Research On Improved BBO Algorithm And Its Application In Optimal Scheduling Of Micro-Grid

With the multiple pressures of the national economy,power system and ecosystem,the way that fossil fuels are used to generate electricity is overburdened,and new power generation methods are desired to be developed urgently.The micro-grid is gradually concerned because of its clean and flexible characteristics,and the increase of clean energy utilization and the decrease of environmental pollution are its significant advantages,so the research on the optimal scheduling of micro-grids is of great significance.In this thesis,aiming at the cooperative optimization of economy and environmental protection of the traditional micro-grid,the P2 G with the ability of discarding wind,light and carbon capture is added.Further,the micro-grid model is established,and the improved BBO algorithms are also applied to solve the objective functions.Furthermore,the operation cost and pollution gas treatment cost are considered.Finally,the energy scheduling of micro-grids is realized.The main research contents are demonstrated as follows:Firstly,the micro-grid containing carbon capture device and P2 G is constructed,and the working principle and relevant mathematical models of various components are described.Then the energy control strategy of micro-grids is developed.Further,two single objective functions and one multi-objective function are derived,which is conducive to laying the foundation for the next optimal scheduling.Secondly,IBBO algorithm is proposed.Compared with traditional algorithms such as De,ES and BBO,the ecological expansion operation is added,and new mobility model is used to improve the search speed and performance.On this basis,the convergence of IBBO is derived in detail.Then IBBO is used to solve the energy optimal scheduling problem,which contains two kinds of single objective in micro-grids.The efficacy of the proposed methods is shown by presenting simulation results in single objective optimization of the micro-grid.Finally,HDBBO algorithm based on the hybrid migration and dual-mode mutation strategy is studied.The micro disturbance factor and Gaussian mutation are respectively presented to traditional BBO,Then the convergence is also analyzed,and the superior advantages in terms of optimization accuracy and convergence speed are manifested by the simulation results.Further,the multi-objective optimal scheduling of micro-grids is researched.The feasibility of the proposed methods is demonstrated by presenting simulation results in multi-objective optimization of micro-grids.In conclusion,these two proposed BBO algorithms can be used to solve the optimal scheduling problems in the micro-grid.The utilization rate of renewable energy can be improved,and the operation cost and the environmental pollution of micro-grids can be decreased.Thus,this thesis is good at theoretical research and practical application value.