Research Of Multi-objective Optimization For Wind-solar-battery Hybrid Power System

With the development of smart grid and distributed generation technologies, Wind and photovoltaic power generation as the most important part of the new energies, Which gained each country’s attaches. But they also have the weakness of energy density low and the characteristics of strong randomicity. Because of this, The separate photovoltaic generating system or wind power generation system difficult to provide a reliable and stable power output, In consideration of the complementary characteristics of wind and solar resource in time and geography, We can build the wind-solar-battery hybrid power system to meet the requirement of power quality. The wind-solar-battery hybrid power system consists of the Wind turbine, photovoltaic ("PV") array, energy storage unit, system controller and so on, how to reasonably optimize various parts of the system capacity to meet system power supply reliability and economical efficiency become a hot topic.Based on the distribution of wind or solar resources in the northwest of China, An improved multi-objective capacity optimization for wind-solar-battery power system is proposed in this thesis. This thesis analyzes the work principle of wind turbines and solar cell and the system architecture of the wind power generation. Then the mathematical models of wind turbine, photovoltaic panel and battery are established, secondly, Based on the economy and reliability of the system as the objective function, An objective function combining the system total cost and loss of power supply probability is built to keep a balance between the economy and reliability of the system. At last, considering the system stand-alone modes, The complementary characteristics and grid-connected modes will influence the fluctuation of power injected into the grid, Different optimization objective are considered in both stand-alone and grid-connected modes. The objectives include investment costs, power supply reliability, wind-solar resources utilization and power fluctuation. The vector-evaluated genetic algorithm (VEGA) is used to solve the optimal problems, The optimal allocations of distributed source and batteries are found in micro-grid.