Research On Environmental/Economic Dispatch Based On Adaptive Artificial Bee Colony Algorithm

Economic dispatch(ED)is a hot research topic in power system dispatch optimization.Its essence is to meet the end users demand for electricity by rationally arranging the operation mode and flexibly distributing the load of the unit under various constraints.Different from traditional ED,in response to the call for energy conservation and emission reduction,as well as relieving the pressure of global energy and environment,environmental/economic dispatch(EED)with consideration of environmental pollution?fuel cost and dynamic factors become an urgent problem to be solved in the new market environment.Lots of artificial intelligence optimization algorithms have been applied to solve this dynamic?multi-objective and highdimensional optimization problem,among which artificial bee colony(ABC)algorithm that is put forward on the basis of foraging behaviors of bees have been widely used in numerical optimization problems.Based on the background above,this thesis takes the environmental/economic dispatch problem as the research framework,and studies the dynamic,multi-objective economic dispatch model by proposing an adaptive artificial bee colony algorithm.The main work of the thesis is summarized as follows:(1)Environmental/economic dispatch model is established,which considers the fuel cost and polluted gas emissions as the scheduling targets at the same time,and comprehensively consider the dynamic factors of valve point effect and the environmental/economic dispatch model of the four constraints of the upper and lower limit constraints,climbing rate,prohibited zone and unit output balance.(2)Adaptive artificial bee colony algorithm(Adaptive ABC),is achieved by resizing the population of bee colony dynamically in original artificial bee colony(ABC)algorithm,via introducing memory feedback mechanism(MFM)to the running process and the concept of evolutionary rate to improve the efficiency of the algorithm,it achieves the balance of exploration and exploitation.(3)The experimental simulation mainly includes two parts: one is the effectiveness verification of the adaptive artificial bee colony algorithm based on the benchmark function,which proves the superiority of the proposed method in the optimization effect.The second is to solve the environmental/economic dispatch model based on the test set of IEEE 6-unit system,and apply the weighted coefficient method to realize the multi-objective transformation of adaptive artificial bee colony algorithm in environmental/economic dispatch problem.The experimental results show that the adaptive artificial bee colony algorithm achieves better optimization results in the dynamic multi-objective environmental/economic disaptch model.