Title :
Probabilistic calculation of total transfer capability (TTC) for power systems with wind farms using evolutionary algorithms
Author :
Aghaebrahimi, M.R. ; Golkhandan, R. Kazemi ; Ahmadnia, S.
Author_Institution :
Univ. of Birjand, Birjand, Iran
Abstract :
Total transfer capability (TTC) represents the maximum power transfer between areas of a power system, while considering its constraints. In modern power systems, it is important to determine the TTC between different areas as it has become a very serious concern for grid designers. This index is used in the operation, design and electricity marketing stages of power systems. In recent years, there is much attention towards the use of renewable energy units in power systems, which increases the necessity of applying probabilistic methods. In this paper, the probabilistic calculations of power transfer capability in the presence of wind farms are performed, applying evolutionary algorithms. In addition, K-means clustering algorithm is applied in clustering the data related to the wind farms´ output power. Then, the simulation results obtained from applying evolutionary algorithms are compared with each other. IEEE 30-bus system is used as the test network.
Keywords :
evolutionary computation; pattern classification; power grids; power transmission; wind power plants; IEEE 30-bus system; K-means clustering algorithm; TTC; evolutionary algorithms; maximum power transfer; power systems; probabilistic calculation; renewable energy units; total transfer capability; wind farms output power; Classification algorithms; Clustering algorithms; Convergence; Evolutionary computation; Probabilistic logic; Wind farms; Wind turbines; Evolutionary Algorithm; Probabilistic Calculation; Total Transfer Capability (TTC); Wind Farms;
Conference_Titel :
Power Electronics and ECCE Asia (ICPE-ECCE Asia), 2015 9th International Conference on
DOI :
10.1109/ICPE.2015.7168073