Education of Search Algorithm for Power Supply Network Introduction Equipment to Reduce CO<sub>2</sub> Emissions

Abstract

Efforts to increase the amount of renewable energy introduced are accelerating in order to reduce CO2 emissions. Especially in cold regions such as Hokkaido, it is important to reduce not only electric power but also CO2 emissions related to heat demand such as heating. Therefore, we have been studying an algorithm for finding the optimum arrangement of renewable energy equipment to be installed in the power and heat supply network. This search program is developed by a genetic algorithm. As a result of conducting a case study targeting Hokkaido, CO2 was reduced by 20%. Since education on the consumer side is also important for further reduction, we considered a power supply and demand programming contest for students. However, programming using a genetic algorithm requires a huge amount of calculation time, and the accuracy of the solution is not certain, so we decided that it would be difficult to establish it as a contest. Therefore, in the compulsory subjects, we started to create a task that can be educated step-up on the search algorithm of renewable energy equipment that reduces CO2.