Modeling And Simulation Of Multi-Objective Optimal Operation And Energy Management For Microgrid

With the development of smart grid technology, it is more convenientfor the implementation of demand-side response and integration of all kindsof distributed energy resources. The paper first analyses the respectivefunctions of distributed generation, load and energy storage in the microgridoptimal operation, and builds up a three-dimension and more flexibleoptimization framework based on the proposed concept of generalizeddemand side resource.As a mobile demand side resource, plug-in electric vehicle has thepotential ability to be utilized in harmony with renewable energy and makeit possible to synthesize all kinds of generalized demand side resources. EVsare studied from two aspects in this paper. Firstly, from the view ofdistributed EVs, this paper focuses on the charge and discharge controlstrategy which should interact with other demand side resources to enhancethe optimal operation effect. Meanwhile the diversity of EV users’requirements should also be taken into consideration. Secondly from theview of a large group of EVs, this paper studies the group behavior. Themodel is formulated base on the probability distribution of EV users’behavior to smooth the fluctuation of the grid load.In order to reduce the dimension of the optimal operation problem, thispaper puts forward a solving model which combines the heuristic rules andparticle swarm algorithm. The heuristic rules are used to generate theoptimal strategies for storages and loads, while the multiple-objective PSOis employed to optimize the power resources. To achieve both stability andaccuracy in the optimal control, the receding horizon optimizationtechnology is adopted. The simulation cases which consider three kinds of demand sideresources demonstrate the effectiveness of the proposed method.