This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount ...This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption;be related to a standard;be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 percent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.展开更多
Arte S坐落在峰峦起伏的甘密山和槟城海峡之间。用主创建筑师斯蒂芬.平博理和林雯慧的话说,"塔楼流动形态的设计灵感来源于槟榔屿壮观的地貌"——高层公寓的外形和结构与甘密山上升的陡坡和槟城海岸线形成了戏剧化的关系,两...Arte S坐落在峰峦起伏的甘密山和槟城海峡之间。用主创建筑师斯蒂芬.平博理和林雯慧的话说,"塔楼流动形态的设计灵感来源于槟榔屿壮观的地貌"——高层公寓的外形和结构与甘密山上升的陡坡和槟城海岸线形成了戏剧化的关系,两座塔楼和裙房通过阳台,露台和游泳池之间的优美曲线相连接,进而产生城市意义上的社区界面感。这里,山地景观被诠释为一系列类似于台阶的层状平面,与人们长期居住在山岭地区的生活方式相呼应。设计的原则是一种基于地形和气候的形态策略。展开更多
This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand...This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.展开更多
文摘This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption;be related to a standard;be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 percent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.
文摘This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.
