Many-objective optimization of energy conservation and emission reduction in China’s cement industry

Industrial Energy Conservation and Emission Reduction (ECER) management is challenging due to the large number of objectives involved, and the complex synergies/conflicts amongst them. Most studies do not quantify these synergies/conflicts, resulting in high dimension ECER management problems. This study builds a 10-objective problem to optimize 5 heavy metals (Cd, Hg, Pb, As, Cr) and 5 conventional ECER-objectives (economic cost, energy, CO2, PM and NOx) in China’s cement industry. First, NSGA-III is used to calculate optimal objective values under technology application constraints. Second, synergies/conflicts amongst objectives are quantified using Spearman’s correlation. Finally, TOPSIS, Conservation Supply Curves and Quadrant methods are used to generate optimal ECER management policies. Results show that: (1) Optimal solutions are reliable as reflected by algorithm verification metrics – Error rate, Spacing metric and Hypervolume indicator; (2) The 10-objective problem is reduced to a 4-objective problem based on synergies. The four main-objectives are economic cost, energy consumption, CO2 and PM emission control. Therefore, ECER policies should focus on these objectives since optimizing them will synergistically improve all other objectives; (3) The average reduction potential for HMs and conventional objectives is 20% and 25% respectively, with an increase in economic cost of about 44–83 CNY/t; (4) From 72-ECER strategies assessed, 11-key strategies have better economic and environmental performances. They are mostly circular economy strategies utilizing industrial wastes, indicating that ECER policies should shift from traditional end-of-pipe approaches to a more circular economy approach. In sum, the proposed methodology can reduce the complexity of many-objective ECER management through a synergic control.