Improvement of Loadability in Distribution System Using Genetic Algorithm
This work addresses loadability improvement in power distribution systems, which is an incremental advancement in optimizing DG placement for operational efficiency.
The paper tackles the problem of improving loadability in distribution systems by optimizing the placement of distributed generation (DG) sources using a genetic algorithm, achieving maximized loadability as demonstrated on IEEE standard benchmarks.
Generally during recent decades due to development of power systems, the methods for delivering electrical energy to consumers, and because of voltage variations is a very important problem, the power plants follow this criteria. The good solution for improving transfer and distribution of electrical power the majority of consumers prefer to use energy near the loads .So small units that are connected to distribution system named "Decentralized Generation" or "Dispersed Generation". Deregulated in power industry and development of renewable energies are the most important factors in developing this type of electricity generation. Today DG has a key role in electrical distribution systems. For example we can refer to improving reliability indices, improvement of stability and reduction of losses in power system. One of the key problems in using DG's, is allocation of these sources in distribution networks. Load ability in distribution systems and its improvement has an effective role in the operation of power systems. However, placement of distributed generation sources in order to improve the distribution system load ability index was not considered, we show DG placement and allocation with genetic algorithm optimization method maximize load ability of power systems .This method implemented on the IEEE Standard bench marks. The results show the effectiveness of the proposed algorithm .Another benefits of DG in selected positions are also studied and compared.