Abstract
The implementation of intelligent power grids, in form of smart grids, introduces new challenges to the optimal dispatch of power. Thus, optimization problems need to be solved that become more and more complex in terms of multiple objectives and an increasing number of control parameters. In this paper, a simulation based optimization approach is introduced that uses metaheuristic algorithms for minimizing several objective functions according to operational constraints of the electric power system. The main idea is the application of simulation for computing the fitness- values subject to the solution generated by a metaheuristic optimization algorithm. Concerning the satisfaction of constraints, the central concept is the use of a penalty function as a measure of violation of constraints, which is added to the cost function and thus minimized simultaneously. The corresponding optimization problem is specified with respect to the emerging requirements of future smart electric grids.
| Original language | English |
|---|---|
| Title of host publication | Life System Modeling and Intelligent Computing (LNCS 6329) |
| Publisher | Springer |
| Pages | 368-378 |
| Number of pages | 11 |
| Volume | 6329 LNCS |
| Edition | PART 2 |
| DOIs | |
| Publication status | Published - 2010 |
| Event | International Conference on Intelligent Computing for Sustainable Energy and Environment - Wuxi, China Duration: 17 Sept 2010 → 20 Sept 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Publisher | Springer |
| ISSN (Print) | 0302-9743 |
Conference
| Conference | International Conference on Intelligent Computing for Sustainable Energy and Environment |
|---|---|
| Country/Territory | China |
| City | Wuxi |
| Period | 17.09.2010 → 20.09.2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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