Using chaotic quantum genetic algorithm solving environmental economic dispatch of Smart Microgrid containing distributed generation system problems

With the decreasing of the fossil energy source and the increasing of load demand, making full use of clean and renewable energy, Distributed Generation (DG) technologies gain more and more attentions. Smart Microgrid (SMG) integrates the advantages of power generation from new energy and renewable energy power generation systems connected to the grid. SMG can not only enhance the comprehensively cascaded utilization of energy, but also can be used as an effective complementary network of the utility in order to improve the power supply reliability and power quality. SMG is becoming one of the most up-to-date and important topics in the field of power systems all over the world. According to the characteristics of distributed generation in SMG, such as photovoltaic (PV), wind power (WP), fuel cell and micro gas turbine, considering different fuel, efficiency, operation and maintenance costs, greenhouse gas emission level of distributed generation with various types and capacity, characteristic of PV and WP, a novel model environmental and economic dispatch of SMG was presented, which considered generation cost and emission cost. In this paper, use the quantum genetic algorithm to confirm the accuracy and validity of the mathematic model through some actual examples, and then used this method to compare with some other optimization approaches that usually be used to solve the economic dispatch problem to show the superiority and usability of the approach mentioned here.