Mitigating voltage sag by optimal allocation of Distributed Generation using Genetic Algorithm

The necessity for flexible electric systems, changing regulatory and economic scenarios, quality of power and environmental impacts are providing impetus to the development of Distributed Generation (DG), which is predicted to play an increasing role in the electric power systems of the future. With so much new DG being installed, it is essential that the effects on power systems be assessed accurately so that DG can be applied in a manner that not only avoids causing degradation of power quality; but also it enhances specific indices in that category. For these reasons, a new procedure is proposed based on a Genetic Algorithm (GA), capable to establish the optimal distributed generation allocation on a MV distribution network, considering the vulnerability of the system to voltage sag. In order to demonstrate the effect of DG allocation in a network three indices have been examined. Average RMS (Variation) Frequency Index, SARFIx; which represents the average number of specified RMS variation events that occurs over the assessment period per customer served, the Overall Sag Performance (OSP) which is the number or percentage of buses experiencing voltage sag and the Overall Voltage Drop (OVD) which is basically a summation of all voltage drops in the distribution network under study. The first index reveals the effect of the positioning, on the end users, while the other two reflect the effect on the whole network. The most appropriate places for DG installation have been found to be the weakest parts of the network. The results show that the appropriate placement of DG results in a tremendous improvement of the aforementioned indices.