Optimization in Power System (3 ECTS)

Learning outcomes

Students will learn some optimization techniques that are applied to the power system operation. This course will focus on the photovoltaic (PV) generation and thermal power plants.
First, students will study the technique to maximize the power from the PV generation. This function is called “maximum power point tracking (MPPT)”. To know its electrical feature, Ohm’s law and the relationship between the voltage and the current on PV generation will be introduced. After that, the computational simulation for the PV output maximization using the hill climbing method will be implemented by Python.
Second, students will learn the application of mixed integer linear programming (MILP) to schedule the daily start/stop condition of the thermal generator. This problem is called “unit commitment (UC) problem” The objective of this problem is to minimize the total fuel cost of thermal power plants. Its equipment and the difference of cost with fuel cost, the equation for the relationship between the power and the fuel cost will be explained.

Content

Day 1
-The introduction of the photovoltaic generation. (Lecture)
-The optimal resistance will be decided by trial-and-error approach. (Lab work)

Day 2
-The explanation of hill climbing method. (Lecture)
-The implementation of the hill climbing method for maximization of PV generation output. (Lab work)

Day 3
-The introduction of the thermal power plant. (Lecture)

Day 4
-The fundamental programming of MILP for decision of combination of thermal power plants (unit commitment problem). (Lecture, Lab work)

Day 5
-The fundamental programing of MILP for the unit commitment problem. (Lecture, Lab work)

Prerequisites

-Experience in fundamental programing on C or Python.

Assessment methods and criteria

Active attendance at all laboratory sessions.
Completing practical exercises.

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

Students can understand the maximization of PV output and the cost minimization of thermal power plants.

Assessment criteria, good (3)

Students can make a computational program on the maximization of PV output and the cost minimization of thermal power plants.

Assessment criteria, excellent (5)

Students can improve the computational program on the maximization of PV output and the cost minimization of thermal power plants.

Assessment criteria, approved/failed

Students can understand the maximization of PV output and the cost minimization of thermal power plants.