基于投入产出非线性优化的制造业完全能耗强度情景分析

当前,环境污染仍为中国最突出的问题之一,而降低制造业完全能耗强度是减少消耗及污染的重要途径。本文基于投入产出非线性优化理论,以制造业完全能耗强度最小为目标,并以18个行业最终需求为决策变量,构建了一个完全能耗强度非线性优化模型,特引入了进出口系数等约束条件,并基于已有投入产出表等数据,预测调整模型的相关系数。在此基础上,设计了三个方案与两个情景,并运用粒子群算法求解模型。结果表明:2015年中国制造业完全能耗强度最小值区间为0.7823-0.9048tce/万元,相比2010年,下降率区间为8.9%-21.31%。在高方案情景2下,可实现制造业完全能耗强度降低20%的目标。为实现该目标,应促进中低能耗制造业发展、降低高能耗制造业的完全能耗量、适当提高消费和进口系数并降低投资和出口系数。本文既有利于政府部门制定科学系统的节能减排政策,也有利于深化能源经济与管理理论。

Scenario Analysis of Complete Energy Intensity of Manufacturing Industry in China Based on Input and Output and Non-linear Optimization

Presently, environmental pollution is still one of the most prominent problems in China, to lower complete energy intensity of manufacturing industry is an important approach to reduce consumption and pollution. Based on input and output and non-linear optimization theory, non-linear optimization model of complete energy intensity is constructcd on the basis of minimum target of complete energy intensity of manufacturing industry and decision variables of 18 industries' final demands. It introduces import and export coefficients for constraint condition specially, then forecasts and adjusts correlation coefficients of the model based on existing data from input-output table and so on. On the basis of it, three schemes and two scenarios are designed and particle swarm optimization is applied to resolve model. Results show that minimum value range of complete energy intensity of manufacturing industry is from 0.7823 to 0.9048 ton of coal equivalent/ten thousand yuan in 2015. Compared with 2010, the decline rate range is from 8.9% to 21.31%. Under scenario 2 of high scheme, it can realize the goal that complete energy intensity of manufacturing industry decreases by 20%. To achieve this goal, China is supposed to promote the development of manufacturing industry in low and medium energy consumption, reduce complete energy consumption of manufacturing industry in high energy consumption, heighten the consumption and import coefficients and lower the investment and export coefficients reasonably. This paper is beneficial to government departments to formulate scientific and systematic policy of energy conservation and emission reduction and conducive to deepening energy economic and management theory.