Comparison of different redispatch optimization strategies

Nowadays, electric networks very often work on their transmission limits because of the growing use of renewable and distributed energy sources, the growth of the power grid complexity, the strong electricity market competition, some forecast errors and the general increase of the network utilization. Hence, the risk of congestions in the power grids has permanently grown especially in central Europe. If a line congestion occurs, the transmission system operators have to apply a suitable remedial measure to remedy it very fast and optimally. One of the methods used to avoid line congestions is redispatch. However, its realization is still not optimal in most cases. Therefore, the optimization of this process has become very important issue for the transmission network operators especially in Germany. In this paper several optimization methods for the solving of the redispatch optimization problem, such as simplex, genetic algorithms, particle swarm optimization and mean variable mapping optimization, are introduced and compared.