Description

Optimal decision-making is a must in energy system planning and operation as the non- optimal decisions may lead to high economic losses and/or technical issues. The course on “Advanced Optimization Techniques for Energy Systems Planning and Operation” is aimed at providing an in-depth introduction to energy system optimization methods. The course will contain a wide range of the basic methods to advanced techniques with hand on examples related to energy systems. The participants will learn how to implement the methods using optimization packages such as GAMS and MATLAB.

Prerequisites

Basic knowledge in linear algebra and programming

Form of evaluation

The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project on the optimization of energy systems at the end of the course.

Price

8000 DKK for the Industry and 6000 DKK for PhD students outside of Denmark (VAT-FREE Education)

The Danish universities have entered into an agreement that allows PhD students at a Danish university (except Copenhagen Business School) the opportunity to free of charge take a subject-specific course at another Danish university.
Read more here: https://phdcourses.dk/ 

Questions

hr@energy.aau.dk   

More information

https://www.energy.aau.dk/research/phd   

Literature:

Books:

1. A. J. Conejo, E. Castillo, P. Pedregal, R. Garcia, N. Alguacil. “Building and        Solving Mathematical Programming Models in Engineering and Science”. John Wiley & Sons, 2002.
2. A. J. Conejo, E. Castillo, R. Minguez, R. Garcia-Bertrand. “Decomposition Techniques in Mathematical Programming. Engineering and Science Applications”. Springer-Verlag, 2004.
3. Zhu, Jizhong. Optimization of power system operation. Vol. 49. Wiley. com, 2009.
4. Rao, S.S., "Optimization, Theory & Applications", 3d Ed. Wiley Eastern Ltd., (1984).
5. Soliman, Soliman Abdel-Hady, and Abdel-Aal Hassan Mantawy. Modern optimization techniques with applications in electric power systems. Springer, 2011.
6. Antonio J. Conejo, Miguel Carrión, Juan M. Morales, “Decision Making Under Uncertainty in Electricity Markets”, Springer, 2010.
7. Stephan Dempe, “Foundations of Bilevel Programming”, Springer, 2002.

Presentations:

1. Natalia Alguacil, Lecture notes on “Linear programming”, Nov. 2009.
2. Lecture notes of “LOG734 Heuristics in Analytics”, Molde University College.
3. Chun-Wei Tsai, “An Introduction to Metaheuristics”, Electrical Engineering, National Cheng Kung University.
4. Esmaeil Atashpaz Gargari et. Al, “Designing MIMO PID Controller using Colonial Competitive Algorithm: Applied to Distillation Column Process”, University of Tehran.
5. - Data Mining”, Sabanci University.
6. Marcelo Sampaio de Alencar, Djalma de Melo Carvalho Filho, “Cellular Network Planning”, River Publishers, 19 Dec 2016.
7. Yong Wang, “Operations Research 04G: Goal Programming”, Binghamton University.
8. Notes of Chris Fricke, “An Introduction to Bilevel Programming”, Department of Mathematics and Statistics University of Melbourne.
9. Dempe, Stephan. “Foundations of bilevel programming”, Springer, 2002.

Papers:

1. A. Anvari-Moghaddam, et al., “Optimal Smart Home Energy Management Considering Energy Saving and a Comfortable Lifestyle”, IEEE Trans. Smart Grid, vol.6, no.1, pp. 324-332, 2015.
2. A. Mansour-Saatloo, et al., “Robust Decentralized Optimization of Multi-Microgrids integrated with Power-to-X Technologies”, Applied Energy, vol. 304, pp. 1-22, 2021.