王俐英, 宋美琴, 董厚琦, 方程, 曾鸣. 基于系统动力学的能源大数据生态系统演化发展研究[J]. 华北电力大学学报(自然科学版), 2023, 50(5): 87-96,104.
引用本文: 王俐英, 宋美琴, 董厚琦, 方程, 曾鸣. 基于系统动力学的能源大数据生态系统演化发展研究[J]. 华北电力大学学报(自然科学版), 2023, 50(5): 87-96,104.
WANG Liying, SONG Meiqin, DONG Houqi, FANG Cheng, ZENG Ming. Evolution and Development of Energy Big Data Ecosystem Based on System Dynamics[J]. Journal of North China Electric Power University, 2023, 50(5): 87-96,104.
Citation: WANG Liying, SONG Meiqin, DONG Houqi, FANG Cheng, ZENG Ming. Evolution and Development of Energy Big Data Ecosystem Based on System Dynamics[J]. Journal of North China Electric Power University, 2023, 50(5): 87-96,104.

基于系统动力学的能源大数据生态系统演化发展研究

Evolution and Development of Energy Big Data Ecosystem Based on System Dynamics

  • 摘要: 以宏观系统角度研究能源大数据生态系统发展的影响因素,分析能源大数据生态系统的内涵和架构,建立了能源大数据生态系统演化发展的系统动力学模型,并运用Vensim软件进行模拟仿真验证了模型的有效性,分析了影响能源大数据生态系统演化发展的关键因素。研究结果表明,影响能源大数据生态系统发展的最关键因素为消费趋势影响因子,其次为技术研发投入因子和技术升级需求,最后为财政投入因子、环境影响因子和法律法规政策投入因子。

     

    Abstract: In this paper, we studied the influencing factors of the energy big data ecosystem development from a macro-systematic perspective and analyzed the connotation and architecture of the energy big data ecosystem. We established a system dynamics model for the evolution and development of energy big data ecosystem and used Vensim software to carry out simulation and verify the validity of the model to analyze the key factors affecting the evolution and development of the energy big data ecosystem. The research results show that the most critical factor affecting the development of the energy big data ecosystem is the consumption trend impact factor, followed by the technology R&D input factor and technology upgrade demand, and finally the financial input factor, environmental impact factor and laws, regulations and policy input factors.

     

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