Models And Application Research Of New Energy System

With the further deepening of the global energy crisis, increasingly highlight the importance of new energy field of research. Microgrid using renewable energy as supply power is a substitute for the traditional centralized power grid. Microgrid technology research and development potential is tremendous. Microgrid system is small, its grid capacity is limited, and the load sequence fluctuation and highly not smooth and nonlinear. At the same time, wind power, photovoltaic power generation is conditioned by nature objective conditions, the power and the power supply quality is affected by user load. So how to increase the short-term load forecasting accuracy of the micro power grid, improve power supply quality has become a current research hot spot. This paper make a thorough research on the regulation of wind power, photovoltaic power generation, the reasonable combination of systems and the structure design, draws some meaningful conclusions. The research results provide a new thinking and new path for the study of the microgrid technology.This paper summarizes microgrid short-term load forecasting background, significance and research development at home and abroad. This paper designs solar energy and wind energy complementary microgrid system structure. Firstly introduces the basic working principle of wind power and solar power. On the basis of renewable energy sources’complementary advantages, the author designs the main wiring diagram of the microgrid with solar energy, wind energy and energy storage. This paper analyzes the working principle of microgrid structure, combing with featured solar energy device operated in maximum conversion efficiency. Secondly, this paper introduces the mathematical model of microgrid contain photovoltaic battery output characteristic, main grid system signal model, storage battery charging and discharging model and model of the wind turbine. Then put forward a multi-model switching predictive control strategy and research the multi-model predictive control switch strategy of complex systems under linear time-varying and nonlinear time-varying system structure. Again, this paper proposes a normalization preprocessing prediction model of micro power grid load value, and use a quantum particle swarm optimization (QPSO) to optimize adaptive neural fuzzy inference system (ANFIS) prediction algorithm. On the basis of theory analysis, simulation, and combining with the actual micro power grid load data of a certain island, the results show that the method is effective. Finally, introduced the influence factors of microgrid power quality problems, choose the combination type reactive power compensation device. Build a reactive power optimization model, using an improved quantum particle swarm optimization algorithm for reactive power optimization. Finally the simulation results verify the effectiveness of the proposed model and algorithm, through reasonable reactive power optimization can decrease grid network loss and improve power quality.