Research On Multi-objective Optimal Dispatch Strategy For Microgrid

As a typical way of effective consumption and manangement of distributed generation,microgrid can coordinate and solve the contradiction between distributed generation and distributed network,on the other hand,it can take the advantages of distributed generation technology,such as reducing economic costs and environmental impact.At the same time,the study of multi-objective optimization provides a theoretical basis for the optimal dispatching of microgrid.In this dissertation,two kinds of microgrid are studied.Considering economy,environmental protection,reliability,voltage deviation and other factors,a multi-objective optimal scheduling model of microgrid is established,and two different solving methods are introduced,which provides ideas and solutions for the optimization of microgrid.Firstly,the characteristics and mathematical model of each component in the microgrid are stated.At the same time,the working principle and grid-connection model of each distributed generation are also studied.The microgrid with taking the wind,solar,diesel and energy is taken as an example,and a scheduling model with three optimization objectives including system economic operation cost,pollutant treatment cost and system load shedding cost is developed.Then,the multiple optimization objectives are transformed into a single objective by linear weighting method,and the hierarchical analysis method and quantum behaved particle swarm optimization algorithm are combined.At the same time,the performance of microgrid is studied Finally,a case study is given to verify the practicability and effectiveness of the method.The grid structure,operation cost,voltage deviation and active power loss of the system are considered.Taking IEEE 33 node microgrid as an example,a multi-objective optimal scheduling model of microgrid is established,and then the model is studied from the perspective of solving the problem directly.The niche technology based on crowding mechanism and non dominated sorting strategy are introduced into particle swarm optimization algorithm,and the improved particle swarm optimization algorithm is proposed to solve the two objective and three objective optimal scheduling models respectively.Finally,the fuzzy decision method is applied.The Pareto frontier is analyzed to find the Pareto optimal frontier solution which can balance the contradiction of all objectives.Finally,the content of the article is summarized and prospected,and the follow up research direction is introduced.