A Control Method for Regulating Power Supply Based on the Combination of Ant Colony Algorithm and Genetic Algorithm

Currently, the power system planning software developed domestically and internationally mainly focuses on the current power structure of fossil energy generation, based on traditional power generation optimization and scheduling models. Existing planning software platforms are difficult to adapt to the flexible regulation of coal electricity and new energy collaborative planning needs, and lack the construction of carbon emission assessment modules. This article designs a platform architecture for collaborative planning and carbon emission assessment of multiple types of regulated power sources and new energy, establishes a basic database for grid transmission network planning, develops functional modules for collaborative planning and carbon emission assessment of multiple types of regulated power sources and new energy, integrates key technologies for collaborative planning of multiple types of regulated power sources and new energy. The results indicate that this algorithm overcomes the shortcomings of genetic algorithm which can obtain the local optimal solution. It also shortens the task scheduling time of cloud computing system and achieves better task scheduling effect. The average cost of the tasks completed by the algorithm is obviously lower than that of the other two algorithms and the solution is better.