Evolutionary Programming Based Optimal Placement of Renewable Distributed Generators

In this paper, an evolutionary programming (EP) based technique has been presented for the optimal placement of distributed generation (DG) units energized by renewable energy resources (wind and solar) in a radial distribution system. The correlation between load and renewable resources has been nullified by dividing the study period into several segments and treating each segment independently. To handle the uncertainties associated with load and renewable resources, probabilistic techniques have been used. Two operation strategies, namely turning off wind turbine generator and clipping wind turbine generator output, have also been adopted to restrict the wind power dispatch to a specified fraction of system load for system stability consideration. To reduce the search space and thereby to minimize the computational burden, a sensitivity analysis technique has been employed which gives a set of locations suitable for DG placement. For the proposed EP based approach, an index based scheme has also been developed to generate the population ensuring the feasibility of each individual and thus considerably reducing the computational time. The developed technique has been applied to a 12.66-kV, 69-bus distribution test system. The solutions result in significant loss reduction and voltage profile improvement.