2023
Electricity as an Energy Carrier
Name: Electricity as an Energy Carrier
Code: EME10369M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Electrotechnical Engineering
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
- The student should acquire / consolidate their knowledge in relation to Electrical Energy Systems, particularly in the areas of Production, transformation and Transportation.
It should also acquire knowledge in order to be able to use load charts and calculate power transits.
It is intended that the student identify the various problems associated with the quality of electricity.
- The student should acquire / consolidate knowledge in the area of intelligent systems for control and supervision. In this context the student will study tools for acquisition and processing of electrical signals (virtual instrumentation - LabView) as well as tools for Supervisory Control (SCADA - Supervisory Control and Data Acquisition).
These tools will allow the student for future interaction with advanced control systems (eg solar concentration), SCADA supervision of industrial processes (eg biomass) and intelligent control of power flows (eg smart grids - energy efficiency).
It should also acquire knowledge in order to be able to use load charts and calculate power transits.
It is intended that the student identify the various problems associated with the quality of electricity.
- The student should acquire / consolidate knowledge in the area of intelligent systems for control and supervision. In this context the student will study tools for acquisition and processing of electrical signals (virtual instrumentation - LabView) as well as tools for Supervisory Control (SCADA - Supervisory Control and Data Acquisition).
These tools will allow the student for future interaction with advanced control systems (eg solar concentration), SCADA supervision of industrial processes (eg biomass) and intelligent control of power flows (eg smart grids - energy efficiency).
Contents
1. Introduction
- Evolution of the power systems. Fuels. Electric power plants.
2. Mathematical programming problem
- Utility and basic definitions. Identification of the great. Karush-Kuhn-Tucker theorem. Lagrandeana relaxation. Dynamic programming.
3. Electricity market
- Market for electric energy. Equilibrium market. Environmental and economic dispatch. Solution without considering line losses.
4. Short-term planning for hydric groups
- Problem Formulation. Solution considering fixed fall.
5. Short-term planning for thermal groups
- Characterization of thermal groups. Solution using Lagrangian relaxation. Solution using dynamic programming
6. Short term hydrothermal coordination
- Problem formulation. Cases study using the Karush Kuhn Tucker theorem. Decomposition and coordination.
- Evolution of the power systems. Fuels. Electric power plants.
2. Mathematical programming problem
- Utility and basic definitions. Identification of the great. Karush-Kuhn-Tucker theorem. Lagrandeana relaxation. Dynamic programming.
3. Electricity market
- Market for electric energy. Equilibrium market. Environmental and economic dispatch. Solution without considering line losses.
4. Short-term planning for hydric groups
- Problem Formulation. Solution considering fixed fall.
5. Short-term planning for thermal groups
- Characterization of thermal groups. Solution using Lagrangian relaxation. Solution using dynamic programming
6. Short term hydrothermal coordination
- Problem formulation. Cases study using the Karush Kuhn Tucker theorem. Decomposition and coordination.
Teaching Methods
- Lectures
- Laboratory classes
The teaching method is based on theoretical classes and practical classes. An active learning system is focused to stimulate the student to make his own research on the matters presented in the classes.
During the classes four computational/ experimental works (at least) are given to the student, to work in group, in order to gain experience with industrial technology.
Assessment methods and criteria:
The grades are within the interval [0,20].
The assessment method consists of two components (TP and Ex):
- [TP] Laboratory work - (30%)
- [Ex] Examination or Final Project ? (70%)
[NF] Final Grade: NF = TP×0.30 + Ex ×0.70
If NF> 9.5 ^ TP> 9.5 ^ Ex> 9.5: Approved
- Laboratory classes
The teaching method is based on theoretical classes and practical classes. An active learning system is focused to stimulate the student to make his own research on the matters presented in the classes.
During the classes four computational/ experimental works (at least) are given to the student, to work in group, in order to gain experience with industrial technology.
Assessment methods and criteria:
The grades are within the interval [0,20].
The assessment method consists of two components (TP and Ex):
- [TP] Laboratory work - (30%)
- [Ex] Examination or Final Project ? (70%)
[NF] Final Grade: NF = TP×0.30 + Ex ×0.70
If NF> 9.5 ^ TP> 9.5 ^ Ex> 9.5: Approved
Teaching Staff
- Mário Rui Melício da Conceição [responsible]
