【作者】 顾玲玲；

【导师】 孙伟；

【作者基本信息】 合肥工业大学 ， 电子信息（专业学位）， 2024， 硕士

【摘要】 为实现我国“碳达峰”、“碳中和”的目标,响应国家的碳交易政策,控排企业不仅需要在供能端增加清洁能源占比来降低碳排放,实现能源调度优化。还需要在用能端减少能源的消耗来降低碳排放、从而减少配额的购买和“碳税”的支出。因此,分析控排企业全流程生产经营中的碳排放过程尤为重要。然而,在分析控排企业碳排放的过程中,控排企业不仅存在产生大量碳排放的来源不明、影响因素不明、影响因素因素之间是否相互关联不明等问题。同时,企业设备的碳关联数据(主要包括煤炭、电力、天然气等能源数据)中存在海量的异常数据,且不同类别能源数据的特征、采集频率不同对研究也带来了困扰。此外,在工业生产中,受外部因素的影响,能源供应和价格波动常常变化无常,能源系统负荷和新能源波动对多能源优化也是一个亟待解决的难题。因此,控排企业很难以碳排放指标为约束进行多能调度优化,从而无法实现利益最大化。为解决上述问题,本文提出了一种基于碳关联体系框架的控排企业多能优化控制策略,以企业碳排放为约束实现企业产出利润最大化。本文的主要工作如下:(1)针对控排企业在全流程生产经营中碳排放的影响因素不明晰,碳排放影响因素之间关系不明晰等问题。本文基于灰色关联度分析和主成分分析方法构建控排企业设备与碳排放的关联体系框架,通过该框架可以确定设备包括哪些碳关联数据。(2)针对企业多能用量数据中存在大量的异常数据,且不同类别能源数据的特征、采集频率不同的问题。本文提出了一种基于小波分解与重构的预测模型,并将其成功应用于钢铁企业场景。通过实验证实了该算法的有效性和准确性。(3)针对以碳排放指标为约束,在满足生产要求的基础上,难以进行多能优化调度的问题。本文提出了一种综合的多能优化控制策略,基于粒子群算法求解了控排企业在时域上的多能控制策略的最优解,将多能优化控制策略应用到钢铁企业场景。通过实验验证了该方案的有效性与可行性。更多还原

【Abstract】 To achieve the goals of"carbon peaking"and"carbon neutrality"in China and respond to the national carbon trading policy,key emission reduction enterprises need to not only increase the proportion of clean energy on the supply side to reduce carbon emissions and optimize energy scheduling,but also reduce energy consumption on the demand side to reduce carbon emissions,thereby reducing the purchase of quotas and"carbon tax"expenditures.Therefore,it is particularly important to analyze the carbon emission process in the whole process of production and operation of key emission reduction enterprises.However,in the process of analyzing the carbon emissions of key emission reduction enterprises,key emission reduction enterprises not only have the problems of unknown sources of large amounts of carbon emissions,unknown influencing factors,and unknown whether the influencing factors are interrelated,The carbon-associated data of enterprise equipment,primarily including coal,electricity,natural gas,and other energy data,contains a vast amount of anomalous data.Moreover,the different characteristics and sampling frequencies of various energy data categories also pose challenges to the research.In addition,in industrial production,affected by external factors,energy supply and price fluctuate frequently,and energy system load and new energy fluctuation are also problems that need to be solved for multi-energy optimization.Therefore,it is difficult for key emission reduction enterprises to carry out multi-energy optimization scheduling with carbon emission indicators as constraints,thus failing to achieve profit maximization.To solve the above problems,this paper proposes a multi-energy optimization control strategy for key emission reduction enterprises based on the carbon correlation system framework,and maximizes the output profit of enterprises through multi-energy optimization control with enterprise carbon emissions as constraints.The main work of this paper is as follows:(1)Aiming at the problems of unclear influencing factors of carbon emissions in the whole process of production and operation of key emission reduction enterprises and unclear relationship between influencing factors of carbon emissions,based on grey correlation analysis and principal component analysis methods,a framework for the correlation between equipment and carbon emissions in emission control enterprises is constructed.Through this framework,the carbon related data included in the equipment can be determined.(2)Aiming at the problems of massive abnormal data in the multi-energy consumption data of enterprises and different characteristics and collection frequency of different categories of energy data,this paper proposes a prediction model based on wavelet decomposition and reconstruction,and successfully applies it to the scenario of steel enterprises.The effectiveness and accuracy of the algorithm are verified by experiments.(3)Aiming at the problem of difficulty in carrying out multi-energy optimization scheduling with carbon emission indicators as constraints and meeting the production requirements,this paper proposes a comprehensive multi-energy optimization control strategy,and solves the optimal solution of multi-energy control strategy of key emission reduction enterprises in the time domain based on particle swarm algorithm,and applies the multi-energy optimization control strategy to the scenario of steel enterprises.The effectiveness and feasibility of the scheme are verified by experiments.更多还原