Research On Economic Dispatching Of Smart Grid Based On Particle Swarm Optimization

The problem of economic dispatch is to maximize the economic efficiency of operation and minimize the total energy cost of the system under the primary premise of satisfying the stable operation of the system and ensuring the quality of power.In essence,it is an optimal problem.In view of the consideration of the newly added disturbance factors in the power grid system,some of the original classic solution processing algorithms are already powerless.Furthermore,as the people gradually pay more attention to the surrounding living environment,the problem of economic dispatch has changed from a single-objective optimization that only targets the total cost of power generation to a multi-objective optimization that simultaneously takes into account the total cost of power generation and pollutant emissions.Starting from the traditional economic dispatching model of the power system and the classic solution algorithm,this paper has roughly completed the following tasks:First,it analyzes the traditional economic dispatch model of the power system and the classic calculation method.A traditional economic dispatch model that only takes into account the balance of supply and demand and the output constraints of units is constructed,which only aims at minimizing the total cost of power generation.The solution process of Lambda iterative method is shown according to actual calculation examples,and the effect of unit valve point and environmental factors on the built model are discussed.Secondly,considering the excellent effect of the swarm algorithm in solving non-convex optimization,under the premise of carefully analyzing the origin and principle of the particle swarm optimization(PSO)algorithm and the influence of various parameters on the performance of the algorithm,A variety of targeted improvement measures.The IEEE-30 node standard test system is used,and the improved algorithm and the basic particle swarm algorithm are respectively used to solve the problem.By comparing the simulation results of the two algorithms,it is verified that the improved particle swarm algorithm can solve the economic dispatch problem taking into account the valve point effect of the unit Outstanding in the.Finally,the problem of multi-objective environmental economic dispatch of power system is studied.Taking into account the impact of pollutant emissions on the surrounding environment,the economic dispatch problem is transformed into a multi-objective optimization problem including cost and pollutant emissions.Therefore,a mathematical model of multiobjective environmental economic dispatch of the power system is constructed.Based on the Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,an improved MOPSO algorithm is proposed in combination with the Pareto optimal theory.The model is used to perform Matlab simulation experiments on the model,and the simulation results are compared with NSGA-II The algorithm is compared with the MOPSO algorithm.The simulation results show that the proposed improved algorithm can effectively converge to the Pareto optimal frontier of this kind of multi-objective economic scheduling problem.