Wu C B, Huang G H, Liu Z P, Zhen J L, Yin J G
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.
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.
J Environ Manage. 2017 Mar 1;188:120-136. doi: 10.1016/j.jenvman.2016.12.001. Epub 2016 Dec 19.
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 CO emissions 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.
在本研究中,开发了一种非精确多阶段随机混合整数规划(IMSMP)方法,以支持区域尺度的能源系统规划(EPS),该规划涉及以离散区间、概率分布及其组合形式呈现的多种不确定性。为了证明其适用性,针对青岛制定了基于IMSMP的能源系统规划(IMSMP-ESP)模型。已获得能够提供能源资源生成、转换、传输、分配及设施容量扩展方案的最优模式的解决方案。这些结果有助于地方决策者制定具有成本效益的能源系统管理方案,并在经济目标和环境要求之间实现全面权衡。此外,考虑到第一部分中提到的CO排放情景,基于所开发的模型和情景分析研究了碳排放对能源结构调整的反驱动效应。从结果中可以得出几条建议:(a)为确保低碳和可持续发展的顺利实现,决策者应考虑对高成本能源资源进行适当的价格控制和财政补贴;(b)与煤炭相比,应大力鼓励天然气的利用,以确保青岛在2020年达到碳排放峰值;(c)为保障青岛未来的电力供应安全,应强调新建电厂的建设,而不是增强电网基础设施的输电能力。