Research On Optimal Energy Management Technology Of Microgrids

With the concerns on energy crisis and environmental pollution, and the flourishing of wind, solar energy and other renewable energy power generation, the microgrid technology is introduced in order to meet the large-scale applications of renewable distributed generation energy. Microgrid can integrate a variety of distributed generation technologies effectively, exerting economic and environmental benefits brought from new energy generation and smart grid fully. Besides, it can meet the demand of users for higher power quality and reliability in a better way, which has become an important part of the smart grid. Optimal energy management for microgrid is the important guarantee to achieve safe, reliable, economical, efficient and intelligent operation.This paper focuses on the research of microgrid energy optimal management technology. At first, the research background and its significance, an overview of microgrid and its domestic and abroad development situation, the study status of the optimal energy management of microgrid were comprehensively introduced. On the basis of considering the fuel cost, operation and maintenance cost, battery depreciation cost and power purchase cost, an economic scheduling mathematical model of microgrid was established with the goal of minimum operating cost. A bat optimization algorithm was used in economic operation scheduling of microgrid method. And then, a mathematical model of dynamic optimal operation scheduling for microgrid was presented according to the characteristics of microgrid operation and its internal relations between different time periods. The objective is to obtain an optimal operation scheduling at minimum operating cost and emission, while meeting the load demand and system operating requirements. A binary bat optimization is proposed to optimize the operation scheduling of microgrid. At last, in order to deal with the uncertainty in the output of wind power, photovoltaic power and load demand, the randomness of these variables were incorporated into the optimization model. An improved black hole algorithm was combined with three-point estimate method to achieve optimal operation of microgrid and its uncertainty analysis through certain relations between stochastic variables and objective function by the use of Cornish-Fisher series expansion.