太阳能风能互补储能发电系统容量优化算法

System Capacity Optimization Algorithm of Energy Storage and Power Generation for Solar Wind Complementary

随着互补型储能发电系统日益普及,其覆盖范围也不断扩大,但容量优化技术仍处于单一能源阶段。为此,针对太阳能风能互补储能发电系统,设计了一种容量优化算法。通过分析发电系统的电能输出情况,获得其年产出与供应状态,然后根据电能均衡准则构建容量优化目标及约束条件。然后结合差分进化算法进行变异、交叉和选择等操作,再通过粒子群算法更新方位与速度,二者结合取得亲体与群体的当前最优解,经迭代循环实现储能系统容量优化。经实验研究分析,并通过对组件配置量、负荷缺电率等数据发现,该算法在大幅提升经济效益的同时,确保了供电可靠性,表明该算法具有显著的优化优越性与较大的试运行潜力。

With the increasing popularity of complementary energy storage power generation system,its coverage is also expanding.But the capacity optimization technology is still in the single energy stage.Therefore,a capacity optimization algorithm is designed for the solar and wind energy complementary storage and power generation system.By analyzing the power output of the power generation system,the state of annual output and supply is obtained,and the capacity optimization objectives and constraints are established according to the power balance criterion.Then,the differential evolution algorithm is used for mutation,crossover,selection and other operations,and the particle swarm optimization algorithm is used to update the orientation and velocity.The current optimal solution of parent body and population is obtained by the combination of the two,and the capacity optimization of energy storage system is realized through iterative cycle.In the experimental,through the data of component configuration quantity and load power shortage rate it is found that this algorithm greatly improves the economic benefits,and ensures the reliability of power supply,which shows that the algorithm has significant optimization advantages and great application potential.