Research On Optimal Model For Low-carbon Urban Agglomeration Based On Energy Structure Reduction

Carbon dioxide from human activities is making the greenhouse effect more andmore serious. Construction of low-carbon city is one of the main ways to reducegreenhouse gas. This paper built index system of the urban agglomeration low-carbondevelopment according to the principles of sustainable development of economic,social, environment.In this paper, the urban agglomeration was divided into key construction of the"core area" and outside the "buffer area" according to the regional planning of urbanagglomeration, optimization goal is urban agglomeration net carbon emissionsminimum, built a certainty optimization model of the low carbon urban agglomerationbased on energy structure emission reduction combined with reduction targetsrequires that were put forward by national greenhouse gas emission. The case studyshows that the net carbon emission of urban agglomeration is3.83×10~7tons in2015,and the carbon intensity was decreased by24.26%and energy intensity was reducedby30.27%compared with those in2010; meanwhile, the carbon intensity and energyintensity in the core area was reduced by32.55%and35.28%respectively comparedwith those in2010. The optimized scheme could not only meet the requirements ofcarbon intensity decreased by17.00%, energy intensity reduced by16.00%in2015compared with those in2010proposed by the12th Five-Year Planning Outline ofControlling Greenhouse Gas Emission, but also complied with the requirements ofcarbon intensity decreased by18.00%and energy intensity reduced by20.00%ofregional planning targets.Taking into account the uncertainty about different energy carbon emissionscoefficient parameters, this paper adjusted the low-carbon model of urbanagglomerations through introducing interval programming method and built anuncertainty optimization model of the low carbon urban agglomeration based onenergy structure emission reduction. The model optimized the quantity of carbonquantity and the ownership of carbon sink in2015. Optimization results show that thenet carbon emission of the urban agglomeration is [3.83,4.77]×10~7tons in2015, and the carbon intensity was decreased by [24.26,31.23]%and energy intensity wasreduced by [30.27,36.25]%compared with those in2010; meanwhile, the carbonintensity and energy intensity in the core area was reduced by [32.55,33.80]%and[35.28,35.83]%respectively compared with those in2010. The optimized resultscould not only meet the requirements of carbon emission reduction in2015comparedwith those in2010proposed by the12th Five-Year Planning Outline of ControllingGreenhouse Gas Emission, but also complied with the requirements of carbonintensity decreased by18.00%and energy intensity reduced by20.00%of regionalplanning targets. The established model provided more decision-making space for thesustainable development of low-carbon urban agglomeration.In order to enhance the stability of the model，this paper built an uncertaintyoptimization model of the low carbon urban agglomeration based on energy structureemission reduction， Introduced the concept of membership degree on the basis of thecertainty and uncertainty of the urban agglomeration optimization model. Theobjective function is maximize the degree of membership and modified the originalobjective function and constraints. Optimization results show that the carbon intensityof the urban agglomerations was decreased by [20.11,32.73]%and energy intensitywas reduced by [27.63,37.70]%compared with those in2010. The carbon intensityand energy intensity in the core area was reduced by [27.23,36.68]%and [32.55,37.57]%respectively compared with those in2010. The results could not only meetthe requirements of carbon emission reduction and energy consumption intensityreduction proposed by the12th Five-Year Planning Outline of ControllingGreenhouse Gas Emission, but also complied with the requirements proposed byregional planning targets. The model improved the stability of the optimization modelon the basis of meeting greenhouse gas emissions targets of carbon intensity, energyintensity which were put forward by national and regional, and provided a scientificbasis for the development of low-carbon urban agglomeration.