1. Introduction

1.1. Introduction

2. Economic Dispatch with Storage in a 1-bus grid

2.1. Introduction

2.2. Defining the input data in Python / Pyomo

2.3. We define the model

2.4. Mathematical Formulation

2.5. Defining the decision variables

2.6. Defining the objective and constraints in Python

2.7. Solving the model and making plots in Python

2.8. Modelling and solving in GAMS

2.9. How to do debugging in GAMS

2b. Economic Dispatch with Storage and CO2

2b.1. Solving the model in Python with Storage and CO2

2b.2. Convexity of the objective function and the CO2 constraint

2b.3. Modelling and solving in GAMS: With Storage and CO2

2b.4. Modelling in Pyomo: Without Storage, with CO2. 2b.5. Modelling in GAMS: Without Storage, with CO2.

2c. Economic Dispatch with Storage, wind and CO2

2c.1. Modelling in Python: With storage, wind and CO2

2c.2. Modelling in Python: No Storage, with wind & CO2.

2c.3. Modelling in GAMS.

2d. Conclusions & Code

2d.1. GAMS: Sending the results to Excel

2d.2. Conclusions.

3a. Economic Dispatch with Storage in a 24-bus grid

3a.1. Introduction and formulation

3a.2. What is a topology of a power system

3a.3. What is a reliability test system

3a.4. What is the per-unit system

3a.5. Modelling in Python

3a.6. Modelling in Python: Defining the constants

3a.7. Defining more constants

3a.8. Defining the decision variables

3a.9. Defining the constraints

3a.10. Optimal solution

3a.11. Solving in GAMS

3b. Solving without Storage

3b.1. Python modelling

4. Conclusions

4.1. Conclusions