Parameter identification method for grid-connected photovoltaic power generation system based on transient disturbance

• Main Authors: SHEN WEICHENG, ZHANG SAI, LIU XIULIANG, WEI RUNZHI, YANG JUN, MA XIPING, LIU KEQUAN, TONG HUANZHEN, DONG KAISONG, WEI BO, XU HONGLEI, ZHAO YAO, CHEN MINGZHONG, MIN ZHANKUI, ZHANG WEI, LIU LIJUAN, LI SHULIN, ZHENG XIANGYU, HU DIANGANG, ZHOU ZHENGLONG, ZHANG GUANGRU, ZHEN WENXI, CHEN BAIXU, DANG JIAN, ZHU HONGYI, ZHAO WEI, LIANG YOUZHEN, LI ZHIMIN, ZHAO LIN
• Format: Patent
• Language: Chinese; English
• Published: 21.02.2020
• Subjects: CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; ELECTRICITY; GENERATION; SYSTEMS FOR STORING ELECTRIC ENERGY

The invention discloses a parameter identification method for a grid-connected photovoltaic power generation system based on transient disturbance. The grid-connected photovoltaic power generation system comprises a photovoltaic array, a DC/DC converter, an inverter controlled by a VSC, an inverter, an inverter controller, and a filter circuit. The filter circuit is connected with a power grid. The DC/DC converter is connected with a maximum power controller. The inverter is connected with the inverter controller. The method is based on an improved genetic algorithm-particle swarm optimization(GA-PSO). By analyzing current changes under different transient disturbances, optimal identification of inverter parameters is achieved. The problem that a traditional mathematical analysis method is inaccurate in identification of the inverter parameters is solved, and a foundation is provided for research on inverter control optimization, low voltage ride-through, power grid power flow optimization and the like. 本发明公开