个人简历

教育经历\r
2006/09-2011/07，中国科学技术大学，管理学博士（与中国科学院科技政策与管理科学研究所联合培养硕博连读研究生），导师为范英研究员\r
2002/09-2006/07，华东理工大学，管理学学士\r
\r
研究工作经历\r
工作经历\r
2020/09-至今，北京航空航天大学经济管理学院，教授\r
2015/12-2020/09，北京航空航天大学经济管理学院，副教授\r
2015/02-2015/12，中国科学院科技政策与管理科学研究所，副研究员\r
2011/07-2015/01，中国科学院科技政策与管理科学研究所，助理研究员\r
\r
国际访问经历\r
2017/03-2017/06获批“香港特别行政区政府输入内地人才计划”，应邀赴香港中文大学开展光伏技术发展评价合作研究\r
2015/01-2015/02应邀作为访问学者访问新加坡国立大学能源研究所，并作为专家参与‘China’s Regional Diversities in Energy Use and Carbon Emission’项目研究，主要负责能源投资评价和技术评估\r
2012/03-2012/04获全额资助赴瑞典参加哥德堡大学经济系“Environmental Policy Instruments course study”（环境政策建模）课程学习（世界范围内共12位博士受此资助）。通过课程考核获得7.5个欧洲博士学位学分\r
2009/07-2009/08获全额资助赴澳大利亚参加了由国际能源署（IEA）举办的“IEA GHG International CCS Summer School”（碳捕获与封存暑期学校）\r
\r
国际交流经历\r
2018/04/27-2018/04/28应香港中文大学香港亚太研究所（HKIAPS）邀请赴香港参加全球可持续发展和一带一路国际学术研讨会并做报告\r
2016/11/10-2016/11/11应新加坡国立大学能源研究所（NUS-ESI）邀请赴新加坡参加新加坡-中国能源论坛并做报告\r
2015/11/13-2015/11/14应日本国立环境研究所（NIES）邀请赴日本参加第21届AIM国际研讨会并做报告\r
2015/11/27应东亚与东盟经济研究所（EIRA）邀请赴印尼参加东盟与东亚经济研究所（ERIA）工作组会议

研究领域

主要从事能源技术的评价方法与决策优化""

近期论文

Lei Zhu, Xu Wang, and Dayong Zhang. 2020. Identifying Strategic Traders in China's Pilot Carbon Emissions Trading Scheme. The Energy Journal, 41(2): 123-142.\r
\r
Lei Zhu, Xing Yao, Xian Zhang. 2019. Evaluation of cooperative mitigation: case study of captured carbon dioxide for enhanced oil recovery. Mitigation and Adaptation Strategies for Global Change, 25(7): 1261-1285.\r
\r
Lei Zhu, Yuan Xu, Yingjie Pan. 2019. Enabled comparative advantage strategy in China's solar PV development. Energy Policy, 133: Article 110880.\r
\r
Lei Zhu, Linju Chen, Xueying Yu, Ying Fan. 2018.Buying green or producing green? Heterogeneous emitters’ strategic choices under a phased emission-trading scheme. Resources, Conservation and Recycling, 136: 223-237.\r
\r
Lei Zhu, Pan Peng, Xin Wang, Ying Fan. 2017.Exploring optimal mitigation and adaptation investment strategy in China. Climate Policy,18(6):781-793.\r
\r
Lei Zhu, Xiao-Bing Zhang, Yuan Li, Xu Wang, Jianxin Guo. 2017.Can anEmission Trading Scheme Promote the Withdrawal of Outdated Capacity inEnergy-Intensive Sectors? A Case Study on China’s Iron and Steel Industry. Energy Economics,63:Pages 332-347.\r
\r
Lei Zhu, Zhongxiang Zhang, Ying Fan. 2015. Overseas oil investment projects under uncertainty: how to make informed decisions? Journal of Policy Modeling, 37:742-762..\r
\r
Lei Zhu, Xin Liu. 2015. Promoting the Carbon Removal in Coal Utilization- A Benefit-Risk Analysis Among Full-Chain Carbon Capture and Utilization Project. Energy & Environment, 26(6&7): 1035-1053..\r
\r
Lei Zhu, Hong-Bo Duan, Ying Fan. 2015. CO2 mitigation potential of CCS in China - an evaluation based on an integrated assessment model. Journal of Cleaner Production, 103:934-947.\r
\r
Lei Zhu, Ying Fan. 2013. Modelling the Investment in Carbon Capture Retrofits of Pulverized Coal-Fired Plants. Energy, 57(8): 66-75.\r
\r
Lei Zhu. 2012. A simulation based real options approach for the investment evaluation of nuclear power. Computers and Industrial Engineering, 63(3): 585-593.\r
\r
Lei Zhu, Xiao-Bing Zhang and Ying Fan. 2012. A Non-Linear Model for Estimating the Cost of Achieving Emission Reduction Targets: the Case of the US, China and India. Journal of System Science and System Engineering, 21(3): 297-315.\r
\r
Lei Zhu, Ying Fan. 2011. A real options based CCS investment evaluation model: case study of China’s power generation sector. Applied Energy. 88(12): 4320-4333.\r
\r
Lei Zhu, Ying Fan. 2010. Optimization of China s Generating Portfolio and Policy Implications Based on Portfolio Theory. Energy, 35: 1391-1402.\r
\r
Yao, X., Fan, Y.,Zhu, L.*, Zhang, X. 2020. Optimization of dynamic incentive for the deployment of carbon dioxide removal technology: A nonlinear dynamic approach combined with real options. Energy Economics, 86: 104463.\r
\r
Xing Yao, Bowen Yi, Yang Yu, Ying Fan,Lei Zhu*. 2020.Economic analysis of grid integration of variable solar and wind power with conventional power system.Applied Energy,Volume 26415 April 2020Article 114706\r
\r
Yuan Li, Beixing Wang, Yanli Xie,Lei Zhu*. 2020.Cost and potential for CO2 emissions reduction in China’s petroleum refining sector—A bottom up analysis.Energy Reports,6:497-506.\r
\r
Li, L., Liu, J.,Zhu, L*. 2020. Dynamics of energy technology diffusion under uncertainty. Applied Stochastic Models in Business and Industry, 36(5): 795-808.\r
\r
Lei Zhu, Lianbiao Cui,Joachim Schleich. 2020.Designing a globally acceptable carbon tax scheme to address competitiveness and leakage concerns.Climate Change Economics, 11(2), 2050008.\r
\r
Songmin Yu, Ying Fan,Lei Zhu*,Wolfgang Eichhammer.Modeling the Emission Trading Scheme from an Agent-based Perspective: System Dynamics Emerging from Firms' Coordination among Abatement Options.European Journal of Operational Research, 286: 1113-1128.\r
\r
Xinyuan Ren,Lei Zhu. 2020. Influence of allowance allocation events on prices in China’s carbon market pilots– an AR-GARCH-based analysis. Energy Sources Part B Economics Planning and Policy, 15(3):1-15.\r
\r
Xinyuan Ren, Dayong Zhang*,Lei Zhu*, Liyan Han. 2020 How do carbon prices react to regulatory announcements in China? A genetic algorithm with overlapping events. Journal of Cleaner Production, 277: 122644.\r
\r
JunXie, Zhuang Liang, Xiaobing Zhang,Lei Zhu*. 2019. Efficiency evaluation of thermal power plants in China based on the weighted Russell directional distance method. Journal of Cleaner Production, 222(10): 573-583.\r
\r
Xu Wang, Xiao-Bing Zhang,Lei Zhu*. 2019. Imperfect market, emissions trading scheme, and technology adoption: A case study of an energy-intensive sector. Energy Economics, 81: 142-158.\r
\r
Kangjuan Lv, Xia Feng, Scott Kelly,Lei Zhu*, Maozhi Deng*. 2019. A study on embodied carbon transfer at the provincial level of China from a social network perspective. Journal of Cleaner Production, 225(10): 1089-1104.\r
\r
Pan Peng, Xinyuan Ren,Lei Zhu*, Ying Fan, Tavoni Massimo. 2019. A Comparison of Two Approaches for Damage Evaluation on Optimal Mitigation and Adaptation Responses in China. Journal of Systems Science and Complexity, 32: 1641–1658.\r
\r
Xing Yao, Ying Fan, Yuan Xu, Xian Zhang,Lei Zhu*, Lianyong Feng. 2019. Is it worth to invest? -An evaluation of CTL-CCS project in China based on real options. Energy, 182(1): 920-931.\r
\r
Li Li, Junqi Liu,Lei Zhu*, Xiao-Bing Zhang. 2020. How to design a dynamic feed-in tariffs mechanism for renewables – a real options approach. International Journal of Production Research, Accepted. DOI: 10.1080/00207543.2019.1652776\r
\r
Bingxin Zeng,Lei Zhu*, Xing Yao. 2020. Policy choice for end-of-pipe abatement technology adoption under technological uncertainty. Economic Modelling,87:121-130.\r
\r
Bingxin Zeng,Lei Zhu*.2019.Market Power and Technology Diffusion in an Energy-Intensive Sector Covered by an Emissions Trading Scheme. Sustainability, 11, 3870\r
\r
Bingxin Zeng, Jun Xie, Xiaobing Zhang, Yang Yu*,Lei Zhu*. 2019. The impacts of emission trading scheme on China’s thermal power industry: A pre-evaluation from the microlevel.Energy & Environment, 31(6): 1007-1030.\r
\r
Yingjie Pan, Xing Yao, Xin Wang*,Lei Zhu*. 2019. Policy Uncertainties: What Investment Choice for Solar Panel Producers. Energy Economics,78:454-467.\r
\r
Xing Yao, Ping Zhong, Xian Zhang*,Lei Zhu*. 2018. Business model design for the carbon capture utilization and storage (CCUS) project in China. Energy Policy, 121: 519-533\r
\r
Xu Wang,Lei Zhu*, Ying Fan. 2018. Transaction costs, market structure and efficient coverage of emissions trading scheme: A microlevel study from the pilots in China.AppliedEnergy, 220(15): 657-671\r
\r
Xin Liu, Yuan Li, Dayong Zhang*,Lei Zhu*. 2018.On the Effectiveness of the Abatement Policy Mix: A CaseStudy of China’s Energy-Intensive Sectors. Energies,11(3): 1-31\r
\r
Pan Peng,Lei Zhu*, Ying Fan. 2017.Performance Evaluation of Climate Policies in China: A Study Based on an Integrated Assessment Model. Journal of Cleaner Production,164:1068-1080.\r
\r
Songmin Yu,Lei Zhu*. 2017.Impact of Firms’ Observation Network on theCarbon Market. Energies, 10(8): 1-14.\r
\r
Xiaobing Zhang,Lei Zhu*. 2017.Strategic Carbon Taxation and Energy Pricing under the Threat of Climate Tipping Events. Economic Modeling,60:352-363..\r
\r
Hongbo Duan,Lei Zhu*, Gurkan Kumbaroglu,Ying Fan. 2016.Regional Opportunities for China to Go Low-Carbon: Resultsfrom the REEC Model. The Energy Journal,37(SI1): 223-252.\r
\r
Jianxin Guo,Lei Zhu*.2016.Optimal timing of technology adoption under the changeable abatement coefficient through R&D. Computers & Industrial Engineering, 96: 216-226\r
\r
Lian-Biao Cui, Pan Peng,Lei Zhu*. 2015. Embodied Energy, Export Policy Adjustment and China's Sustainable Development: A Multi-Regional Input-Output Analysis. Energy, 82(3):457-467.\r
\r
Yuan Li,Lei Zhu*. 2014. Cost of energy saving and CO2 emissions reductions in China’s iron and steel sector. Applied Energy, 130: 603-616.\r
\r
Hong-Bo Duan,Lei Zhu*, Ying Fan. 2014. Optimal carbon taxes in carbon constrained China: A logistic-induced energy economic hybrid model. Energy, 69(5): 345-356.\r
\r
Jian-Lei Mo,Lei Zhu*. 2014. Using Floor Price Mechanisms to Promote CCS Investment and CO2 Abatement. Energy and Environment, 25(3&4): 687-707..\r
\r
Chang-Sheng Li,Lei Zhu*, Tobias Fleiter. 2014. Energy Efficiency in Shandong Chlor-Alkali sector in China –Based on a Process-Specific Technology Assessment of Saving Potentials. Energy and Environment, 25(3&4): 661-686..\r
\r
Handong He, Di Hu, Qun Sun,Lei Zhu, Yanrong Liu. 2019. A landslide susceptibility assessment method based on GIS technology and an AHP-weighted information content method: a case study of southern Anhui, China. ISPRS International Journal of Geo-Information, 8(6), 266.\r
\r
Lianbiao Cui, Rongjing Li, Malin Song,Lei Zhu. 2019. Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments? Energy Economics, 83: 61-73.\r
\r
Lianbiao Cui, Yi Sun, Malin Song,Lei Zhu. 2019. Co-financing in the green climate fund: lessons from the global environment facility. Climate Policy, In press.\r
\r
Lianbiao Cui, Malin Song,Lei Zhu.2019. Economic evaluation of the trilateral FTA among China, Japan, and South Korea with big data analytics. Computers & Industrial Engineering, 128: 1040-1051.