智能电网低碳效益关键指标选取与评价模型研究
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摘要
近年来,为应对全球气候变化,实现经济、社会与环境的可持续发展,世界各国相继把发展低碳经济作为国家核心战略。作为我国CO2排放大户,电力行业亟需转变发展模式,促进电力系统低碳化发展。智能电网能够支持各种低碳技术的引入,进而带来碳减排效益。因此,评价我国智能电网带来的低碳效益,对促进我国智能电网建设、落实国家碳减排任务、推动低碳经济发展具有重要意义。本文以智能电网低碳效益为研究对象,对我国智能电网低碳效益形成机理进行了分析论述,对智能电网低碳效益的关键指标进行了选取,并在静态、动态、剔除干扰因素三种情景下,构建了智能电网低碳效益的评价模型,以期为我国智能电网建设与低碳经济发展提供参考。
首先,基于智能电网低碳效益内涵,对智能电网实现低碳效益的作用机理进行了研究。结合我国国情,分析了我国智能电网的发展模式,明确了智能电网的支撑体系,并对智能电网的技术支撑体系进行了重点分析；基于我国智能电网的特点,界定了我国智能电网低碳效益的定义与内涵；在此基础上,分析了先进低碳技术对智能电网促进电力系统低碳化发展的影响机理和减排能力,确定了智能电网在发电侧、电网侧、用电侧各环节实现低碳效益的具体路径,为智能电网低碳效益关键指标选取与评价模型建立提供了研究基础。
其次,构建了结构熵-因子分析优化模型,对智能电网低碳效益关键指标进行了选取。基于我国智能电网低碳效益的实现路径,分别从发电侧、电网侧、用电侧初步选取了智能电网低碳效益评价的关键指标；在此基础上,运用熵理论和统计学原理,建立了智能电网低碳效益关键指标选取的结构熵-因子分析优化模型；基于结构熵-因子分析优化模型,利用结构熵减少了初选关键指标的不确定性,运用SPSS软件对初选关键指标进行了因子分析,以因子载荷为判据对初选关键指标进行了优化,并对指标优化结果进行了信度检验和效度检验；最终从静态评价和动态评价两个维度构建了智能电网低碳效益评价的关键指标体系,为智能电网低碳效益评价模型建立提供了框架范畴。
第三,构建了ANP-Fuzzy静态评价模型,对智能电网低碳效益水平进行了静态评价研究。从智能电网低碳效益静态评价的特点入手,以智能电网低碳效益静态评价的关键指标体系为框架范畴,设计了智能电网低碳效益静态评价的总指标体系、评价等级与评价标准；在此基础上,运用网络层次分析法理论和模糊数学理论,建立了评价智能电网低碳效益水平的ANP-Fuzzy静态评价模型；基于ANP-Fuzzy静态评价模型,设计了反映静态评价指标之间相互关系的ANP网络结构和精确界定定性指标的Fuzzy多层次评价结构,运用Super Decisions软件在ANP网络结构中确定了各指标权重,运用Matlab软件在Fuzzy多层次评价结构中对智能电网低碳效益水平进行了静态评价研究。
第四,构建了SD动态评价模型,对智能电网低碳效益大小进行了动态评价研究。从智能电网低碳效益动态评价的特点入手,以智能电网低碳效益动态评价的关键指标体系为框架范畴,设计了智能电网低碳效益动态评价的因果关系环路；在此基础上,运用系统动力学理论,建立了智能电网低碳效益的SD动态评价模型；基于SD动态评价模型,结合我国电网实际和发展预期设定了模型参数,刻画了我国智能电网促进低碳发展的SD动态反馈系统,运用Vensim PLE软件在SD动态反馈系统中仿真模拟了不同情景下我国智能电网实现低碳效益的动态量化过程,对智能电网低碳效益大小进行了动态评价研究。
第五,构建了三阶段-超效率DEA评价模型,对智能电网低碳效益的投入产出效率进行了剔除环境影响因素的评价研究。从剔除环境影响因素的智能电网低碳效益评价的特点入手,在SD动态评价模型中选取了关键存量作为投入指标、选取了“CO2减排总量”作为产出指标,考虑经济增长、消费、投资等重要外在环境影响因素,建立了剔除环境影响因素的智能电网低碳效益评价指标体系;在此基础上,运用数据包络分析理论和随机理论,建立了基于三阶段-超效率DEA的剔除环境影响因素的智能电网低碳效益评价模型；基于三阶段-超效率DEA评价模型,运用Frontier4.1软件剔除了外在环境影响因素对智能电网低碳效益的投入产出效率评价的“噪声”影响,运用DEAP2.1软件对不同时点或不同区域的智能电网低碳效益投入产出效率进行了评价研究,最终运用EMS1.3软件对得分相同的有效投入产出效率进行了进一步区分评价研究。
研究结果表明,选取的智能电网低碳效益关键指标科学、合理,具有较高的信度和效度,符合我国实际和智能电网发展趋势,可以为我国智能电网低碳效益评价提供有效的指导框架；建立的智能电网低碳效益评价模型全面、有效,能够从效益水平、效益大小、效益投入产出效率不同角度反映我国智能电网的低碳效益。此外,这些评价模型均可以借助相关软件实现,操作性强,具有较高的实用价值。
For responding to the change of global climate and achieving the sustainable development of economy, society and environment, developing low-carbon economy has been taken as a national core strategy in many countries in recent years. As the main source of CO2emission in China, the power industry is required to change its development mode to promote the power system to realize the development of low-carbon as soon as possible. Smart Grid can support the introduction of various low-carbon technologies, and thus bring benefit of reducing carbon emission. Therefore, evaluating low-carbon benefit of Smart Grid is significant to promote the construction of China's Smart Grid, the implement the national task of reducing carbon emission and the development of low-carbon economy. This paper takes the low-carbon benefit of Smart Grid as its research object. In this paper, the formation mechanism of low-carbon benefit of Smart Grid is discussed, the key indicators of low-carbon benefit of Smart Grid are selected and the evaluation models of low-carbon benefit of Smart Grid are built under three scenarios of static, dynamic and eliminate interference factors in order to provide references for the construction of Smart Grid and the development of low-carbon economy in China.
Firstly, the formation mechanism of Smart Grid achieving low-carbon benefit is analyzed based on the connotation of Smart Grid's low-carbon benefit. According to the status of China, the development mode and support system of China's Smart Grid are analyzed, especially, the technology support system is discussed a key point. The definition and connotation of low-carbon benefit of Smart Grid are defined based on the characteristics of China's Smart Grid. On this basis, the influence mechanism and emission reduction capability of advanced low-carbon technologies which provide support for Smart Grid promoting the development of low-carbon power system is analyzed. The concrete paths of Smart Grid realizing low-carbon benefit on generation side, grid side and demand side are cleared, which can provide research foundation for key indicators selecting of low-carbon benefit and its evaluation models.
Secondly, the key indicators of low-carbon benefit of Smart Grid are selected based on Structure Entropy and Factor Analysis optimization model. The key indicators are selected preliminarily from generation side, grid side and demand side based on the path of low-carbon benefit of Smart Grid. On this basis, the Structure Entropy and Factor Analysis optimization model of key indicators of Smart Grid's low-carbon benefit is built by applying entropy theory and statistics principle. Based on Entropy and Factor Analysis optimization model, reduce the uncertainty of preliminary selection of key indicators by Structure Entropy, use SPSS software to analyze the factor of preliminary selection of key indicators and optimize the preliminary selection of key indicators by factor loading. Then make reliability test and validity test for the optimal indicators. At last, the key evaluation indicator system of low-carbon benefit of Smart Grid is established from two dimensions of the static evaluation and dynamic evaluation, which can provide a framework for the establishment of evaluation models of Smart Grid's low-carbon benefit.
Thirdly, the static evaluation on the level of low-carbon benefit of Smart Grid is researched based on ANP-Fuzzy static evaluation model. Considering the characteristics of static evaluation of Smart Grid's low-carbon benefit, design the overall indicator system, evaluation grades and evaluation standards of static evaluation based on the key indicator system of static evaluation of Smart Grid's low-carbon benefit. On this basis, the ANP-Fuzzy static evaluation model of low-carbon benefit of Smart Grid is built by applying analytic network process theory and fuzzy mathematics theory. Based on ANP-Fuzzy static evaluation model, design ANP network structure, which can reflect the relationships among the static evaluation indicators and Fuzzy hierarchy evaluation structure, use Super Decisions software to determine the weights of indicators in the ANP network structure and use Matlab software to static evaluate the level of low-carbon benefit of Smart Grid in the Fuzzy hierarchy evaluation structure.
Fourthly, the dynamic evaluation on the amount of low-carbon benefit of Smart Grid is researched based on SD dynamic evaluation model. Considering the characteristics of dynamic evaluation of Smart Grid's low-carbon benefit, design the causality loop of dynamic evaluation based on the key indicator system of dynamic evaluation of Smart Grid's low-carbon benefit. On this basis, the SD dynamic evaluation model of low-carbon benefit of Smart Grid is built by applying system dynamics theory. Based on SD dynamic evaluation model, set the parameters in SD model with regard to the actual and expected situations of China's power grid, describe the dynamic feedback system of Smart Grid promoting the low-carbon development in China, use Vensim PLE software to simulate the dynamic process of Smart Grid realizing low-carbon benefit under different scenarios in the dynamic feedback system and then evaluate the amount of low-carbon benefit of Smart Grid.
Finally, the evaluation on the input-output efficiency of low-carbon benefit of Smart Grid with eliminating environmental impact factors is researched based on Three-stage DEA and Super-efficiency DEA evaluation model. Considering the characteristics of evaluation of Smart Grid's low-carbon benefit with eliminating environmental impact factors, select the key stock variables in SD dynamic evaluation model as the input indicators, select the reduction of CO2emission in SD dynamic evaluation model as the output indicator and then establish the evaluation indicator system of low-carbon benefit of Smart Grid with eliminating environmental impact factors with regard to the important external environmental impact factors, such as economic growth, consumption and investment. On this basis, the evaluation model of low-carbon benefit of Smart Grid with eliminating environmental impact factors is built based on Three-stage DEA and Super-efficiency DEA by applying data envelopment analysis theory and stochastic theory. Based on Three-stage DEA and Super-efficiency DEA evaluation model, use Frontier4.1software to eliminate the noise effect of external environmental impact factors in the input-output efficiency evaluation of Smart Grid's low-carbon benefit, use DEAP2.1software to evaluate the input-output efficiency of low-carbon benefit of Smart Grid at different times or in different regions and finally use EMS1.3software to distinguish the effective input-output efficiencies further, which have the same evaluation score.
The results of the researches show that the selected key indicators of low-carbon benefit of Smart Grid are scientific and rational with high reliability and validity, and in accordance with China's actual conditions and Smart grid development trend, these indicators can provide effective guidance framework for the evaluation of Smart Grid's low-carbon benefit in China. The constructed evaluation models of low-carbon benefit of Smart Grid are comprehensive and effective. These models can reflect Smart Grid's low-carbon benefit in different views such as level, amount and input-output efficiency. Moreover, all of those evaluation models can be achieved with related software. Easy operation makes these models have a high application value.
首先,基于智能电网低碳效益内涵,对智能电网实现低碳效益的作用机理进行了研究。结合我国国情,分析了我国智能电网的发展模式,明确了智能电网的支撑体系,并对智能电网的技术支撑体系进行了重点分析；基于我国智能电网的特点,界定了我国智能电网低碳效益的定义与内涵；在此基础上,分析了先进低碳技术对智能电网促进电力系统低碳化发展的影响机理和减排能力,确定了智能电网在发电侧、电网侧、用电侧各环节实现低碳效益的具体路径,为智能电网低碳效益关键指标选取与评价模型建立提供了研究基础。
其次,构建了结构熵-因子分析优化模型,对智能电网低碳效益关键指标进行了选取。基于我国智能电网低碳效益的实现路径,分别从发电侧、电网侧、用电侧初步选取了智能电网低碳效益评价的关键指标；在此基础上,运用熵理论和统计学原理,建立了智能电网低碳效益关键指标选取的结构熵-因子分析优化模型；基于结构熵-因子分析优化模型,利用结构熵减少了初选关键指标的不确定性,运用SPSS软件对初选关键指标进行了因子分析,以因子载荷为判据对初选关键指标进行了优化,并对指标优化结果进行了信度检验和效度检验；最终从静态评价和动态评价两个维度构建了智能电网低碳效益评价的关键指标体系,为智能电网低碳效益评价模型建立提供了框架范畴。
第三,构建了ANP-Fuzzy静态评价模型,对智能电网低碳效益水平进行了静态评价研究。从智能电网低碳效益静态评价的特点入手,以智能电网低碳效益静态评价的关键指标体系为框架范畴,设计了智能电网低碳效益静态评价的总指标体系、评价等级与评价标准；在此基础上,运用网络层次分析法理论和模糊数学理论,建立了评价智能电网低碳效益水平的ANP-Fuzzy静态评价模型；基于ANP-Fuzzy静态评价模型,设计了反映静态评价指标之间相互关系的ANP网络结构和精确界定定性指标的Fuzzy多层次评价结构,运用Super Decisions软件在ANP网络结构中确定了各指标权重,运用Matlab软件在Fuzzy多层次评价结构中对智能电网低碳效益水平进行了静态评价研究。
第四,构建了SD动态评价模型,对智能电网低碳效益大小进行了动态评价研究。从智能电网低碳效益动态评价的特点入手,以智能电网低碳效益动态评价的关键指标体系为框架范畴,设计了智能电网低碳效益动态评价的因果关系环路；在此基础上,运用系统动力学理论,建立了智能电网低碳效益的SD动态评价模型；基于SD动态评价模型,结合我国电网实际和发展预期设定了模型参数,刻画了我国智能电网促进低碳发展的SD动态反馈系统,运用Vensim PLE软件在SD动态反馈系统中仿真模拟了不同情景下我国智能电网实现低碳效益的动态量化过程,对智能电网低碳效益大小进行了动态评价研究。
第五,构建了三阶段-超效率DEA评价模型,对智能电网低碳效益的投入产出效率进行了剔除环境影响因素的评价研究。从剔除环境影响因素的智能电网低碳效益评价的特点入手,在SD动态评价模型中选取了关键存量作为投入指标、选取了“CO2减排总量”作为产出指标,考虑经济增长、消费、投资等重要外在环境影响因素,建立了剔除环境影响因素的智能电网低碳效益评价指标体系;在此基础上,运用数据包络分析理论和随机理论,建立了基于三阶段-超效率DEA的剔除环境影响因素的智能电网低碳效益评价模型；基于三阶段-超效率DEA评价模型,运用Frontier4.1软件剔除了外在环境影响因素对智能电网低碳效益的投入产出效率评价的“噪声”影响,运用DEAP2.1软件对不同时点或不同区域的智能电网低碳效益投入产出效率进行了评价研究,最终运用EMS1.3软件对得分相同的有效投入产出效率进行了进一步区分评价研究。
研究结果表明,选取的智能电网低碳效益关键指标科学、合理,具有较高的信度和效度,符合我国实际和智能电网发展趋势,可以为我国智能电网低碳效益评价提供有效的指导框架；建立的智能电网低碳效益评价模型全面、有效,能够从效益水平、效益大小、效益投入产出效率不同角度反映我国智能电网的低碳效益。此外,这些评价模型均可以借助相关软件实现,操作性强,具有较高的实用价值。
For responding to the change of global climate and achieving the sustainable development of economy, society and environment, developing low-carbon economy has been taken as a national core strategy in many countries in recent years. As the main source of CO2emission in China, the power industry is required to change its development mode to promote the power system to realize the development of low-carbon as soon as possible. Smart Grid can support the introduction of various low-carbon technologies, and thus bring benefit of reducing carbon emission. Therefore, evaluating low-carbon benefit of Smart Grid is significant to promote the construction of China's Smart Grid, the implement the national task of reducing carbon emission and the development of low-carbon economy. This paper takes the low-carbon benefit of Smart Grid as its research object. In this paper, the formation mechanism of low-carbon benefit of Smart Grid is discussed, the key indicators of low-carbon benefit of Smart Grid are selected and the evaluation models of low-carbon benefit of Smart Grid are built under three scenarios of static, dynamic and eliminate interference factors in order to provide references for the construction of Smart Grid and the development of low-carbon economy in China.
Firstly, the formation mechanism of Smart Grid achieving low-carbon benefit is analyzed based on the connotation of Smart Grid's low-carbon benefit. According to the status of China, the development mode and support system of China's Smart Grid are analyzed, especially, the technology support system is discussed a key point. The definition and connotation of low-carbon benefit of Smart Grid are defined based on the characteristics of China's Smart Grid. On this basis, the influence mechanism and emission reduction capability of advanced low-carbon technologies which provide support for Smart Grid promoting the development of low-carbon power system is analyzed. The concrete paths of Smart Grid realizing low-carbon benefit on generation side, grid side and demand side are cleared, which can provide research foundation for key indicators selecting of low-carbon benefit and its evaluation models.
Secondly, the key indicators of low-carbon benefit of Smart Grid are selected based on Structure Entropy and Factor Analysis optimization model. The key indicators are selected preliminarily from generation side, grid side and demand side based on the path of low-carbon benefit of Smart Grid. On this basis, the Structure Entropy and Factor Analysis optimization model of key indicators of Smart Grid's low-carbon benefit is built by applying entropy theory and statistics principle. Based on Entropy and Factor Analysis optimization model, reduce the uncertainty of preliminary selection of key indicators by Structure Entropy, use SPSS software to analyze the factor of preliminary selection of key indicators and optimize the preliminary selection of key indicators by factor loading. Then make reliability test and validity test for the optimal indicators. At last, the key evaluation indicator system of low-carbon benefit of Smart Grid is established from two dimensions of the static evaluation and dynamic evaluation, which can provide a framework for the establishment of evaluation models of Smart Grid's low-carbon benefit.
Thirdly, the static evaluation on the level of low-carbon benefit of Smart Grid is researched based on ANP-Fuzzy static evaluation model. Considering the characteristics of static evaluation of Smart Grid's low-carbon benefit, design the overall indicator system, evaluation grades and evaluation standards of static evaluation based on the key indicator system of static evaluation of Smart Grid's low-carbon benefit. On this basis, the ANP-Fuzzy static evaluation model of low-carbon benefit of Smart Grid is built by applying analytic network process theory and fuzzy mathematics theory. Based on ANP-Fuzzy static evaluation model, design ANP network structure, which can reflect the relationships among the static evaluation indicators and Fuzzy hierarchy evaluation structure, use Super Decisions software to determine the weights of indicators in the ANP network structure and use Matlab software to static evaluate the level of low-carbon benefit of Smart Grid in the Fuzzy hierarchy evaluation structure.
Fourthly, the dynamic evaluation on the amount of low-carbon benefit of Smart Grid is researched based on SD dynamic evaluation model. Considering the characteristics of dynamic evaluation of Smart Grid's low-carbon benefit, design the causality loop of dynamic evaluation based on the key indicator system of dynamic evaluation of Smart Grid's low-carbon benefit. On this basis, the SD dynamic evaluation model of low-carbon benefit of Smart Grid is built by applying system dynamics theory. Based on SD dynamic evaluation model, set the parameters in SD model with regard to the actual and expected situations of China's power grid, describe the dynamic feedback system of Smart Grid promoting the low-carbon development in China, use Vensim PLE software to simulate the dynamic process of Smart Grid realizing low-carbon benefit under different scenarios in the dynamic feedback system and then evaluate the amount of low-carbon benefit of Smart Grid.
Finally, the evaluation on the input-output efficiency of low-carbon benefit of Smart Grid with eliminating environmental impact factors is researched based on Three-stage DEA and Super-efficiency DEA evaluation model. Considering the characteristics of evaluation of Smart Grid's low-carbon benefit with eliminating environmental impact factors, select the key stock variables in SD dynamic evaluation model as the input indicators, select the reduction of CO2emission in SD dynamic evaluation model as the output indicator and then establish the evaluation indicator system of low-carbon benefit of Smart Grid with eliminating environmental impact factors with regard to the important external environmental impact factors, such as economic growth, consumption and investment. On this basis, the evaluation model of low-carbon benefit of Smart Grid with eliminating environmental impact factors is built based on Three-stage DEA and Super-efficiency DEA by applying data envelopment analysis theory and stochastic theory. Based on Three-stage DEA and Super-efficiency DEA evaluation model, use Frontier4.1software to eliminate the noise effect of external environmental impact factors in the input-output efficiency evaluation of Smart Grid's low-carbon benefit, use DEAP2.1software to evaluate the input-output efficiency of low-carbon benefit of Smart Grid at different times or in different regions and finally use EMS1.3software to distinguish the effective input-output efficiencies further, which have the same evaluation score.
The results of the researches show that the selected key indicators of low-carbon benefit of Smart Grid are scientific and rational with high reliability and validity, and in accordance with China's actual conditions and Smart grid development trend, these indicators can provide effective guidance framework for the evaluation of Smart Grid's low-carbon benefit in China. The constructed evaluation models of low-carbon benefit of Smart Grid are comprehensive and effective. These models can reflect Smart Grid's low-carbon benefit in different views such as level, amount and input-output efficiency. Moreover, all of those evaluation models can be achieved with related software. Easy operation makes these models have a high application value.
引文
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