Research On Energy Management And Capacity Optimal Design Of Microgrid

With the intensification of global energy crisis and greenhouse effect, microgrid technology is attracting more and more attention and research. Energy management and optimal planning for microgrid are two major subjects. In the paper, the two subjects are taken as the core research field, and the main work involves the following elements.1) The quasi-steady-state models of typical distributed generators, energy storage units, heating and ventilation devices are studied. Meanwhile, the random simulation method of load and renewable resource data is introduced.2) Different energy management methods are presented for both the stand-alone microgrid and grid-connected microgrid in the paper. For combined cooling heating and power(CCHP) mocrogrid, an optimal dispatch model with the minimum operating cost as the optimal objectives. And the model is solved by the mixed integer linear programing(MILP). For stand-alone microgrid, the coordinated control strategies are presented corresponding microgrid consisting of different devices. For those strategies, the diesel generator and energy storage unit are considered to be the main power source, which can maximize the energy utilization rate with the guaranty of reliable and stable operating of the microgrid.3) For CCHP microgrid, a two-stage optimal planning and design method with economic performance and environment performance being considered is presented. For the two-stage model, the first stage is used to optimize the devices capacity of the microgrid, and the second stage is used to optimize the operating dispatch.4) For stand-alone microgrd, the determined method and the stochastic chance-constraint programming method are presented to build the optimal planning and design model. For the two models, the economic performance, power distribution reliability and environmental performance are considered as the optimal objectives. Meanwhile, the type and capacity of distributed generators and energy storage unit are selected as optimal variables to improve the applicability of the model.