Energy Efficiency最新文献

This paper investigates the dynamics surrounding energy efficiency measures in building renovation projects to understand how energy issues are dealt with at planning and design meetings for building renovations. Through a comparative analysis of case studies of residential building renovation projects in Sweden and Denmark, document studies, observations, and interviews were conducted. The study revealed barriers hindering the effective implementation of energy efficiency practices and discussed how these can be overcome. Despite a growing recognition of the importance of energy issues, professionals often prioritise design aspects and technical installations over energy saving or efficiency. Conventional renovation practices limit the adoption of more innovative or advanced energy-efficient solutions. Financial constraints and a lack of focus on energy performance were significant barriers to the implementation of more progressive measures. Energy calculations as well as energy consultants are not given space and time at the project meetings. Clear guidance and alternative financing mechanisms are crucial for overcoming these hurdles and promoting sustainable building practices.

The Non-Intrusive Load Monitoring (NILM) technique has emerged as an efficient technique for conserving power and enhancing energy efficiency in residential buildings. This paper introduces a NILM disaggregation framework based on the multi-target regression approach, which is particularly suitable for real-time energy disaggregation. For this purpose, this work proposes a new Parallel Hybrid CNN-GRU (PHCNN-GRU) deep learning model for NILM disaggregation tasks. This technique takes advantage of the ability of Convolutional Neural Networks (CNN) to efficiently process spatial data and the excellent capability of Gated Recurrent Units (GRU) to process complex time-series data, due to their ability to retain memory of prior inputs. The proposed model has been tested and evaluated using two low-frequency benchmark databases: the UK-DALE database and the AMPds database. The experimental results demonstrate the effectiveness of the proposed model for energy disaggregation. Specifically, when using the UK-DALE database, the proposed model achieves an overall F1-score of 86.86% and an estimation accuracy of 87.16%. Moreover, when utilizing the AMPds database, the proposed model achieves an overall F1-score of 94.21% and an estimation accuracy of 94.13%. Furthermore, to better assess the performance of the proposed model, a noise signal was added to the input data. The obtained results indicate the effectiveness and robustness of the proposed model, even in the presence of noise.

This paper presents the configuration and performance of a Low Enthalpy Geothermal System successfully installed and utilized in the Mediterranean climate zone. Additionally, it examines the performance of different types of Ground Heat Exchangers (GHE), all installed in the same System. The Ground Source Heat Pump (GSHP) of the system consists of vertical ground heat exchangers (GHEs) in five different configurations, one double helicoidal coil in a well and an open loop (well) system. The entire system is constantly monitored by a Building Management System (BMS) that records the energy, volume flow, incoming and outgoing temperature at critical points of the system. Based on the recorded values, the performance of the System was analyzed in a heating and a cooling working mode, after examining the power flows in and out from critical points of the System. Results show higher heat exchange values inside the open well, both in heating and cooling mode suggesting the usage of this type of GHE, where applicable. Additionally, the electric power consumed by the chillers which are the largest electricity consumers within the System, is approximately five times lower than the power placed in the building by the Geothermal System (SCOP between 4.5 and 5). In terms of primary energy savings, we can say with confidence the GSHP systems working under Mediterranean climate zone conditions, can be consider as high efficiency solutions, verifying the theoretical efficiency given by the manufacturer of the GSHP.

The full penetration of electric vehicle (EV) is the support for China's dual carbon goal of decarbonizing urban transportation. However, the inadequate layout of EV service facilities, especially the battery swapping station network (BSSN), has hindered the development of EV in cities and the promotion of decarbonization of urban transportation. Therefore, in this paper, a novel BSSN two-stage layout model for EV is proposed by combining the characteristics of urban road net. At the first stage, a comprehensive utility model is constructed to select the candidate site nodes of BSSN by combining the node characteristics of urban road net based on Social Network Analysis (SNA). At the second stage, a layout model of BSSN is proposed to quantify the battery swapping demand and provide the optimal solution of BSSN, based on the comprehensive utility and the cost objective of the battery swapping station (BSS). Finally, the BSSN optimal solution is provided based on the layout model to cover the swapping demand within the Fourth Ring Road of Beijing as a case. In the case study, the consideration of multi-objective is proved to be effective. The optimal service radius for BSS is 5-7 km and 399,127.2t carbon emission reductions that can be generated based on this plan. In addition, the sensitivity analysis of BSS service radius, minimum station number and EV scale is carried out. The layout model of BSSN introduces comprehensive utility into the road net and optimizes the location of BSSN from the perspective of urban planning, and it is of significance to the planning of urban transportation.

Net Zero Energy Building (NZEB) is a concept that promotes the reduction of energy consumption in buildings by applying energy efficiency measures. The energy supply for the remaining demand should only come from sources with low CO2 emissions. Despite abundant research on NZEB for new buildings, only a small number of studies address its application to those already existing. This study aims to bridge this research gap by organizing the proposed methods to transform existing buildings into NZEB. The research method is a systematic literature review covering the methodological development and the application of the concept. We conducted a bibliometric and Scientometric analysis of 117 articles and a content analysis of 48 of them. The results highlighted that the methods identified follow similar stages: (i) planning, (ii) data collection, (iii) pre-design, (iv) design, and (v) delivery. The sub-stage with the highest frequency (88%) was the presentation of the efficiency measure package, making it an essential step in the transformation process. The review did not find specific topics, such as equipment listing and performance, occupant engagement, and charrette design. Finally, the study established guidelines for future research.

This study examines how stable public acceptability judgements towards novel and established energy technologies are over time, which is important to consider in decision-making about the transition to low-carbon and energy-efficient systems. We conducted two longitudinal survey experiments, one with a convenience sample of students and another with a representative sample of Dutch adults, to explore the extent to which acceptability judgements towards energy technologies are stable over time and to examine potential factors influencing stability of acceptability judgements, including technology novelty, people’s knowledge about a technology, ambivalence towards a technology, perceived importance of the technology, and personal values. We also tested if stability affects citizenship behaviors (e.g., signing petitions, supporting political candidates) towards energy technologies. As expected, acceptability judgements are less stable for novel (i.e., geothermal energy and CCS) than for established technologies (i.e., wind and nuclear energy). Moreover, the more ambivalent people felt towards a technology and the less an energy technology was personally important to them, the less stable their acceptability judgements. Yet, neither knowledge nor personal values were significantly related to stability of acceptability judgements. Interestingly, acceptability judgements were associated with citizenship behavior regardless of how stable acceptability judgements were. We discuss the theoretical and practical implications of our findings.

Demand-side management (DSM) programs aiming to both reduce and render household consumption more flexible are becoming increasingly essential due to ongoing energy crises and the growing integration of renewable energy into energy production. The active involvement of households and energy users is crucial to fully unlock the potential of DSM programs. As this paper demonstrates, despite more than thirty years of feminist scholarly work focusing on the home as an important site of the production of gender inequality, few of these insights have been taken into account by DSM designers. Additionally, we note a broader pattern concerning gaps in knowledge regarding the diverse perspectives of energy users and their domestic contexts, all of which create obstacles to successful rollout and scalability. This paper uses the concepts of the social license to automate and intersectionality to analyze the existing literature on DSM programs. We find that three primary barriers in household DSM programs have been addressed: 1) there is an unresolved tension between DSM technology being perceived as a masculine domain and the home as a feminine domain; 2) low-income households face challenges in accessing the technology needed to enable both flexibility and savings; and 3) disparities in opportunities for youth and the elderly to participate in DSM programs are insufficiently considered. Based on these findings we argue that user diversity—not only conceived of as separate identity category variables but also as implicating overlapping and possible mutually reinforcing marginalizations– is needed to form a starting point in DSM program design for fair and scalable solutions.

The transportation sector is one of the main consumers of energy produced in the world and is responsible for 40% of global emissions, which shows the urgency of reducing energy consumption by improving Energy Efficiency (EE) for transportation. This research aims to develop an Urban Mobility Energy Efficiency Index (UMEEI). The model is based on the ASI (Avoid-Shift-Improve) approach, which is anchored in three EE pillars: systemic efficiency, travel efficiency, and vehicle efficiency. The applicability analysis was carried out through a case study in the city of São Paulo (SP), Brazil, presenting the Urban Mobility Energy Efficiency Index (UMEEI) for this city. The model consisted of a hierarchy of criteria with 7 themes, 14 initiatives, and 29 attributes. The multi-criteria decision analysis method was used, using the Analytical Hierarchy Process (AHP). The Energy Efficiency in Urban Mobility (EEUM) model for São Paulo achieved an UMEEI of 0.542. The research contributed to the elaboration of a multidisciplinary Evaluation Model and the development of a UMEEI, which can be used as a control indicator for urban mobility actions. In practical terms, the research made it possible to pinpoint the priority initiatives that should be the focus of improvement policies in São Paulo. As it is a flexible tool, that allows new criteria to be removed or incorporated, it can be adapted for municipalities of different sizes.

Improving energy consumption efficiency has the potential to reduce poverty in addition to reducing greenhouse gas emissions. However, very little is known about the impact of electricity consumption efficiency on poverty. Using data from a household survey, we estimate electricity consumption efficiency, multidimensional poverty, and consumption poverty among Ghanaian households. We then use an instrumental variable and probit models to estimate the impact of electricity consumption efficiency on multidimensional and consumption poverty respectively. The results indicate that a percentage increase in electricity consumption efficiency reduces multidimensional poverty by approximately 35.7% and 16.5% when the extreme and national poverty lines are considered respectively. Improvement in electricity consumption efficiency reduces extreme consumption poverty by about 9.1% but does not significantly impact consumption poverty measured by the national poverty line. This shows that multidimensional poverty can be highly reduced by improvement in household electricity consumption compared to consumption poverty. Households willing to take the risk of buying new electrical appliances significantly reduce the probability of being both multidimensional and consumption poverty. Higher educational qualifications reduce both consumption and multidimensional poverty. We recommend government to strengthen policy choices on demand-side management of electricity through the enhancement of energy efficiency programmes such as the Efficiency Standards and Labelling Programme through turn-in and rebate schemes that cover cooling appliances and develop regulations to cover other appliances. Efforts should also focus on improving access to education, roll-out mass information and training programmes on electricity consumption efficiency and conservation measures and encouraging households to take the risk to buy new electrical appliances. The government could also incorporate efficiency measures in poverty alleviation programmes like the Livelihood Empowerment Against Poverty in Ghana.

Mechanical ventilation plays an important role in an increasingly energy-efficient building stock by promoting a good indoor air quality, occupant comfort and building protection. It can also reduce energy losses due to suboptimal ventilation behavior during the cold season and increase the overall energy efficiency of the building. However, the effectiveness of mechanical ventilation systems is dependent on appropriate user behavior. Discrepancies between technical requirements and actual user behavior in terms of adequate ventilation system use have been observed in empirical research. This can decrease energy efficiency and potentially negatively impact indoor air quality. The aim of this research was to explore factors that predict occupants’ attitudes towards their ventilation system and their satisfaction with it. We examined self-reported natural ventilation practices of occupants as well as predictors of technology acceptance and user satisfaction with mechanical ventilation. Predictors of these two dependent variables differed slightly in our sample. Perceived usefulness and perceived ease of use of the ventilation system predicted both attitudes and user satisfaction. In addition, user satisfaction was significantly associated with the perceived cleanliness of the ventilation system. Even though stated as a relevant preference for ventilation systems in our pre-study, satisfaction with control options was not related to attitudes or user satisfaction, neither was the subjective importance of the noise level and energy efficiency. We therefore conclude that it is essential to emphasize the goals and benefits of mechanical ventilation systems, hence their usefulness for comfort, health, building protection, and energy efficiency. Furthermore, it seems crucial to provide detailed explanations on the correct operation of the system to maintain its effectiveness. Ensuring the system’s understandability and ease of use are also vital for aligning technology requirements with user needs. Finally, to increase user satisfaction it may be critical to place importance on the filtering capabilities and cleanliness of the ventilation systems. Highlighting these aspects and explaining what is required of users to maintain hygienic environments in manuals and during installation could be a promising means of ensuring adequate long-term operation by occupants.