Application Of Multi-agent CSO Algorithm With Different Topologies In Power Grid Economic Dispatching

As an algorithm with full application prospect proposed in 2014,the crisscross algorithm(CSO)is committed to centralizing the free pairing crossover under the joint action of the two operators of horizontal crossover and vertical crossover.Because of this,compared to other algorithms,its advantages in convergence accuracy and convergence speed are quite obvious.In the field of economic dispatching,traditional power grid dispatching and regional integrated energy dispatching have always been the important research areas,which respectively take real-time and accurate dispatching and maximizing energy conservation and emission reduction as the optimization objects.In facing economic dispatching problems,especially in the case of large-scale units running in parallel,the traditional centralized computing not only consume lot of time,but also requires a large amount of computing resources and increases the input of hardware equipment.In this paper,the multi-agent system(MAS)will be able to solve this problem to some extent.MAS imitate the human society which solve problems in a cooperation way,the heavy computational tasks assigned to host multiple individuals(Agent)on multiple computing unit(CPU),and maximum use of idle resources to reduce the hardware investment.Multi-agent system can realize of parallel computing when facing massive economic dispatch problem and try to meet the requirements of real-time scheduling.In order to save energy and reduce emission in real-time scheduling,improving crisscross algorithm is a very worthy direction of research.Although the crisscross algorithm can largely jump out of local optimal,so that the population can avoid the precocity problem to a certain extent.But for higher dimensional problems,it is still possible to stuck into a relative local optimal.To enhance the convergence precision of CSO,this paper set up one parameter average degree 6)and trying to increase species diversity by it.Based on this parameter,this paper proposed nine kinds of different topologies,and tested in test function,DED problems and CHPED problems.In this paper,the performance of multi-agent crisscross algorithm with different topological structures in different models is analyzed in detail,and the influence of population with different topological structures on the convergence accuracy of crisscross algorithm is explored.Firstly,two simulation models of economic dispatching are introduced in this paper.Secondly,MACSO are introduced,and the concept of neighborhood network structure definition and construction is expounded in this paper.Based on this,the multi-agent crisscross algorithm under nine different topological structures is proposed.Finally,the proposed methods will be tested which are test functions and different economic dispatch problems.According to the test result,compare to original CSO,the proposed methods can largely increase the convergence accuracy and save computing time.