摘要
将可再生能源技术、储能技术与天然气冷热电联产技术相融合的复合能源系统是构筑未来清洁低碳、安全高效能源体系的重要方式。然而,这种复合能源系统结构复杂、变量众多、各种形式的能量输出相互耦合,难以优化;同时,由于气象参数及用户侧需求的强烈波动,对能源系统的设计优化通常需要详细的模拟和大量的输入数据,而现有方法在长时间尺度的优化上无法兼顾计算速度及其准确性。为此,基于全年逐时负荷,设计一个结合遗传算法和优劣解距离法的双层协同多目标整体优化框架。内层以运行成本、余热利用率、电网交互为目标优化余热分配比及发电单元功率;外层则以年成本、一次能源消耗、二氧化碳排放为目标优化设备容量,通过内外层间的迭代确定设备最优容量及运行规划。此外,通过与基于典型日负荷的典型日优化方案对比发现,基于全年负荷的全年优化方案下的年成本、二氧化碳排放、一次能源消耗、电网依赖程度分别减少3.64%、3.04%、17.56%及40.27%,整体表现优异,表明该方法可为研究类似能源系统的设计和运行优化提供有效借鉴和解决方案。
The hybrid energy system that integrates renewable energy technology,energy storage technology with natural gas cogeneration technology is an important way to build a clean,low-carbon,safe and efficient energy system in the future.However,this kind of hybrid energy system is difficult to optimize due to its complex structure,numerous parameters and variables and high coupling degree of multiple supply energy.On the other hand,due to the strong fluctuations of meteorological parameters and user-side demand,the design and optimization of the energy system require detailed simulation and a large number of input data.However,the existing methods can not balance the accuracy and calculation speed in such long-time-scale optimization.Therefore,this study proposes a two-layer global multi-objective co-optimization framework that combines genetic algorithm and the technique for order of preference by similarity to ideal solution based on hourly load throughout a year.The inner layer optimizes the ratio of waste heat distribution and the power of the generating unit with the objectives of operation cost,waste heat utilization rate and grid interaction.The outer layer optimizes the equipment capacity based on the annual cost,primary energy consumption and carbon dioxide emission.The optimal capacity and operation planning of the equipment are determined by the iteration between the inner and outer layers.Furthermore,by comparing with the typical-day optimization scheme,the research finds that the year-round optimization scheme possesses a better overall performance with 3.64%less annual cost,3.04%less carbon dioxide emission,17.56%less primary energy consumption and 40.27%less power grid dependence.The above results show that the method this paper proposed can provide effective reference and solution for the study of similar energy system design and operation optimization.
作者
刘中明
刘江岩
姜志远
李夔宁
刘彬
LIU Zhongming;LIU Jiangyan;JIANG Zhiyuan;LI Kuining;LIU Bin(Key Laboratory of Low-Grade Energy Utilization Technology and System of Ministry of Education,Chongqing University,Shapingba District,Chongqing 400044,China;College of Energy and Power Engineering,Chongqing University,Shapingba District,Chongqing 400044,China)
出处
《分布式能源》
2023年第2期26-36,共11页
Distributed Energy
基金
重庆市自然科学基金面上项目(cstc2019jcyj-msxmX0537)。
关键词
复合能源系统
可再生能源
多储能
双层协同优化
全年优化
hybrid energy system
renewable energy
multiple energy storage
two-layer global co-optimization
year-round optimization