考虑风电消纳多向量流系统的遗传优化方法

随着全球能源短缺问题的加剧，风电的大规模消纳显得十分重要。为了克服风电大规模消纳困难的问题，提出一种多矢量储氢发电系统的遗传优化方法。分别研究分析风力风电、氢储能系统、储气罐中的等效荷电状态的数学模型，建立以风电本地消纳最大化为目标的联合优化模型，结合多种约束条件，通过遗传算法实现能量流最优解的求取。以东北某地区的实际测量数据为基础，进行了案例分析。通过对系统在运行过程中的风电消纳效果进行比较，验证了所提方法能够有效减少交互电量，实现了风电本地消纳最大化。

Genetic optimization method for multi-vector flow system considering wind power consumption

With the global energy shortage problem intensifying, the large-scale consumption of wind power is very important. In order to overcome the difficulty of large-scale wind power consumption, a genetic optimization method for a multi-vector hydrogen storage power generation system is proposed. Study and analyze mathematical models of equivalent state of charge in wind power, hydrogen energy storage systems, and gas storage tanks separately. Establish a joint optimization model with the goal of maximizing local wind power consumption. Combined with various constraints, the genetic algorithm is used to achieve Finding the optimal solution of energy flow. Based on the actual measurement data of a certain area in Northeast China, a case analysis was carried out. By comparing the effects of wind power consumption during the operation of the system, it is verified that the proposed method can effectively reduce the interaction power and maximize the local wind power consumption.