Interface Between GAMS and MATLAB Software: Integration Methods and Applications

The interface between GAMS (General Algebraic Modeling System) and MATLAB proves highly valuable in power system programming by enabling users to leverage the complementary strengths of both platforms. GAMS excels in optimization modeling and solution, while MATLAB provides robust numerical computation and data visualization capabilities.

Key applications of this integration include: Data Exchange: Facilitates transfer of optimization model inputs and outputs between GAMS and MATLAB, such as power system load data, generator parameters, or optimal dispatch results. Implementation typically involves using MATLAB's data structures (arrays, tables) to format inputs and parse optimization outputs. Pre-processing and Post-processing: MATLAB can generate initial data required for GAMS optimization and perform visual analysis of results (e.g., plotting power flow distribution diagrams). Code implementation often uses MATLAB's plotting functions (plot, surf, contour) coupled with data transformation algorithms. Automated Workflows: Through script control, users can automatically execute GAMS optimization models and process results directly in MATLAB, enhancing research efficiency. This involves developing wrapper scripts that coordinate both software environments using system calls or API interfaces.

Common implementation approaches include: GDX File Exchange: GAMS stores data in GDX (GAMS Data Exchange) format, while MATLAB utilizes specialized toolboxes (like gdx2mat or rgdx) to read and write GDX files. The code implementation requires proper handling of GDX data structures and dimension mapping. API Calls: MATLAB can invoke GAMS APIs to execute models and directly retrieve optimization results. This method involves using GAMS' programming interfaces (GAMS Object-oriented API) with proper error handling and parameter passing mechanisms. Command-line Integration: Executing GAMS models through system commands within MATLAB and parsing output logs. Implementation requires text processing algorithms to extract relevant solution metrics and convergence information from GAMS listing files.

In power system applications, this interface particularly benefits optimization problems such as unit commitment, optimal power flow (OPF), and economic dispatch, where MATLAB's analytical capabilities complement GAMS' optimization solvers for comprehensive solution analysis.