TY - GEN
T1 - Overview
T2 - International Conference on Intelligent Computing for Sustainable Energy and Environment
AU - Hutterer, Stephan
AU - Auinger, Franz
AU - Affenzeller, Michael
AU - Steinmauerer, Gerald
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=78649544333&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15597-0_41
DO - 10.1007/978-3-642-15597-0_41
M3 - Conference contribution
VL - 6329 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 368
EP - 378
BT - Life System Modeling and Intelligent Computing (LNCS 6329)
PB - Springer
Y2 - 17 September 2010 through 20 September 2010
ER -
