摘要
随着综合能源系统中清洁能源占比的不断增加,供能不确定性与时空分散性愈发凸显,系统建模与优化调度面临较大挑战。针对上述问题,首先,以能量流动模型为基础,建立能够反映设备效率与负荷率之间非线性关系的变工况模型;然后,考虑柔性负荷特性,引入需求侧管理,优化能源定价和时段策略,激励用户参与调度;最后,建立多目标优化模型和双层递阶优化策略,采用智能优化算法进行源–荷互动多目标优化调度。基于某园区典型日负荷和气象数据进行仿真实验,结果显示该方法能够促进良性源–荷互动,充分调动供需两侧的调峰潜力,在保证用户用能舒适度的同时,提高系统运行的经济性、环保性和稳定性。
The ever-increasing proportion of clean energy sources adds the uncertainties and space-time distribution factors to the integrated energy system(IES)making the modeling and optimal dispatching of IES faced with great challenges.Aiming to these problems,an off-design model which reflects the nonlinear relation between efficiency and load rate is established first based on the internal energy flow model.Considering the flexible load characteristics,a demand-side management strategy is applied to encouraging the users to participate in the dispatching by optimizing the energy prices and the period division.Finally,a multi-objective optimization model and a bi-level hierarchy optimal strategy are proposed,on whose basis the multi-objective problem is solved by the intelligent optimization algorithm.The simulation is carried out based on the typical daily load and meteorological data of an IES park,and the results show that the proposed method can promote the positive source-load interaction,mobilize the enthusiasm of supply and demand sides.The economy,environmental protection and stability of the system operation are enhanced without affecting the comfort of energy consumption.
作者
李云鸷
刘吉臻
马素玲
胡阳
LI Yunzhi;LIU Jizhen;MA Suling;HU Yang(State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources(North China Electric Power University),Changping District,Beijing 102206,China;Beijing China-power Information Technology Co.,Ltd.,Haidian District,Beijing 100872,China)
出处
《电网技术》
EI
CSCD
北大核心
2022年第7期2472-2482,共11页
Power System Technology
基金
国家重点研发计划项目(2021YFE0102400)
国家自然科学基金项目(51821004)。
关键词
综合能源系统
变工况模型
源–荷互动
需求侧管理
双层递阶优化
价格激励
integrated energy system
off-design model
source-load interaction
demand-side management
bi-level hierarchy optimization
price incentive