Title :
Evolutionary programming based optimal placement of renewable distributed generators
Author :
Khatod, D.K. ; Pant, Vivek ; Sharma, Jaibir
Author_Institution :
Alternate Hydro Energy Centre, Indian Inst. of Technol. Roorkee, Roorkee, India
Abstract :
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.
Keywords :
distributed power generation; evolutionary computation; sensitivity analysis; turbogenerators; wind turbines; 69-bus distribution test system; clipping wind turbine generator output; distributed generation unit; evolutionary programming technique; optimal placement; probabilistic technique; radial distribution system; renewable distributed generators; renewable energy resource; sensitivity analysis technique; turning off wind turbine generator; voltage 12.66 kV; wind power dispatch; Evolutionary computation; Load modeling; Mathematical model; Reactive power; Renewable energy sources; Resource management; Wind energy generation; Wind power generation; Distributed generation; evolutionary programming; renewable energy resources; sensitivity analysis;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2012.2211044