摘要
文章结合某市3个垃圾填埋场CDM项目扩建改造工程,利用填埋气收集利用方法学ACM0001ver.1与AMS-I.D.ver.6、0-1整数规划方法,以填埋气发电系统GHG年减排量最大为目标,选取建设成本、经济利润、填埋气收集、供电等为约束条件,构建了基于发电机组布局的垃圾填埋气GHG减排优化模型。模型优化方案显示:案例工程优化后发电机组布局发生了较大变化,工程总投资降低7.87%,垃圾填埋气发电系统正常运行且产气量稳定条件下,达产年(2020年)最大GHG年减排当量为6 314 397 t(CO2e),较案例推荐方案增加了11.55%,经济效益提高了19.57%,说明合理调整垃圾填埋场CDM项目扩建改造工程发电机组的布局,不但可以减少工程总投资、提高经济效益,还可以有效缓解由于填埋气大量排放造成的温室气体效应。
An optimization model of GHG emission reduction from landfill gas was constructed based on the generator sets layout for a city＇s three landfill CDM expansion and reconstruction projects. In the model,the GHG emission minimization was set as optimization objective, the con- struction cost, economic profit, landfill gas collection and electricity supply and other factors were employed as constraints,combining both the 0-1 integer programming and the ACM0001 ver.1 and AMS-I. D.ver. 6 landfill gas collection and utilization methodology. The optimum proposal showed that： the generator sets layout of the case project changed a lot after optimization, with reduction by 7.87% in the project total investment. Furthermore, under the circumstance of the landfill gas generating electricity system working normally and producing landfill gas stably, the amount of GHG emission reduction equivalent would be up to 6 314 397 t C02e in the year of 2020 （the expected designed capacity was realized）,increasing by 11.55% compared with the case of the previous recommended landfill CDM expansion and reconstruction project.Also, the economic benefits of the project would improve by 19.57%.This indicated that the proper adjustment towards the generator sets layout of the landfill CDM expansion and reconstruction project would not only reduce project total investment and increase economic benefits, but also effectively relief greenhouse effect caused by massive landfill gas emissions.
出处
《可再生能源》
CAS
北大核心
2014年第11期1730-1736,共7页
Renewable Energy Resources
关键词
温室气体减排
填埋气发电
发电机组布局
0-1整数规划
优化模型
GHG emission reduction
landfill gas power generation
Layout of generator sets
0-1 integer programming
optimal model
