1. Introduction

1.1. Introduction to Unit Commitment

1.2. Who uses the Unit Commitment model

1.3. Differences between the Unit Commitment and Economic Dispatch models

1.4. The Day - Ahead Electricity Market Structure. Part 1 : Unit Commitment

1.5. The Day- Ahead Electricity Market Structure. Part 2 : Economic Dispatch

1.6. Why is the focus only on thermal power stations

1.7. Why is it necessary to have a Day-Ahead Electricity Market Structure

2. The Objective Function

2.1. The formulation of the objective function

2.2. The binary variables for modelling the status of the power stations

2.3. The startup and shutdown costs of thermal power stations

2.4. Fuel Costs: Linear and Nonlinear

2.5. Piecewise linear approximation of the fuel costs

2.6. Piecewise linear approximation of the equation

2.7. Piecewise linear approximation of the objective function

3. The Constraints

3.1. The total output of a power station

3.2. The ramping constraints

3.3. The power balance equation

3.4. Limits on the output of power stations

3.5. The Technoeconomics of thermal power stations

3.6. The description for minimum uptime/downtime constraints

3.7. The minimum downtime constraint at initial periods

3.8. The minimum uptime constraint at initial periods

3.9. The minimum uptime constraint through the day

3.10. The minimum downtime constraint through the day

3.11. The minimum uptime and downtime constraints for the last periods of the day

4. The Implementation

4.1. Python: Input parameters

4.2. Python: Linearization of Fuel Cost

4.3. Python: Constraints

4.4. Python: Objective Function and Solution

4.5. GAMS Implementation

5. The Implementation of the Price-Based version

5.1. Python and GAMS implementation

6. Conclusion

6.1. Overview