基于双层多情景的风光抽水蓄能混合系统多目标随机优化研究

Multi-objective Stochastic Optimization of Wind-wind Pumped Storage Hybrid System Based on Double-layer Multiple Scenario

风能、太阳能等可再生能源已成为减少环境污染的有效供能方式之一。然而,由于其出力的随机性、不稳定性以及间歇性,难以被电网全部直接消纳,导致了大量的弃风弃光,而将风光和抽水蓄能电站结合有望解决这一问题。本文针对风-光-抽水蓄能混合系统,采用双层多场景随机优化模型,以一次能源节约率、年均成本节约率以及二氧化碳减排率作为目标函数,对混合系统经济、技术以及环境性能进行了优化分析,得到了混合系统的最优容量配置和运行策略。结果显示,综合考虑系统经济性以及环境收益,可以实现年均成本节约率为49.9%,二氧化碳减排率为61.8%。仿真结果表明,所建立的模型能够有效地实现混合系统的容量及运行规划,模型具有较高的可行性。

Wind energy,solar energy and other renewable energy has become one of the effective ways to reduce environmental pollution.However,due to the randomness。instability and intermittence of its output,it is difficult to be directly absorbed by the power grid,resuling in a large number of wind and light abandonment,and the combination of wind and pumped storage power stations is expected to solve this problem.For the wind-light-pumped storage hybrid system,a double-layer multi-scenario stochastic optimization model was adopted in this paper,and the economic,technical and environmental performance of the hybrid system was optimized and analyzed with primary energy saving rate。annual average cost saving rate and carbon dioxide emission reduction rate as the objective function,and the optimal capacity configuration and operation strategy of the hybrid system were obtained.The results showed that,considering the economic and environmental benefits of the system,the average annual cost saving rate was 49.9%,and the carbon dioxide emission reduction rate was 61.8%.The simulation results show that the proposed model can effectively realize the capacity and operation planning of the hybrid system,and the model has high feasibility.