Design of a Dynamic Electricity Trade Scheduler Based on Genetic Algorithms

摘要: This paper presents a design and measures the performance of dynamic electricity trade scheduler employing genetic algorithms for convenient application vehicle-to-grid services. Arriving at being plugged-in to microgrid, each electric vehicle specifies its stay time sales amount, while scheduler, invoked before slot, creates connection schedule considering microgrid-side demand available from vehicles given scheduling window. For operations, is encoded an integer-valued vector with complementary definition C-space, which orderly lists all combinatory allocation maps task. Then, integer element indexes map entry in C-space. The measurement result, obtained prototype implementation, reveals that our can stably work even when number sellers exceeds 100 as well improves meet ratio by up 6.3% compared conventional parameter set.