摘要
低碳电源规划研究中,为满足电力行业日益增长的减排指标的要求,在规划期内,考虑新建风电场、火电机组和碳捕集机组及对现有火电机组配置碳捕集系统进行改造。在考虑电力、电量及碳减排量等约束条件的基础上,建立年综合成本最小及碳排放量最小的多目标模型,对规划期内每年投运机组的类型及容量进行优化。研究风电出力的不确定性对低碳电源规划的影响,建立鲁棒电源规划优化模型。采用离散细菌群体趋药性算法进行优化计算,得到满足鲁棒性的Pareto最优解。
In order to meet the requirements of the increasing emission reduction index of the power industry,in the study of low carbon power supply planning,new wind farms,new thermal power units,new carbon capture units and retrofitting the existing thermal power units with carbon capture system are considered in the planning period.Considering the constraints of power,electricity and carbon emission reduction,a multi-objective model with minimum annual comprehensive cost and carbon emission is established to optimize the type and capacity of units put into operation each year in the planning period.The influence of uncertainty of wind power output on low-carbon power planning is studied,and a robust power planning optimization model is established.The discrete bacterial colony chemotaxis algorithm is used for optimization calculation,and the Pareto optimal solution satisfying the robustness is obtained.
作者
钟嘉庆
王一鸣
赵志锋
张晓辉
Zhong Jiaqing;Wang Yiming;Zhao Zhifeng;Zhang Xiaohui(Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province of Yanshan University,Qinhuangdao 066004,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2020年第9期114-120,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(6187023566)
河北省高等学校科学技术研究重点项目(ZD2020149)。
关键词
风电场
碳捕集
鲁棒优化
低碳电源规划
离散细菌群体趋药性算法
wind power
carbon capture and storage
robust stability
low-carbon power planning model
discrete bacterial colony chemotaxis algorithm
