DocumentCode
253586
Title
MOPSO-based multi-objective TSO planning considering uncertainties
Author
Qi Wang ; Chunyu Zhang ; Yi Ding ; Ostergaard, Jacob
Author_Institution
Center for Electr. Power & Energy, Tech. Univ. of Denmark, Copenhagen, Denmark
fYear
2014
fDate
12-15 Oct. 2014
Firstpage
1
Lastpage
5
Abstract
The concerns of sustainability and climate change have posed a significant growth of renewable energy associated with smart grid technologies. Various uncertainties are the major problems need to be handled by transmission system operator (TSO) planning. This paper mainly focuses on three uncertain factors, i.e. load growth, generation capacity and line faults, and aims to enhance the transmission system via the multi-objective TSO planning (MOTP) approach. The proposed MOTP approach optimizes three objectives simultaneously, namely the probabilistic available transfer capability (PATC), investment cost and power outage cost. A two-phase MOPSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of the proposed multi-objective planning approach has been verified by the 77-bus system.
Keywords
Pareto optimisation; power transmission planning; probability; smart power grids; MOPSO-based multiobjective TSO planning; MOTP approach; PATC; Pareto-optimal front set diversity; generation capacity; investment cost; line faults; load growth; optimization problem; power outage cost; probabilistic available transfer capability; smart grid technologies; transmission system operator planning; Investment; Load modeling; Optimization; Particle swarm optimization; Planning; Power system faults; Uncertainty; multi-objective TSO planning; smart grid; two-phase MOPSO; uncertainties;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2014 IEEE PES
Conference_Location
Istanbul
Type
conf
DOI
10.1109/ISGTEurope.2014.7028762
Filename
7028762
Link To Document