The Research Of Microgrid Optimizing Allocation Based On Anew Hybrid Algorithm

Nowadays, the importance of energy for social progress and economic development is showing more and more prominent. As the worldwide energy shortage and the ecological environment worsen, many countries begin to exploit and utilize new energy, and the electric power industry is also in urgent to reform on intelligent. The micro grid is not only the important part of the construction of smart grid, but also the main way of using new energy, so the microgrid naturally become the focus of national development in the future. If the addressing and capacity planning of microgrid are not reasonable with microgrid grid-connected, it would have a significant impact on the power supply reliability and economy of the main grid. Therefore, the optimal configuration of microgrid has become the focus in the research of the microgrid. The paper uses a new kind of intelligent optimization algorithm to make a reasonable optimization considering the reliability and economy for the distribution network planning with microgrid and the long-term island operation autonomous microgrid, respectively.The main contents are as follows:(1) The paper introduces the concept and development status of microgrid at home and abroad, points out the importance of micro-grid planning for the development of the micro-grid and smart grid, and studies micro-grid planning as the basis of researching reasonable optimization of the microgrid.(2) The paper studies the development of wind turbine、photovoltaic cells、battery and other distributed generations and their performances, explains the theory and mathematical calculation for the planning of microgrid. Many kinds of optimization algorithm of the microgrid planning are presented. The genetic algorithm、particle swarm optimization (pso) algorithm and bacterial foraging algorithm are programmed on MATLAB.(3) The paper takes a 14-node radiant distribution network as an example for distribution network planning with microgrid, and establishes the optimization objective function considering active network loss of distribution network and the investment、operation and maintenance cost of microgrid with the constraints of the various micro-power output、load flow、voltage and current, in order to optimize the construction site and the capacity of the microgrid. Based on the MATLAB programming, the paper uses a new kind of intelligent optimization algorithm:that is the particle swarm optimization based on the bacterial foraging optimization, then obtains the best optimal configuration of address and capacity of microgrid connected with the main grid, and compares its results with the particle swarm algorithm and the bacterial foraging algorithm.(4) The paper takes a particular areas in China as an example for the long-term autonomous and island operation microgrid, and sets up an optimization objective function considering the power supply reliability of microgrid and the investment and operating cost、fuel cost、environmental cost of microgrid, combining with the constraints of micro-sources output and reliability, then optimizates the micro-powers of the island operation microgrid. The optimization also uses the particle swarm optimization based on the bacterial foraging optimization, and obtains the optimization results of microgrid for the the example area. The paper also obtains a conclusion that high power reliability costs high economy. Finally, the paper compares its results with genetic algorithm, particle swarm optimization (pso) algorithm and bacterial foraging algorithm optimization.The research results show that:during the planning of the distribution network with microgrid, the grid active loss through optimizing the microgrid is obviously lower than the distribution network without microgrid, and this is beneficial to improve economy of grid; if the microgrid would improve power supply reliability, it would cost much money; the adopted new algorithm has the advantages of fast convergence, easy to achieve the global optimal, and high calculating precision.