Rational Inattention and Energy Efficiency

Cities face increasing challenges in reducing their impact on climate change while also preserving their cultural heritage, both older and more modern. This paper investigates the articulations of energy efficiency and cultural values in local public policies of the City of Stockholm. The municipality is particularly interesting in its self-imposed role as being world-leading in the climate transition. However, we argue that the city fails in undertaking a holistic approach to sustainability by not providing sufficient guidance on how energy efficiency and cultural values can be reconciled. Cross-sectorial and sectorial policy documents as well as the implementation of local directives and objectives in a large municipally owned housing company are studied. Two cases of renovation serve to demonstrate how policy is turned into practice and how energy efficiency aims and cultural values are assessed. One significant finding is the clear asymmetry between the steering ability of policy relative to energy efficiency and cultural values respectively. A major drawback is the lack of directives and guidelines concerning the built heritage, particularly at a building level, supporting decision-making when implementing necessary energy efficiency measures in buildings with cultural values. A recommendation made is to introduce cross-sectorial guidance in implementing energy efficiency measures in buildings with cultural values.

Performance improvement of a single slope solar still by employing thermoelectric cooling channel and copper oxide nanofluid: An experimental study

PurposeThe purpose of this study is to examine whether financial markets value a firm’s specific corporate environmental performance (CEP), i.e. its energy efficiency. This study also investigates the mechanism through which energy efficiency is associated with firm value.Design/methodology/approachFor the empirical study, a sample of 324 US-listed non-financial firms during the period 2006–2019 was accessed from Thomson Reuters Refinitiv. Using baseline ordinary least squares regression models, this study first estimates the association between energy efficiency and firm value. It then tests the role of analyst coverage (the number of sell-side financial analysts following the firm) in ascertaining the value relevance of energy efficiency. To ensure the robustness of the results, alternative estimations including endogeneity and sample bias correctness tests were performed.FindingsThe study shows that energy efficiency is associated with firm value, and the role of analyst coverage as an external corporate governance mechanism is positive and significant on the value relevance of energy efficiency. Furthermore, this study documents that the relationship is shaped by sustainability-related internal and external risks, indicating that financial analysts’ role becomes more imperative when firms are subject to high scrutiny.Originality/valueThis study contributes to the literature by examining the intersections of energy efficiency, analyst coverage and firm value. It attempts to demonstrate how and why CEP and financial performance are linked. In the context of growing environmental concerns, the pressure of climate change and achievement of net-zero carbon emissions, this study provides valuable insights into the financial market wherein firms’ environmentally responsible behaviours are value-enhancing, and governance mechanisms are impactful. This study suggests that financial analysts can serve as an effective external corporate governance mechanism.

The present study was designed for the experimental and modeling investigations on thermodynamic analysis of drying onion slices using four microwave power levels (100, 350, 500, and 750 W) and the four samples thicknesses (2.5, 5, 7.5, and 10 mm). A multilayer feedforward artificial neural network was employed in order to predict energy and exergy performance of the dryer and the prediction success were compared using three evaluation criteria. The average values for energy efficiency and specific energy loss ranged from 13.52% to 37.94% and from 1.35 to 7.43 MJ/kgwater, respectively. Findings showed that the exergy efficiency changed from 11.79% to 30.84%. In addition, the statistical analysis revealed that higher microwave power levels and the thinner samples significantly (p < .05) enhanced both the energy and exergy efficiencies. The obtained results for exergy improvement potential (accounted for 37.83%–69.41% from the total exergy inlet) indicated that the drying process has good potential for exergy performance improvement. Based on the modeling outcomes, the energy efficiency was well predicted by an artificial neural network with a topology of 3–18–18–1 and LM training algorithm and threshold function of Tan–Tan–Lin. However, the best topology for the exergy efficiency prediction had 3–20–16–1 structure, LM training algorithm and Log–Log–Lin transfer function (R2 of .94).Practical ApplicationsIn this study, onion slices were dried in a domestic microwave oven and the influence of the power level and thickness of the samples on energy and exergy parameters was investigated. In addition to experimental evaluation, the multi‐layer feed‐forward neural network can be used to model and predict changes in energy efficiency and exergy during the process.

Energy and exergy analysis of single slope single basin solar still in Indian condition: an experimental analysis

Massive multiple-input multiple-output (MIMO) systems are designed to increase data capacity systems. However, there are growing social and economic concerns in developing these communication technologies. Energy efficient systems are desirable for these systems considering the costs and minimizing resources. Thus, the optimization of these approaches is significant in the advancement of green communication. This paper converges on the circuit power in modelling massive MIMO systems. Specifically, to apply various power consumption of the transceiver chains, to determine the desired power of the base station value for maximum energy efficiency, and to define the effects of a realistic circuit power consumption model in Massive MIMO systems. Mathematical models were developed, and the corresponding codes were simulated using MATLAB. Different processing schemes were also studied, namely, maximum ratio transmission/maximum ratio combining, and zero forcing for the perfect and imperfect single-cells scenario. In contrast, multiple cells consider different re-use factors. As observed, a low power wattage consumption of transceiver chains and base stations is desired to produce a more remarkable relative change in energy efficiency. Local oscillators' power usage is also recommended to be low wattage. Low-power systems utilize low energy consumption but not disregarding higher energy efficiency. Other factors in data throughput – bandwidth, transmit power, noise power spectral density, and path loss, can be studied to optimize energy-efficient massive MIMO systems.

Machine learning approach of detecting anomalies and forecasting time-series of IoT devices

For decades, the construction industry has contributed significantly to China's economic growth. The heavy energy consumption inevitably leads to the release of large amounts of carbon emissions. Improving energy efficiency has been a crucial solution for mitigating the environmental impacts while boosting its green economy in the construction industry. Measuring the energy efficiency in the construction industry considering the quality of government sector is still limited. Using panel provincial data in China from 2011 to 2020, this paper proposes a two-stage dynamic data envelopment analysis (DEA) framework integrating the government sector with the production sector in the construction industry, and calculates energy efficiency. The spatial Durbin model is used to analyze the driving forces of energy efficiency. The research findings include (1) the energy efficiency in the eastern region is higher than that in the central and western regions. The mean values of energy efficiency in the eastern, central, and western regions are 0.42, 0.34, and 0.37. (2) Even though governance efficiency is lower than production efficiency, there is a positive correlation between governance efficiency and production efficiency with a correlation coefficient of 0.48. Improving governance efficiency is a significant step to increase the production efficiency and further increase energy efficiency of the construction industry. (3) Digital transformation has a positive effect on governance efficiency but has no effect on production efficiency. The government-production nexus framework provides implications for clarifying the role of government intervention in improving energy efficiency.

Residential demand-side management (DSM) of electricity has been gaining attention as a way to reduce energy consumption at home and as a way of maximizing the utilization of fluctuating solar power generation. To promote the smooth introduction of DSM into homes, power usage trends according to the time of the day should be examined for individuals in relation to their lifestyles. The analyses of power usage trends can identify the types of home appliances that should be utilized differently in order to increase energy efficiency. Such analyses can also predict the individual behavioral changes that should result in home appliances being used in the time slots in which solar power is more conveniently available. The purpose of this research was to estimate and observe the amount of power saving potential for each daily time slot with respect to an individual’s particular attributes, and to derive the power saving potential of the whole country by accumulating these data on individuals. This was achieved by using the Survey on Time Use and Leisure Activities (STULA) and Energy-Saving Performance Catalog (ESPC) in Japan. According to the results of our estimation, a meaningful power saving potential is sufficient to address a power supply shortage after a disaster such as an earthquake. It is possible to save power by replacing existing home appliances with more energy efficient ones, by making environmentally conscious choices when using home appliances, and by discontinuing the use of home appliances during electricity shortages within the community as a whole. Using the estimated power saving potentials, we examined the effects of two DSMs: (1) adjusting the time for which home appliances are used; and (2) aggregating the power demand of households with different attributes. The results showed that these DSMs would contribute to a more stable power system operation. Future research might address the rapid penetration of community energy management systems and demand response systems.

This paper introduces a method for the assessment and evaluation of energy efficiency of the manufacturing processes in the production as well as a corporate and cross-industry comparison. Already today, energy-related characteristic value systems are used, which are related to the energy consumption of large electronic household appliances or are focusing on their production facilities. The energy efficiency value is a newly developed indicator and will provide valuable information about the energy efficiency of the production of various products, production operators, and consumers. In the following, the energy efficiency value, which is based on the approach of minimal value calculation, is presented in detail. The basic idea is the comparison and evaluation of energy efficiency based on the ratio of the theoretically required energy consumption to the actual energy consumption. Depending on the analysis of influencing factors, a model highlighting their dependencies could be established. The developed system hinges on a successive calculation of the minimum value. Each of these minimum types can be put in relation to the measured energy consumption. However, depending on the chosen basis, the conclusion and focus of the calculated key figure may vary. By using the real minimum as a basis, the actually existing energy savings become visible. The method will be put to the test through an exemplary application for processes in the fields of cutting technologies. This course of action allows for the validation of the developed energy efficiency value and reveals the potential of this method.

An experimental study for optimizing the energy efficiency of a proton exchange membrane fuel cell with an open-cathode

Performance analysis and optimization of cascade waste heat recovery system based on transcritical CO2 cycle for waste heat recovery in waste-to-energy plant

A sub-system design comparison of renewable energy based multi-generation systems: A key review along with illustrative energetic and exergetic analyses of a geothermal energy based system

Energy efficiency and conservation values in a variable renewable electricity system

Energy efficiency and the influence of gas burners to the energy related carbon dioxide emissions of electric arc furnaces in steel industry