摘要
综合考虑江苏省经济增长、能源节约与CO2、SO2减排的目标,运用改善的GADS优化算法对江苏省能耗结构进行优化,并对比江苏省低碳发展的情景,测算了江苏省能源消费结构优化的节能减排效应。研究结果表明:①能耗结构优化主要表现为高碳能源低度化,低碳能源高度化的演变过程。煤炭仍占主导地位,且呈倒"U"型的发展趋势,2020峰值1.822×108tce,而天然气与低碳能源在总量与结构上均呈上升趋势;②能源结构优化具有正负双向效应,一方面节能减排效应显著,2020年将节能2.244×108tce,CO2减排1.275×108t,但难以实现2020年减排目标,还需其它方面的努力。另一方面由于能源成本等因素造成GDP较之于低碳情景将减少2.096×1012元;③以"低"代"高"的能源优化策略是转移环境压力的主要途径,但其先决条件是煤炭资源的清洁高效利用与新能源核心技术的突破。未来江苏省能源消费结构的优化应以煤炭资源的清洁、高效利用为主,同时加快风能、太阳能、生物质能等新能源资源的产业化、规模化发展。
Considering the goals of economic growth of Jiangsu Province, energy saving and pollution reduction, applied an improved GADS algorithm to optimize energy consumption structure, and designed multi-programs to conduct the scenario comparison and trends analysis. The results show that： （1）the process of energy consumption optimization manifested an salient features, which is the utilization of high-carbon energy and the improvement of low-carbon technology. Coal still dominated the energy structure and inverted ＇U＇ shaped trends, peaking 182. 175 million tce in 2020, the gas and low-carbon energies showed an upward trends in amount and structure ; （2）energy consumption optimization had two-side effects, noticeable effect of energy-saving 224.4 million tee, and reduce the carbon emissions 127.5 million tons in 2020, on the other hand, GDP will be reduced 2. 096 trillion yuan ; （3）To ＇ low＇ on behalf of the ＇high＇ energy optimization strategy is the main way to transfer environmental pressures, but the prerequisite is that coal resources＇ efficient utilization and breakthroughs in core technologies of new energies. The future energy structural optimization should be mainly based on clean and efficient utility of the coal, and accelerate the low carbon energies＇ industrial development, such as the wind, solar, biomass and other new energy resources.
出处
《中国人口·资源与环境》
CSSCI
北大核心
2011年第3期48-53,共6页
China Population,Resources and Environment
基金
国家自然科学基金基金项目(No.71073157)
江苏省哲学社会科学研究基地项目(No.09JD023)
江苏省软科学研究计划项目(No.BR2008079)
国家统计局全国统计科研计划重点项目(No.2010LB10)
关键词
能源消费结构
多目标优化
节能
碳排放
经济增长
energy consumption structure
multi-objective optimization
energy savings
carbon emission
economic growth
