新能源风电发展预测与评价模型研究
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摘要
进入21世纪,能源安全和环境保护已成为全球化的问题。我国政府高度重视发展可再生能源,将其作为缓解能源供应矛盾、优化能源结构、减少温室气体排放和应对气候变化的重要措施,提出明确的发展目标和相应的激励政策,鼓励新能源的发展。而且明确“十二五”新能源产业发展重点是加快提高风电在能源供应中的比重,我国新能源风电产业从起步到大规模发展呈跳跃式前进,其开发利用过程也呈现多学科交叉的特点,因而需要对影响产业发展相关的技术、人才等关键因素进行研究,才能确保新能源风电产业的可持续健康发展。
新能源风电产业持续稳定发展,对技术进步提出了更高的要求,而技术进步与创新最终需要强有力的技术人才支撑。另一方面技术人才的技术水平不断提升,也会促进产业技术进步。因此,根据新能源风电产业发展的要求,进行新能源风电装机容量、发电负荷、技术人才需求、技术贡献率、技术进步程度等预测与评价研究,成为新能源风电产业发展重要支撑点。
本文就新能源风电发展中相关预测与评价进行了理论研究和实证分析,主要研究内容如下：
(1)在对风电发展和技术进步现状与趋势分析的基础上,提出了基于生产函数法新能源产业技术进步贡献率评价模型；基于要素投入分析方法构建了技术人才技术进步贡献率模型；结合技术人才发展规律,基于因子分析方法提出了新能源技术人才技术进步程度评价模型,以促进技术进步。
(2)在对时间序列分析、灰色理论等相关预测理论分析和我国新能源产业发展规律研究的基础上,提出基于灰色理论新能源风电装机容量预测,在此基础上,考虑技术进步因素,提出基于灰色理论新能源人均装机容量预测,并以欧盟风能发展数据和就业人数对模型进行了验证。
(3)研究了新能源产业风电发展环境下的电力负荷预测模型,建立了基于优选组合的风电负荷预测模型,将时间序列预测模型,马尔可夫预测模型和灰色预测模型分别进行风电负荷的预测,用最优权组合模型将三种方法得到的预测结果进行组合,得到了很好的预测结果。并且对于其他新能源的负荷预测具有重要的参考性。
(4)根据新能源风电产业开发利用过程技术要求呈现多学科交叉特点,在传统人才结构的基础上,增加了技术人才载体类型、专业细分研究方向,提出了技术人才结构模型。并以专业细分研究方向为切入点,提出了技术人才结构聚类分析模型；基于贝叶斯网络分类器构建了新数据归类模型,在此基础上采取多维度复合方法对新能源产业技术人才结构进行分析。
(5)在对新能源产业产业发展中技术人才供给因素分析的基础上,提出了基于马尔可夫链和神经网络优化的技术人才供给预测模型,为新能源技术人才供给预测提供了理论方法支撑。
(6)根据风电装机容量和电力负荷预测结果,从制度体系建设一系列的政策建议；根据风电技术人才供需预测分析,提出了风电技术人才培养数量建议,并从人才发展角度提出了一系列的培养与发展建议,为新能源风电的持续健康发展提供政策参考。
The issue of energy security and environment protection has become globalization problems in the21century. Our government pays high attention to the development of renewable energy and makes it an important measure to ease the tension of energy supply, optimize energy structure, reduce greenhouse gas emission and address climate change. The specific goals of development and relevant incentive policies are put forward to encourage the development of renewable energy, and it is also clarified that the12th Five-Year Plan of new energy industry development is mainly focusing on increasing the proportion of wind power in the new energy supply, popularizing the diversification utilization of biomass energy, comprehensively promoting the solar thermal utilization, and improving the economic and market competitiveness of solar power continuously.
The rapid development of the new energy industry has made remarkable achievements, with the measures of core technology introduction and independent research and development, technologies such as wind, solar, biomass are also developing steadily. As China's new energy industry is leaping forward from the start, the characteristics of multi-crossed disciplines are emerging markedly in the whole process, thus the research of key factors which affect the industry development such as technologies and talents are required to ensure the continuous and healthy development.
The sustainable development of the new energy industry makes a higher demand on technical progress. On one hand the technical progress and innovation will eventually requires a strong support of talents; on the other hand as the talents' technical level rising, the industrial technology is promoting. However the basic technology research and development is still a weak link which not only affects the ability of independent innovation, but also imposes limitation on the absorption capacity of introduced core technologies, which seriously constrained the quality and competitiveness of China's new energy products.
Therefore, according to the requirements of new energy industrial development, the research is mainly focusing on the prediction and evaluation of new energy installed capacity, generated energy, technology talents demand, technical contribution rate, technical progress rate, etc, and becoming an important support of new energy industry development.
This article conducts a theoretical and empirical analysis of related prediction and evaluation. The main contents are as follows:
(1)Based on the new energy industry development trend and technological progress analysis, this article puts forward the prediction model of contribution rate of technological progress based on the Production Function Method; the technical talent contribution rate model of technological progress based on Factor Input Analysis; the evaluation model of technical progress rate of technical talents based on Factor Analysis Method combined with the law of technical talents development, in order to promote technical progress.
(2) According to the relevant prediction analysis of time series, gray theory, etc, as well as research on the laws of development in new energy industries, the article proposes new energy installed capacity prediction based on grey model and on this basis, also considering about the factor of technology progress, the technical talents demand prediction of new energy per capital installed capacity are put forward based on GM (1,1), which verifies with data in wind power development and corresponding employment of EU, showing that the model has high prediction precision. The model predicts the quantity of technical talents in wind power industry, and has application value in the extension of other new energy types.
(3) It researches power load forecasting model in the new energy industry development environment. The wind power forecasting be as a research object representatively. A preferred combination of wind power load forecasting model has been built in the paper, it combines the time series forecasting model, Markov prediction model and the gray prediction model for wind power load forecast with preferred combination model for prediction. With the new model, it can get a good forecasting result and the method can be consulted for other new energy power load forecasting.
(4) According to the characteristics of multi-crossed disciplines required by the technology in the process of development and utilization of new energy industry, the carrier types of technical talents and subdivision of specialties are set on the basis of traditional talent structure model, and technical talent structure model are put forward. Furthermore, the article takes subdivision of specialties as a starting point and proposes the cluster analysis model of technical talent structure; constructs a new data classification model based on Bayesian Network Classifier, and on these basis, a multi-dimensional composite method is adopted to analyze the talent structure.
(5) According to the analysis of technical talents supply factors in the process of development and utilization of new energy industry, the prediction model of technical talent supply based on Markov Chain and Neural Network Optimization is proposed, which provides a theoretical support for the new energy technical talent prediction.
(6) According to the analysis results of wind power installed capacity and power load forecasting and wind power technology talents demand forecast, supply structure, this article puts forward a series of policy suggestions from the system and talents development, in order to make policy suggestions for the new wind energy to the sustained and healthy development.
新能源风电产业持续稳定发展,对技术进步提出了更高的要求,而技术进步与创新最终需要强有力的技术人才支撑。另一方面技术人才的技术水平不断提升,也会促进产业技术进步。因此,根据新能源风电产业发展的要求,进行新能源风电装机容量、发电负荷、技术人才需求、技术贡献率、技术进步程度等预测与评价研究,成为新能源风电产业发展重要支撑点。
本文就新能源风电发展中相关预测与评价进行了理论研究和实证分析,主要研究内容如下：
(1)在对风电发展和技术进步现状与趋势分析的基础上,提出了基于生产函数法新能源产业技术进步贡献率评价模型；基于要素投入分析方法构建了技术人才技术进步贡献率模型；结合技术人才发展规律,基于因子分析方法提出了新能源技术人才技术进步程度评价模型,以促进技术进步。
(2)在对时间序列分析、灰色理论等相关预测理论分析和我国新能源产业发展规律研究的基础上,提出基于灰色理论新能源风电装机容量预测,在此基础上,考虑技术进步因素,提出基于灰色理论新能源人均装机容量预测,并以欧盟风能发展数据和就业人数对模型进行了验证。
(3)研究了新能源产业风电发展环境下的电力负荷预测模型,建立了基于优选组合的风电负荷预测模型,将时间序列预测模型,马尔可夫预测模型和灰色预测模型分别进行风电负荷的预测,用最优权组合模型将三种方法得到的预测结果进行组合,得到了很好的预测结果。并且对于其他新能源的负荷预测具有重要的参考性。
(4)根据新能源风电产业开发利用过程技术要求呈现多学科交叉特点,在传统人才结构的基础上,增加了技术人才载体类型、专业细分研究方向,提出了技术人才结构模型。并以专业细分研究方向为切入点,提出了技术人才结构聚类分析模型；基于贝叶斯网络分类器构建了新数据归类模型,在此基础上采取多维度复合方法对新能源产业技术人才结构进行分析。
(5)在对新能源产业产业发展中技术人才供给因素分析的基础上,提出了基于马尔可夫链和神经网络优化的技术人才供给预测模型,为新能源技术人才供给预测提供了理论方法支撑。
(6)根据风电装机容量和电力负荷预测结果,从制度体系建设一系列的政策建议；根据风电技术人才供需预测分析,提出了风电技术人才培养数量建议,并从人才发展角度提出了一系列的培养与发展建议,为新能源风电的持续健康发展提供政策参考。
The issue of energy security and environment protection has become globalization problems in the21century. Our government pays high attention to the development of renewable energy and makes it an important measure to ease the tension of energy supply, optimize energy structure, reduce greenhouse gas emission and address climate change. The specific goals of development and relevant incentive policies are put forward to encourage the development of renewable energy, and it is also clarified that the12th Five-Year Plan of new energy industry development is mainly focusing on increasing the proportion of wind power in the new energy supply, popularizing the diversification utilization of biomass energy, comprehensively promoting the solar thermal utilization, and improving the economic and market competitiveness of solar power continuously.
The rapid development of the new energy industry has made remarkable achievements, with the measures of core technology introduction and independent research and development, technologies such as wind, solar, biomass are also developing steadily. As China's new energy industry is leaping forward from the start, the characteristics of multi-crossed disciplines are emerging markedly in the whole process, thus the research of key factors which affect the industry development such as technologies and talents are required to ensure the continuous and healthy development.
The sustainable development of the new energy industry makes a higher demand on technical progress. On one hand the technical progress and innovation will eventually requires a strong support of talents; on the other hand as the talents' technical level rising, the industrial technology is promoting. However the basic technology research and development is still a weak link which not only affects the ability of independent innovation, but also imposes limitation on the absorption capacity of introduced core technologies, which seriously constrained the quality and competitiveness of China's new energy products.
Therefore, according to the requirements of new energy industrial development, the research is mainly focusing on the prediction and evaluation of new energy installed capacity, generated energy, technology talents demand, technical contribution rate, technical progress rate, etc, and becoming an important support of new energy industry development.
This article conducts a theoretical and empirical analysis of related prediction and evaluation. The main contents are as follows:
(1)Based on the new energy industry development trend and technological progress analysis, this article puts forward the prediction model of contribution rate of technological progress based on the Production Function Method; the technical talent contribution rate model of technological progress based on Factor Input Analysis; the evaluation model of technical progress rate of technical talents based on Factor Analysis Method combined with the law of technical talents development, in order to promote technical progress.
(2) According to the relevant prediction analysis of time series, gray theory, etc, as well as research on the laws of development in new energy industries, the article proposes new energy installed capacity prediction based on grey model and on this basis, also considering about the factor of technology progress, the technical talents demand prediction of new energy per capital installed capacity are put forward based on GM (1,1), which verifies with data in wind power development and corresponding employment of EU, showing that the model has high prediction precision. The model predicts the quantity of technical talents in wind power industry, and has application value in the extension of other new energy types.
(3) It researches power load forecasting model in the new energy industry development environment. The wind power forecasting be as a research object representatively. A preferred combination of wind power load forecasting model has been built in the paper, it combines the time series forecasting model, Markov prediction model and the gray prediction model for wind power load forecast with preferred combination model for prediction. With the new model, it can get a good forecasting result and the method can be consulted for other new energy power load forecasting.
(4) According to the characteristics of multi-crossed disciplines required by the technology in the process of development and utilization of new energy industry, the carrier types of technical talents and subdivision of specialties are set on the basis of traditional talent structure model, and technical talent structure model are put forward. Furthermore, the article takes subdivision of specialties as a starting point and proposes the cluster analysis model of technical talent structure; constructs a new data classification model based on Bayesian Network Classifier, and on these basis, a multi-dimensional composite method is adopted to analyze the talent structure.
(5) According to the analysis of technical talents supply factors in the process of development and utilization of new energy industry, the prediction model of technical talent supply based on Markov Chain and Neural Network Optimization is proposed, which provides a theoretical support for the new energy technical talent prediction.
(6) According to the analysis results of wind power installed capacity and power load forecasting and wind power technology talents demand forecast, supply structure, this article puts forward a series of policy suggestions from the system and talents development, in order to make policy suggestions for the new wind energy to the sustained and healthy development.
引文
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