The Optimization Design Of Solar Micro Grid In The Mountain Areas Of High Altitude

A large number of non electric areas are scattered in the plateau mountainous region, and need larger heat, it is difficult to use the traditional way to meet the functional approach. But in these regions, the solar energy resources are generally more abundant, so it is in line with the actual to introduce the solar thermal power generation into the micro grid and building an independent solar grid which based of the solar thermal energy and photovoltaic. The design of micro grid is the basis of the construction of micro grid, the optimal design of the capacity of the distributed units in the micro grid is the most important problem in the process of micro grid planning, the results are directly related to whether the micro grid can be economical, reliable, safe and environmentally friendly operation.First of all, this paper put the micro source types and the basic structure of the independent micro grid in mountainous regions of high altitude, and then give the battery life model and the mathematical model of the steady state power of the trough solar power generation system, the PV system, the wind turbine system, the battery system, the diesel engine and the micro gas turbine and then planed the design of the optimization design model including the economic, reliability and environmental protection of the system. At the same time, with the reference of the existing expert strategy and the operating principle of the micro grid, develop a possible comparison of six types of two operating strategies from the role of the battery and diesel engine.Secondly, in view of the characteristics of the optimization design model, this paper combine the advantages of the nonlinear adaptive inertia factor adjustment method and simulated annealing algorithm to improving the particle swarm optimization algorithm, and test the performance of the algorithm and give the concrete process of solving the optimization model with the algorithm.Finally, use the instance data, through comparison and analysis of the optimization results of different optimization algorithms and different operation strategies, we prove the effectiveness and superiority of the improved algorithm and the optimization model, find the optimal operation strategy and the main search direction of the algorithm and then make the sensitivity analysis of the non use of energy penalty cost, pollutant treatment cost, solar energy preferential policy.