Energy Efficiency最新文献

This study investigates the effectiveness of an Optimal Time Recommendation model (OTR) in encouraging citizens to shift the usage of their home appliances, such as dishwasher to off-peak hours. The research was conducted at the HSB Living Lab + in Gothenburg city, involving 74 participants from diverse social groups, including students, one-person households, couples, and families with kids. The study employed a mixed-methods approach, combining surveys, interviews, and data from self-reporting QR-code or iPad-based web-interface. Participants were provided with personalised recommendations generated by the OTR model, which considered factors such as energy demand, grid load, electricity pricing and level of CO2. The recommendations aimed to assist users in identifying the optimal time slots for operating their home appliances during off-peak, motivated by the lower price, lower CO2 emission or both. Results indicated a positive response from participants across all social groups. Most participants reported an increased awareness of their energy consumption patterns and a willingness to adopt delay shifting practices. However, some frictions and obstacles to adopt shifting time of the behaviour were highlighted as well. The findings from this case study contribute to the existing knowledge on flexibility and Demand-Side Management (DSM). These findings can inform home appliances producers to increase the delay start function usability, policymakers to emphasise the eco-design of the white goods, and researchers in developing effective strategies to encourage energy conservation practices on a larger scale.

The renewable energy transition requires more flexible electricity consumption. This article follows up on Norwegian plans to achieve this through demand response and a piloting of smart home technology targeting indoor heating, which we call Smart Energy Technology (SET). Based on 17 in-depth interviews with participants in a technology pilot project, we map the work required to keep the SET system running, how it impacted electricity-consuming household practices, and analyse why use of the system varied widely among participants. We show that the system in question was too complex for other than exceptionally skilled and motivated users, who engaged in extensive “digital housekeeping”. Other users were navigating a complex Norwegian electricity market using technology they found difficult to operate. This was linked with limited system use, which lowered the energy efficiency contribution of the smart system. Smart systems and their use are highly gendered and have the potential both to challenge and reinforce gendered divisions of labour. More research into the gendered impacts of smart systems in Norway is needed. Simpler and more user-friendly systems are necessary for future pilot projects, more hands-on training for users in such pilots is required, and the daily work required to operate complex smart systems should be recognised more clearly by both smart system developers and policy makers.

In light of India's current energy crisis, it has been determined that the coal mining industry may be used to implement Demand Side Management (DSM) applications. This study explores the possibility of energy savings and reduction in energy costs associated with the installation of (Variable Speed Drives) VSDs on primary ventilation fans in below-ground coal mines. According to Ventilation-on-Demand (VOD), where air volume is changed according to demand at various time intervals, a nonlinear constraint optimization model is created to reduce energy costs and achieve better energy efficiency. To achieve accurate results at the fan's operating point, this model is also constructed to adhere to the affinity law of the fan. Tellegen's theorem and Kirchhoff's law are applied to model the ventilation system of the underground mine. The ventilation network was used to investigate energy and financial savings with various airflow scenarios. Load management is accomplished by figuring out the ideal start time for the mining schedule in accordance with the Time of Use (TOU) tariffs. A critical analysis of the Tandsi underground coal mine is presented to explain the impacts of the optimization model. The study found that implementing DSM solutions could result in a total annual energy savings of 118625 kWh, or a reduction in energy costs of USD 22995.

Automatic dishwashing is an example of a complex socio-technical system with an interplay between a variety of factors and participants, including manufacturers, technology, regulators, consumer practices, cultural norms and infrastructure. Understanding this system is a prerequisite to find the right levers to optimise it. In this context, automatic dishwashing in Australia is studied by modelling the installed base of dishwashers in Australian households and recording the consumer usage of dishwashers in detail in a representative way. The information from both combined allows one to estimate the actual average use of resources (energy, water) and programme duration of dishwashers. Analysing the consumer behaviour opens the way to find optimisations of the consumer behaviour which would allow a saving of resources (more than 20 % on electrical energy) without deteriorating the performance and practical use of the dishwashers. Moreover, the comparison of the Australian socio-technical system around automatic dishwashers with the European system allows one to find a possible saving of another 20 % on energy caused by differences in the regulatory framework for those appliances.

To mitigate the impact of aviation on climate change, the International Civil Aviation Organization (ICAO) has committed to reducing carbon dioxide (CO₂) emissions from international aviation by 5% by 2030 and to achieving net-zero carbon emissions by 2050. It is therefore essential to assess the environmental efficiency of airlines to urge them to adjust their actions promptly to meet the desired strategic objectives. This paper focuses on assessing the environmental efficiency of airlines using a network structure and constructs a three-stage airline network structure. Then, a non-convex meta-frontier DEA model with unified natural disposability and managerial disposability is proposed to assess the overall efficiency of 85 airlines for 2018–2019, based on data from 85 airlines worldwide for 2018–2019. The new model not only automatically determines whether an airline's inputs are natural or managerial disposable, but also measures the environmental efficiency of each region, while optimizing overall efficiency. Firstly, Ryanair has the highest overall efficiency among the 85 airlines in 2018–2019, and this increased efficiency is closely related to its excellent performance in handling carbon dioxide emissions. Secondly, the airline efficiency rankings obtained from the non-convex meta-frontier model and the convex meta-frontier model proposed in this paper are largely in line with each other.

Nowadays, there is a growing trend of electricity consumers/users installing solar panels and storage batteries in their premises to alleviate rising energy costs. Despite this, ineffective energy management undermines the potential benefits, especially when there are multiple variables and constraints under consideration. To help solve this issue, we introduce in this paper an inclusive mathematical model for devices energy consumption scheduling based on user preferences under Time-of-Use (ToU) pricing, which also combines intelligently multiple inputs (utility, renewable and storage energy). Our approach attempts to distinguish itself by using all these inputs to optimize various outcomes such as cost, Peak-to-Average Ratio (PAR), and user comfort. It also allows consumers to tune their acceptable comfort level, providing them the autonomy and freedom to choose their preferences. We formulate and solve our mathematical model, subsequently simulating it in Matlab. Validation results underscore its efficacy, showing a notable 18.57% decrease in electricity bills through the combination of renewable energy and storage systems. Furthermore, implementing the model across three operational modes with ToU pricing demonstrates a very significant bill reduction of up to 41.57%. Ultimately, our approach, particularly when coupled with ToU pricing (contrasted with flat-rate), provides users with enhanced decision-making capabilities, driving amplified cost savings and comfort levels.

Understanding sustainability behavior is essential in tackling the global challenge of climate change. The importance of studying sustainability practices and their dynamics grows in light of recent global crises such as the COVID-19 pandemic and the energy crisis following the Ukraine war. These events both challenge and shape individual sustainable practices, offering opportunities for fostering individual sustainable practices and enhancing societal resilience. An online survey was conducted in Germany (n = 571, May 2023) to investigate sustainable behavior dynamics (mobility, energy-saving, and shopping habits) and to identify segments reflecting behavioral shifts. We found relative stability in sustainable mobility choices compared to pre-crisis times, with a tendency towards reduction, as well as an overall increase in energy-saving and sustainable shopping habits. Factor analyses revealed that sustainable mobility behavior (SMB) and sustainable consumer practices (SCP) formed two separate domains. Cluster analyses further identified four segments within each domain, each exhibiting unique behavioral patterns compared to pre-crisis practices. Examining individual variables, adopting more sustainable mobility practices was associated with sociodemographic factors (income, education, and area of living), higher levels of environmental awareness, institutional trust, and increased risk perceptions. Sociodemographic variables had less influence on sustainable consumer practices. Here, higher levels of knowledge, climate change awareness, trust, and risk perceptions played a significant role. Our findings highlight the importance of separately considering behavioral domains in understanding crises-induced changes in sustainability practices. Moreover, it is important to consider specific individual factors and to develop tailored interventions and policies to promote sustainable practices during volatile times.

Garment products are international trade items and essential consumption items. The readymade garment industry of Bangladesh is the second largest garment exporter in the world. The garment industry of Bangladesh consumes one-third of the country's total industrial energy. Such industry consumes significant energy and contributes greenhouse gas (GHG) emissions into the atmosphere. Assessment of energy consumption and GHG emission of garment products helps to understand the baseline status of the production and benchmarking the energy and emission leveling of the product. This paper aims to investigate the energy consumption and GHG emissions of readymade garment (T-shirt) production in Bangladesh. Gate-to-gate production stages have been considered for the investigation. The strategies for the energy and GHG emission-saving potential have been also analyzed. The result showed that the total energy consumption in terms of natural gas, oil, and electricity found are 15,105 m³, 49.93 kg, and 36,265 kWh respectively per day. The total CO₂ emission found is 56.65 tons per day. The specific energy consumption found is 12 MJ/piece and the specific emissions of the CO₂, CO, CH₄, NOx, and SOx are 0.94 kg/piece, 1.69 gm/piece, 3.53 gm/piece, 4.1 gm/piece, and 0.89gm/piece, respectively. The proposed strategies could save energy in the machinery section in the range of 22–70%. The energy saving potential of 25% is possible in the steam generation sector by employing the proposed electric steam generator. The steam generation section gives the highest CO₂ emission and the compressor section gives the lowest emission. The specific energy consumption and carbon footprint of Bangladesh-manufactured garments are in very close agreement with the literature studied.

With the diffusion of prosumerism, where households act both as producers and consumers of energy, policy makers must strike a balance between encouraging microgeneration and regulating this new prosumer segment on the energy market. However, effective policy implementation depends on prosumers’ behavioural reactions. This paper provides evidence on the interplay between digital real-time information and regulation of self-consumption for rooftop photovoltaics (PV) in Croatia. Croatian households that produce more annual electricity than they consume are automatically re-classified as renewable traders, which means additional administrative duties and less favorable tax treatment. This creates perverse incentives to reduce PV generation or increase energy consumption by year-end. We document the behavioural reactions to this policy design, indicating that energy production and consumption are highly elastic regarding regulatory incentives, but only if these incentives are made transparent and accessible with timely information. We collected two survey waves (n = 54 and n = 80) and smart meter data (n = 39), which illustrate the behavioural reaction before and after year-end. According to the survey wave before year-end, almost half of the participants considered curtailing their PV output. According to the smart meter data, a sizable share did indeed take action by shutting down PV production or by powering additional devices to reduce the surplus near year-end. In a second survey wave in the new year, prosumers provide ex-post insights on the specific measures taken to reduce surplus. We discuss research insights regarding the transparency and control offered by metering feedback, and how this can influence household behaviour within regulatory frameworks.