2017年电气论坛第10次活动——Understanding Demand Response, Smart Home Management System, and Occupants’ Energy Efficiency Behaviors through the Social-Psychological Analysis
陈建妃博士：华盛顿州立大学社会学博士，超广域弹性电力传输网络研究中心(CURENT)的研究教授和教育与多样性计划主任，田纳西大学社会学系的客座教授。研究方向：1）电力系统，可再生能源，节能行为和环境社会学领域的跨学科研究; 2）将社会心理因素和人类决策过程引入工程建模，以便更好地了解电力系统，对可再生能源技术的接受和能源问题; 3）商业建筑中的能源行为，以提高用能效率和减少碳排放; 4）向学术界、电力公司和决策者提供基本的跨学科知识。
研究成果：在CURENT负责对于公众接受智能电网技术和需求测响应的研究项目。自2014年以来，她参与了国际能源机构 (IEA),Energy in Buildings and Communities (EBC) Annex 66对影响建筑使用者用能行为的社会心理因素的调查。此外，在NSF-REC-SEES Network：Predictive Modeling Network for Sustainable Human-Building Ecosystems研究会中，带领了教育计划和社会心理分析项目。
Technology is not enough: Understanding Demand Response, Smart Home Management System, and Occupants’ Energy Efficiency Behaviors through the Social-Psychological Analysis
Improving energy efficiency behaviors requires the consideration of technology improvement and human factors. While a growing number of recent studies have focused on the improvement of energy efficiency or building technologies, little attention has been paid to a comprehensive analysis on the impact of social-psychological factors on occupants’ energy conservation and residential demand response behaviors. For example, in the context of the workplaces including commercial or industrial buildings, employees typically are not responsible for utility costs and thus have less financial motivation to keep track of and reduce energy use. Moreover, appliances and facilities are often shared among coworkers, which inhibit the development of a sense of individual responsibilities. Regarding residential demand response, a typical engineering model generally focuses on the impact of electricity price (e.g., time of use) or certain energy efficiency technology on energy saving behaviors without considering residents’ attitudes and motivations.
Gaining a deeper understanding of the social-psychological factors such as trust in utility companies, norms, energy saving attitudes, behavioral control, privacy concern, influencing energy efficiency behaviors in both public or residential buildings is especially relevant for policy and academic conversations about mitigating global climate change. Dr. Chen’s talk will address the advancement of social scientific perspectives in energy efficiency research by focusing on social-psychology theories and associated factors affecting energy behaviors in both residential and workplace settings.
Dr. Chien-fei Chen (Ph.D. in sociology, Washington State university) is a researchprofessor and director of education and diversity program at NSF-DOE funded engineering research center, Center for Ultra-wide-area Resilient Electric Energy Transmission Networks (CURENT) in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. She is also an adjunct faculty in the department of sociology. Her research interests include: 1) interdisciplinary research in the areas of power systems, renewable energy, energy conservation behaviors and environmental sociology; 2) social-psychological factors and human decision-making processes into engineering modeling to better understand power systems, and acceptance of renewable energy technology and energy issues; 3) energy behaviors in commercial buildings to improve energy efficiency and reduce carbon emissions; and 4) fundamental interdisciplinary knowledge to the research community, utility companies and policy makers.
Her publications appear in the IEEE, Building and Environment, Energy Research and Social Science, Journal of Environmental Psychology, ASHRAE, American Sociological Association, Behavior, Energy and Climate Change Conference, and so on. Currently, she leads the projects of public acceptance of power grid technologies and demand response at CURNET. Since 2014, she has involved with the investigation of social psychological factors affecting building occupant behaviors for the International Energy Agency (IEA), Energy in Buildings and Communities (EBC) Annex 66. In addition, she leads sustainability education program and social psychological analysis of energy behaviors for the NSF-REC-SEES Network: Predictive Modeling Network for Sustainable Human-Building Ecosystems (SHBE). Between 2013-2015, she has received several grant awards from National Science Foundation in the United States to conduct interdisciplinary studies regarding public acceptance of communication technology and social-psychological factors and micro-grid resilience and acceptance of grid technologies.