Integrated GIS and Multi-Criteria Decision Analysis Optimizes Renewable Energy Site Selection

Category: Resource Management · Effect: Strong effect · Year: 2023

Combining Geographic Information Systems (GIS) with multi-criteria decision analysis (MCDA) methods like SWARA and DEMATEL can systematically identify optimal locations for large-scale renewable energy installations.

Design Takeaway

When selecting sites for renewable energy projects, employ integrated spatial analysis tools and multi-criteria decision-making frameworks to systematically evaluate and prioritize locations based on a comprehensive set of criteria.

Why It Matters

Effective site selection is critical for maximizing the efficiency and economic viability of renewable energy projects. This approach provides a robust framework for designers and engineers to balance complex environmental, technical, and economic factors, reducing risks and accelerating deployment.

Key Finding

The study successfully identified large, suitable zones for solar, wind, and hybrid renewable energy systems in the Kasserine region, demonstrating the effectiveness of the integrated analytical approach.

Key Findings

Research Evidence

Aim: To develop and apply an integrated spatial analysis model for identifying the most suitable sites for large-scale solar photovoltaic and wind energy systems.

Method: Integrated MCDA and GIS spatial analysis

Procedure: A literature survey was conducted to establish suitability criteria and constraints. The SWARA method was used to assign weights to these criteria, and the DEMATEL method was employed to understand the interdependencies between them. These weighted criteria were then integrated within a GIS environment using a raster calculator to generate suitability maps for solar, wind, and hybrid systems.

Context: Renewable energy site selection in Kasserine, Tunisia

Design Principle

Integrate spatial data analysis with multi-criteria decision-making to systematically optimize site selection for complex infrastructure projects.

How to Apply

Utilize GIS software and MCDA techniques to map and analyze potential sites for renewable energy projects, considering factors such as solar irradiance, wind speed, land availability, grid proximity, and environmental impact.

Limitations

The suitability is dependent on the specific criteria and weights chosen, and may not account for all localized micro-environmental factors or future land-use changes.

Student Guide (IB Design Technology)

Simple Explanation: Using computer maps and a structured way to weigh different factors helps find the best places for solar panels and wind turbines.

Why This Matters: This research shows how to use technology and smart analysis to make important decisions about where to build renewable energy sources, which is key for sustainable design projects.

Critical Thinking: How might the weighting of criteria in the SWARA method be influenced by political or economic pressures, and how could this bias the final site selection?

IA-Ready Paragraph: The integrated approach of using Geographic Information Systems (GIS) with multi-criteria decision analysis (MCDA) methods, such as SWARA and DEMATEL, provides a robust framework for systematically identifying optimal sites for renewable energy installations. This methodology allows for the quantitative assessment and balancing of various factors, leading to data-driven decisions that can significantly enhance project efficiency and reduce associated risks, as demonstrated in the Kasserine region case study.

Project Tips

How to Use in IA

Examiner Tips

Independent Variable: Suitability criteria (e.g., solar irradiance, wind speed, slope, distance to grid)

Dependent Variable: Site suitability index/map

Controlled Variables: GIS software version, specific MCDA algorithms used, data resolution

Strengths

Critical Questions

Extended Essay Application

Source

Unlocking renewable energy potential: A case study of solar and wind site selection in the Kasserine region, central‐western Tunisia · Energy Science & Engineering · 2023 · 10.1002/ese3.1650