期刊文献+

用户多能源选择模型的构建与验证 被引量:1

An agent based simulation for the adoption behavior of multi-energy
下载PDF
导出
摘要 在NETLOGO平台下构建了用户在不同条件下对电能、太阳能、天然气3种能源选择的多智能体仿真模型。模型中,每一种能源是否能被用户选择将取决于该种能源跟其它几种能源使用性价比的比对结果。性价比所考虑的因素包括:能源自身属性因素、用户对不同种能源进行自主选择时受到的邻居影响因素、政府宏观调控因素、地域因素、大众选择倾向心理因素和用户自身经济条件因素。模型构建的技术重点在于如何能够使上述几种因素对用户进行能源选择时的影响得以合理地体现。最后,通过模型中3组重要参数取值的不同设置,对模拟结果的合理性与可信度进行了验证。 In this paper,we develop an agent-based model via NETLOGO in order to simulate and analyze the effect of multi scenarios on the adoption behavior of electric energy, solar power and natural gas. In our modeling framework, the adoption behavior of an energy will be influenced by it's value proposition in comparison to the other available energies. The value proposition includes the energy attributes,governmenCs policies, regional factors,mass psychological factors and consumers' economic condition. In this model, we mainly focus on how to make our model reflect the real situation. Finally,different value simulation that demo'nstrate the effect of important parameters are presented.
出处 《电子测量技术》 2013年第1期8-12,32,共6页 Electronic Measurement Technology
关键词 电能 太阳能 天然气 NETLOGO 多智能体仿真模拟 electric energy solar power natural gas NETI.OGO multi-agent-simulation
  • 相关文献

参考文献11

  • 1李克欣.中国低碳城市发展研究报告[M].郑州:河南大学出版社,2012:211-232.
  • 2周洪伟,罗建,吴英杰,王韫.低电压太阳能供电系统设计[J].电子测量技术,2011,34(2):18-21. 被引量:22
  • 3BASS F M, JAIN D, KRISHNAN T. Modeling the marketing-mix influence in new-product diffusion [M]. London, 2000 : 99-122.
  • 4KIESLING E, GUNTHER M , STUMMER C et al. Agent-based simulation of innovation diffusion: a review[J]. CEJOR, 2012,20 : 183-230.
  • 5ROSANNA G. Uses of agent-based modeling in innovation/new product development research [J]. Journal of Production Innovation Management, 2005, 22(5):380-398.
  • 6MAT G, NAKAMORI Y. Agent-based modeling on teehnologieal innovation as an evolutionary process[J]. European Journal of Operational Research, 2005,166 (3): 741-755.
  • 7VEIT D J, WEIDLICH A. Simulating the dynamics in two-settlement electricity markets via an agent-based approach [J]. International Journal of Management Science and Engineering Management, 2006,1 (2) : 83-97.
  • 8ZHANG T, NUTTALL W J. Evaluating government' s policies on promoting smart metering diffusion in retail electricity markets via agent-based simulation[J]. Journal of Product Innovation Management , 2011,28 : 169-186.
  • 9SHINDE A, HAGHNEVIS M. An agent based simulation and data mining framework for scenario analysis of technology products [EB/OL]. 2011, Retrievedfrom Open ABM.. http://www. openabm. org/model/2290/version/1.
  • 10SKLAR. E. Net logo,a multi-agent simulation environment[J]. Artificial Life,2011,13(3) :303-311.

二级参考文献11

共引文献21

同被引文献16

  • 1SARDIANOU E, GENOUDI P. Which factors affect the willingness of consumers to adopt renewable energies? [J]. Renewable Energy,2013(57) : 1-4.
  • 2ZHANG X, SHEN L, CHAN S Y. The diffusion of solar energy use in HK: What are the barriers? [J]. Energy Policy, 2012, (41) : 241-249.
  • 3MICHELSEN C C, MADLENER R. Motivational factors influencing the homeowners'decisions between residential heating systems: An empirical analysis for Germany[J]. Energy Policy, 2013,57 : 221-233.
  • 4DELRE S A,JAGER W,BIJMOLT T H A,et al. Will it spread or not? The effects of social influences and network topology on innovation diffusion[J]. Journal of Product Innovation Management, 2010,27 (2) : 267- 282.
  • 5BASS F M, JAIN D, KRISHNAN T. Modeling the marketing-mix influence in new-product diffusion [M]. Kluwer Academic Publishers: Boston, MA, 2000.
  • 6KIESLING E, GUNTHER M, STUMMER C, et al. Agent-based simulation of innovation diffusion: a review[J]. Central European Journal of Operations Research,2012,20(2) : 183-230.
  • 7SHINDE A, HAGHNEVIS M. An agent based simulation and data mining framework for scenario analysis of technoogy products [J]. 2011, Retrieved from Open ABM. http://www, openabm, org/model/ 2290 /version/1,2010.
  • 8VEIT D J, WEIDLICH A, YAO J, et al. Simulating the dynamics in two-settlement electricity markets via an agent-based approach[J]. International Journal of Management Science and Engineering Management, 2006,1(2) : 83-97.
  • 9ZHANG T, NUTTALL W J. Evaluating Government's Policies on Promoting Smart Metering Diffusion in Retail Electricity Markets via Agent - Based Simulation [ J ]. Journal of Product Innovation Management, 2011,28 (2) : 169-186.
  • 10FISHBURN P C. Utility theory for decision making[R]. Research Analysis Corp Mclean va, 1970.

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部