摘要
我国乡村地区生物质能产出与分布式光伏发电已经成为乡村能源结构中重要的组成部分,如何因地制宜发展乡村生物质资源,紧密贴合乡村自然条件、资源禀赋以及实际用能需求,拔高乡村光-沼耦合利用能效是亟待解决的问题。基于提升乡村地区光-沼虚拟电厂的低碳经济性运行需求,首先,给出沼气能源系统动力学量化模型,建立沼气能源系统耦合分布式光伏发电系统的动态模型;考虑乡村地区沼气能源系统和光伏机组出力的多重不确定性,建立光-沼能源供能主体不确定性集合;考虑光-沼虚拟电厂低碳运行成本,以日前调度为基础,提出基于深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法的两阶段低碳调度方法,以虚拟电厂低碳运行成本和调度成本最小为优化目标,对乡村地区光-沼虚拟电厂中的分布式光伏及沼气资源的整合利用方案进行修正。最后,通过算例结果验证所提光-沼虚拟电厂低碳调度方法的合理性和有效性。
The biomass energy production and distributed photovoltaic(PV)power generation in rural areas of China have emerged as vital components of the rural energy structure.How to develop rural biomass resources according to local conditions,closely fit the natural conditions,resource endowments,and actual energy needs of rural areas,and improve the energy efficiency of rural PV-biogas coupling utilization is an urgent problem to be solved.In this paper,firstly,the dynamic quantitative modeling of biogas energy system is carried out,a dynamic model of biogas energy system coupled with distributed PV power generation system is established based on improving the low-carbon economic operation demand of PV biogas virtual power plant in rural areas.Considering the multiple uncertainties of biogas energy system and photovoltaic unit output in rural areas,an uncertainty set is established for PV-biogas energy supply entities.Furthermore,considering the low carbon operation cost of the PV-biogas virtual power plant,based on the day-ahead scheduling,a data-driven real-time scheduling method based on the deep deterministic policy gradient(DDPG)algorithm is proposed.With the minimum low carbon operation cost and scheduling cost of the virtual power plant as the optimization goal,the centralized and distributed PV and biogas resources in the PV-biogas virtual power plant in rural areas are integrated.Finally,the rationality and effectiveness of the proposed low-carbon scheduling method for PV-biogas virtual power plant are verified by the example results.
作者
王琛
孙哲夫
张自伟
WANG Chen;SUN Zhefu;ZHANG Ziwei(State Grid Lianyungang Power Supply Company,Lianyungang 222000,China)
出处
《山东电力技术》
2025年第7期14-26,53,共14页
Shandong Electric Power
基金
国网江苏省电力有限公司科技项目(J2023168)。
关键词
低碳调度
光-沼耦合
虚拟电厂
数据驱动
多重不确定性
low carbon scheduling
PV-biogas coupling
virtual power plant
data-driven
multiple uncertainties
