An optimization method for energy structures based on life cycle assessment and its application to the power grid in China.

Abstract The optimization of energy structures, aimed at saving energy and reducing emissions, is an important precautionary measure against climate change. This study considers different environmental impacts of power systems, and investigates ways to optimize power structures and decrease their po...

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Publicado en:Journal of Environmental Management Vol. 238; pp. 18 - 25
Autores principales: Ding, Ning, Pan, Jingjin, Liu, Jingru, Yang, Jianxin
Formato: Artículo
Publicado: Academic Press Inc. May2019
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        03014797
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      jtl: Journal of Environmental Management
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      dt: May2019
      vid: 238
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      pub: Academic Press Inc.
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        135513920
        10.1016/j.jenvman.2019.02.072
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        atl: An optimization method for energy structures based on life cycle assessment and its application to the power grid in China.
      aug:
        au:
          Ding, Ning
          Pan, Jingjin
          Liu, Jingru
          Yang, Jianxin
        affil:
          State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
          University of Chinese Academy of Sciences, Beijing, 100049, China
      su:
        China
        Nuclear energy
        Solar energy
        Electric power distribution grids
        Electric power production
        Wind power
        Raw materials
      sug:
        subj:
          Nuclear energy
          Solar energy
          China
          Fossil Fuel Electric Power Generation
          Nuclear Electric Power Generation
          Other Farm Product Raw Material Merchant Wholesalers
          Solar Electric Power Generation
          Other electric power generation
          Wind Electric Power Generation
          Electric power distribution grids
          Electric power production
          Wind power
          Raw materials
      keyword:
        Greenhouse gas emissions
        Life cycle assessment
        Material input
        Power structure
        Water deprivation
        Greenhouse gas emissions
        Life cycle assessment
        Material input
        Power structure
        Water deprivation
      ab: Abstract The optimization of energy structures, aimed at saving energy and reducing emissions, is an important precautionary measure against climate change. This study considers different environmental impacts of power systems, and investigates ways to optimize power structures and decrease their potential environmental impact. A multi-objectives optimization model of energy structures was created based on life cycle assessment (LCA). This model covers several environment impacts, rather than only focusing on carbon emissions. LCA was used to calculate the different environmental impacts and provided a new method for normalization. The model was applied to the power industry in China. Three kinds of environmental impacts were considered: material input (MI), global warming potential (GWP), and water deprivation (WD). The five major existing methods of electricity generation in China were considered: thermal power, nuclear power, hydro power, wind power, and solar photovoltaic power. The system boundary included all life cycle stages; specifically, extraction of raw materials and resources, production, energy generation processes, and power transport. The optimization results showed that the total environmental impacts were reduced; MI, GWP, and WD were decreased by 29.53%, 29.67%, and 19.06%, respectively. This method provides new insights into optimization of energy structures by considering multi-environment impacts. Highlights • An optimization model for energy structures based on LCA was established. • This study provides reduction way of multiple environment impacts for energy system. • A novel and expanding application of LCA methodology was provided.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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