
• The maps are color-coded to indicate suitability levels: yellow (60–70%), orange (70–80%), and red (>80%).

Technical Potential and Investment Estimates

• Table 1 provides total technical potential (GW) and equivalent investment (USD) for Latin America based on a 1% suitability threshold.

  • Wind, grid-connected: 238 GW, USD 537 billion
  • Wind, off-grid: 184 GW, USD 415 billion
  • Solar PV, grid-connected: 2,154 GW, USD 4,643 billion
  • Solar PV, off-grid: 2,685 GW, USD 5,789 billion
  • Total: 5,260 GW, USD 11,384 billion

• Conversion Methodology is described in Table 2, which includes the following steps:

  1. Sum of suitable surface area (above a given suitability threshold).
  2. Assume a minor share of suitable surface (1% for illustration).
  3. Assume an average installation density (Wind: 4 MW/km²; Solar: 30 MW/km²).
  4. Calculate technical potential using the formula:
     $ P = \text{Suitable surface} \times 1% \times \text{density} $
  5. Convert technical potential to equivalent investment using cost per MW:
     • Wind: USD 2,258/MW
     • Solar: USD 2,156/MW

Opportunity-Based Approach

• The opportunity-based approach is designed to identify ideal or adequate locations for renewable energy projects by ranking areas based on multiple suitability dimensions.
• These dimensions include:
  • Resource intensity (wind speed and solar irradiation)
  • Distance to power grids
  • Population density
  • Land cover
  • Topography and slope
  • Protected areas
• The methodology is replicable and transparent, using un-weighted pixel-to-pixel averages for combining data. Weighted averages could be applied for local analyses.

Spatial Resolution and Data Limitations

• Wind data has a 1 km resolution, while solar data has a 3 km resolution.
• Grid distance data is validated using Google Earth, but may be incomplete in some areas.
• Population density data comes from the LandScan 2014 Global Population Database, which may not capture sudden population movements.
• Land cover and topography data are based on SRTM and SWBD datasets, which have a resolution of 3 arcsec (up to 90 m at the equator).
• Protected areas are represented as polygons and are not weighted in the analysis.

Application and Use

• The suitability maps are intended for strategic planning and stakeholder engagement.
• They help identify promising areas for investment and initiate dialogues with local authorities and communities.
• The maps are iteratively updated as more data becomes available.

Conclusion

IRENA's suitability maps offer a comprehensive and replicable method for assessing renewable energy potential in Latin America. They are designed to guide investment decisions and policy planning by combining resource data with geospatial constraints. While the maps are high-resolution, their information content is limited by the spatial resolution of the underlying datasets. For local analyses, more detailed data and weighted averages may be necessary to improve precision and relevance.