基于多储能技术经济性比较的可再生能源发电系统多目标容量优化

研究基于蓄电池、熔盐储热、抽水蓄能及储氢技术经济性比较的可再生能源发电系统多目标容量优化。该容量优化模型以最小化平准化度电成本及失负荷率为目标,应用4种代表性多目标进化算法进行求解。提出基于超体积的多目标算法综合评价指标,此外考虑了储能运行特性及资源不确定性提高仿真计算的准确性。算法性能比较结果表明,非劣排序遗传算法的平均排序等级为1.6,其具有最优的综合性能;储能的定量技术经济性比较结果表明,不同可靠性条件下熔盐储热系统的经济性均为最优;不同负荷曲线及不同资源水平的敏感性分析验证了储能经济性比较结果的有效性。

MULTI-OBJECTIVE CAPACITY OPTIMIZATION OF RENEWABLE ENERGY POWER SYSTEM CONSIDERING TECHNO-ECONOMIC COMPARISONS OF VARIOUS ENERGY STORAGE TECHNOLOGIES

This paper conducted the multi-objective capacity optimization of renewable energy power system considering techno-economic comparisons of battery, thermal energy storage, pumped hydro storage and hydrogen storage. The multi-objective capacity optimization model considers the minimization of levelized cost of energy and loss probability of power supply, which is solved by four representative multi-objective evolutionary algorithms. This paper also proposes a comprehensive metric of algorithms based on hypervolume, and the device operation characteristics and resources uncertainties are considered to improve the accuracy of simulation. The comparative results of algorithms show that the average rank of non-dominated sorting genetic algorithm is 1.6, which has the best comprehensive performance. The quantitative techno-economic comparative results of energy storage show that thermal energy storage is the most cost-effective under different reliability conditions. The sensibility analyses of different load profile and different resource level verify the effectiveness of techno-economic comparative results.