The Research On Optimal Operation Of Micro-grid With High Proportion Of Renewable Energy

As two of the most abundant natural resources in clean energy,wind and solar energy have been widely used in recent years.Wind power generation and solar power generation have random fluctuation,and direct connection to the power grid will have impact on the main power grid,which is not conducive to the utilization of renewable energy and unified dispatching of the main power grid.As a new type of energy management system,micro-grid can provide effective technology for the utilization of renewable energy.Wind and solar power generation is connected to the micro-grid through power electronic devices such as grid-connected inverter.The micro-grid conducts unified dispatching of all power sources to deal with the random fluctuation of renewable energy.With the increase of the grid-connected proportion of renewable energy,the operation scenarios of the power grid become more complex,and the non-negligible equivalent impedance of the power grid seriously affects the stable operation of the power system.Therefore,it is very important to study the optimization of grid-connected inverter and micro-grid scheduling strategy.In the micro-grid with a high proportion of renewable energy,problems such as network impedance and harmonic are prominent,and the operation mode of the original grid-connected inverter is gradually unable to meet the operation requirements of the micro-grid.Based on the analysis of the weak power grid model and the existing inverter control mode,a new LCL filter parameter design method and the inverter adaptive control mode based on this parameter are proposed,considering the influence of system parameters change,sampling delay and power grid harmonic and other factors.The control mode mainly includes two adaptive links.According to the design method of LCL filter parameters,the filter parameters that match the actual power grid are calculated,and the current feedback of capacitor branch is taken into account;else,according to the collected actual impedance of the grid,the proportional resonance(PR)controller's proportional resonance coefficient is updated to form the second adaptive link.Finally,the effectiveness of the filter parameter optimization method and adaptive control method is verified by experiment.The optimization method can make the inverter adapt to the operation condition of high proportion renewable energy.Due to the uncertainty and randomness of renewable energy,the scheduling optimization method of micro-grid has the characteristics of large computation,multi-dimensional and non-linear.Based on the establishment and analysis of the mathematical model of micro-grid,a micro-grid economic optimization model considering both environmental benefits and operating costs is constructed by using renewable factors and unit power production cost.In order to meet the requirements of rapidity,effectiveness and real-time for micro-grid scheduling,an economic optimization algorithm based on Bayesian theory and particle swarm optimization is proposed.The particle renewal formulas are used in the algorithm to solve the structural learning problem of Bayesian network,and then update a group of particles.Then,the Bayesian information criteria(BIC)are used to evaluate the fitness of the new particles,and the global optimal solution is updated through the fitness value of the particles.Finally,a typical micro-grid system is used to verify the method.The results show that the BN-PSO algorithm avoids the problems of slow convergence and easy to fall into the local optimum,and has certain advantages in convergence effect and operation time;what's more,the Bayesian network needs to be further studied,which is also a new idea to deal with the uncertainty of renewable energy.