title: Scenario analysis of carbon emissions' anti-driving effect on Qingdao's energy structure adjustment with an optimization model, Part II: Energy system planning and management.
abstract: In this study, an inexact multistage stochastic mixed-integer programming (IMSMP) method was developed for supporting regional-scale energy system planning (EPS) associated with multiple uncertainties presented as discrete intervals, probability distributions and their combinations. An IMSMP-based energy system planning (IMSMP-ESP) model was formulated for Qingdao to demonstrate its applicability. Solutions which can provide optimal patterns of energy resources generation, conversion, transmission, allocation and facility capacity expansion schemes have been obtained. The results can help local decision makers generate cost-effective energy system management schemes and gain a comprehensive tradeoff between economic objectives and environmental requirements. Moreover, taking the CO2emissions scenarios mentioned in Part I into consideration, the anti-driving effect of carbon emissions on energy structure adjustment was studied based on the developed model and scenario analysis. Several suggestions can be concluded from the results: (a) to ensure the smooth realization of low-carbon and sustainable development, appropriate price control and fiscal subsidy on high-cost energy resources should be considered by the decision-makers; (b) compared with coal, natural gas utilization should be strongly encouraged in order to insure that Qingdao could reach the carbon discharges peak value in 2020; (c) to guarantee Qingdao's power supply security in the future, the construction of new power plants should be emphasised instead of enhancing the transmission capacity of grid infrastructure.
authors.affiliation: MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, S-C Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China.
authors.forename: C B
authors.initials: CB
authors.lastname: Wu
authors.affiliation: MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, S-C Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China. Electronic address: huang@iseis.org.
authors.forename: G H
authors.initials: GH
authors.lastname: Huang
authors.affiliation: MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, S-C Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China.
authors.forename: Z P
authors.initials: ZP
authors.lastname: Liu
authors.affiliation: MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, S-C Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China.
authors.forename: J L
authors.initials: JL
authors.lastname: Zhen
authors.affiliation: State Grid Shandong Electric Power Research Institute, Jinan 250002, China.
authors.forename: J G
authors.initials: JG
authors.lastname: Yin
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D002244:Carbon / Q000032:analysis*; D002681:China; D003247:Conservation of Natural Resources; D011211:Electric Power Supplies; D008962:Models, Theoretical; D011210:Power Plants; D035501:Uncertainty
chemical_list: D000393:Air Pollutants; D002244:Carbon
keywords: Anti-driving effect; Energy structure adjustment; Inexact multistage stochastic programming; Mixed-integer programming; Scenario analysis