Optimization-based Methods

General Approach

The general approach to implementing optimization-based controllers involves:

1. System modeling: Defining the mathematical representation of the energy system

2. Problem formulation: Specifying the objective function and constraints

3. Solver selection: Choosing an appropriate optimization solver

4. Solution implementation: Applying the optimal control actions to the system

5. Receding horizon implementation: Re-solving the problem at each time step with updated information

Documentation Structure

This section is organized as follows:

• Mathematical Formulations
  • Introduction
  • Mathematical Formulation Structure
  • General Problem Structure
  • Key Concepts
• Implementations
  • Introduction
  • Available Implementations
• Building Your Own Optimization-Based Controller
  • Introduction
  • Prerequisites
  • General Steps
  • Extension Points
  • Best Practices

The Mathematical Formulation section focuses on the general understanding of the objective function and component models, independent of specific implementation details.

The Implementation section provides concrete implementations using different frameworks (Linopy and PyOptInterface).

The Build Your Own section provides instructions on how to extend or customize the optimization-based controllers for specific needs.