A mathematical programming formulation for long-term infrastructure investment planning in Small Island Developing...

Area of Science:

• Electrical Engineering
• Operations Research
• Energy Systems

Background:

• Mixed-integer programming (MIP) is crucial for electricity infrastructure optimization but faces computational challenges with large-scale networks.
• Long run times and the trade-off between network realism and tractability limit practical applications, especially in Small Island Developing States (SIDS).
• Limited availability of real-world data and applications hinders robust infrastructure planning in SIDS.

Purpose of the Study:

• To develop a customized mathematical formulation for co-optimizing generation and transmission infrastructure investments.
• To address computational limitations in MIP models for long-term energy planning.
• To provide a reproducible framework using data from Jamaica.

Main Methods:

• A customized mixed-integer programming (MIP) model was developed for long-term generation and transmission infrastructure investment planning.
• Key customizations include representative hour categorization, biennial construction simulations, and distinct variable treatments for fossil fuel (discrete) and renewable energy (continuous) plants.
• The model was applied to data from Jamaica, with program scripts available for reproduction.

Main Results:

• The customized MIP formulation enhances computational tractability for complex energy infrastructure planning.
• The model effectively co-optimizes generation and transmission investments, balancing network representation with computational feasibility.
• The approach provides a practical and reproducible method for energy infrastructure planning in data-scarce regions like SIDS.

Conclusions:

• The developed customized MIP model offers a viable solution for optimizing electricity infrastructure investments in SIDS.
• The methodology successfully balances computational efficiency with the need for realistic network representation.
• The study provides a valuable, reproducible tool for energy planning, particularly for island nations.