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This paper presents the findings of fifteen energy audits conducted on industrial sites in Canada's Greater Toronto Area (GTA). The audits covered a range of industries including food processing, packaged goods, and finishing processes (powder-coating). The primary focus of the audits was to analyze the natural gas consumption and the performance of major-gas-consuming equipment. The audits identified natural-gas-consuming equipment that could be optimized to yield energy and operational cost savings and greenhouse gas (GHG) reduction opportunities. Food production plants' energy intensity ranges from 5.59 m3/ft2 to 17.73 m3/ft2. Therefore, there is a significant opportunity to improve energy consumption through better technology integration. The results of the audits indicate a trend of an increase in the percentage of non-productive consumption with non-productive time. The proposed energy-saving measures include reducing non-productive natural gas consumption, gas-fired equipment tune-up, optimizing boiler loads, and reducing oven exhaust by using variable frequency drives (VFDs). The findings of this study could be used to develop a demand-side management program specifically for small- and medium-sized industrial facilities in the Greater Toronto Area and other parts of Canada. [ABSTRACT FROM AUTHOR]

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers' energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings. [ABSTRACT FROM AUTHOR]

Energy efficiency represents a key resource for economic and social development, providing substantial benefits to different stakeholders, ranging from the entities which develop energy efficient measures to everyone in society. In addition to cost savings, multiple benefits can be achieved by supporting a better alignment between energy issues and strategic business priorities: e.g., improved competitiveness, profitability, quality, etc. Thus, energy efficiency can be a strategic advantage, not just a marginal issue, for companies. However, most firms, especially small and medium enterprises (SMEs), face many problems and, in some cases, hostility when trying to effectively implement energy efficiency actions. The most dominant barriers are the access to capital and the lack of awareness (especially in terms of life cycle cost effects). The supply chain viewpoint represents one of the main opportunities for overcoming those barriers and improving energy performance even for weaker companies. Since the current literature on energy efficiency and practical approaches to ensure energy efficiency mainly focus on energy performance on a single-firm basis, this paper aims to provide a systematic review of papers on the integration of energy efficiency in supply chain design and management published in academic journal, thereby defining potential research streams to close the gaps in the literature. A number of literature reviews have been published focusing on specific aspects of sustainable or on green supply chain management; however, to the best of our knowledge, no review has focused on the energy efficiency issue. Firstly, the present paper shows how considering energy consumption in supply chain management can contribute to more energy-efficient processes from a systemic point of view. Then, the review methodology used is defined and the sampled papers are analyzed and categorized based on the different approaches they propose. From these analyses, potential future research streams are outlined. [ABSTRACT FROM AUTHOR]

Among the different approaches for minimising the energy consumption of mass transit systems (MTSs), a common concern for MTS operators is the improvement of the electrical infrastructure. The traffic on the lines under analysis is one of the most important inputs to the studies devoted to improving MTS infrastructure, since it represents where and how frequently it is possible to save energy. However, on the one hand, MTS electrical studies usually simplify the traffic model, which may lead to a misrepresentation of the energy interactions between trains. On the other hand, if the stochastic traffic is rigorously modelled, the size of the simulation problem could grow excessively, which in turn could make the time to obtain results unmanageable. To cope with this issue, this paper presents a method to obtain a reduced-size set of representative scenarios. Firstly, a traffic model including the most representative stochastic traffic variables is developed. Secondly, a function highly correlated with energy savings is proposed to make it possible to properly characterise the traffic scenarios. Finally, this function is used to select the most representative scenarios. The representative scenario set obtained by the application of this method is shown to be sufficiently accurate with a limited number of scenarios. The traffic approach in this paper improves the accuracy with respect to the usual traffic approach used in the literature. [ABSTRACT FROM AUTHOR]

A Virtual energy assessment (VEA) refers to the assessment of the energy flow in a building without physical data collection. It has been occasionally conducted before the COVID-19 pandemic to residential and commercial buildings. However, there is no established framework method for conducting this type of energy assessment. The COVID-19 pandemic has catalysed the implementation of remote energy assessments and remote facility management. In this paper, a novel framework for VEA is developed and tested on case study buildings at the University of Melbourne. The proposed method is a hybrid of top-down and bottom-up approaches: gathering the general information of the building and the historical data, in addition to investigating and modelling the electrical consumption with artificial neural network (ANN) with a projection of the future consumption. Through sensitivity analysis, the outdoor temperature was found to be the most sensitive (influential) parameter to electrical consumption. The lockdown of the buildings provided invaluable opportunities to assess electrical baseload with zero occupancies and usage of the building. Furthermore, comparison of the baseload with the consumption projection through ANN modelling accurately quantifies the energy consumption attributed to occupation and operational use, referred to as 'operational energy' in this paper. Differentiation and quantification of the baseload and operational energy may aid in energy conservation measures that specifically target to minimise these two distinct energy consumptions. [ABSTRACT FROM AUTHOR]

Ongoing climate change and increasing energy consumption are becoming a serious threat to international development efforts. To ensure a secure and sustainable future, local, national and regional authorities, as well as energy companies, need to be involved in improving energy efficiency and promoting rational energy use. The consumer is always at the centre of interest of policy and energy reduction strategies makers. It is their behaviour, motives and beliefs that can lead to optimised and economical energy management. This paper responds to the need to identify the individual preferences of energy consumers. The presented research fills an existing gap in the literature by analysing the strength of the influence of different types of instruments and external stimuli shaping pro-environmental attitudes of consumers of different behavioural types. The analysis presented in this paper is the result of the next stage of the authors' research on energy consumers modelling, their segmentation and comprehensive characteristics. The analysis was conducted on a representative sample of N = 4332 respondents from 8 European countries (Czech Republic, France, Greece, Spain, Germany, Poland, Romania, and the United Kingdom). The study used multivariate statistical methods, such as: Correspondence Analysis, Factor Analysis and Kruskal-Wallis test. These methods are adequate to the assumptions of the research procedure and allowed for the identification of 4 latent factors that link the incentives into groups, where the motivation to save energy is based on: information ("Information and Knowledge"), social norms ("Social Influence"), investment funding ("Investments") and energy price changes ("Energy Price"). In addition, the level of effectiveness of the studied incentives and motivators depends on the behavioural type of energy consumers and increases with rising levels of their intrinsic pro-environmental motivation. [ABSTRACT FROM AUTHOR]

Improved energy efficiency has become a strategic issue and represents a priority for European competitiveness. Countries adopt various energy policies on local and national levels where energy audit programs are the most common energy end-use efficiency policy for industrial small- and medium-sized enterprises (SMEs). However, studies indicate that cost-efficient energy conservation measures are not always implemented, which can be explained by the existence of barriers to energy efficiency. This paper investigates how Swedish municipalities can support local micro- and small-sized enterprises with improved energy efficiency and the existence of different barriers to the implementation of energy efficiency. Relating this empirical case study to the theoretical barriers outlined in the text, this study found that the major explanatory factors related to non-implementation of cost-effective energy efficiency measures among micro- and small-sized industrial enterprises were bounded rationality (lack of time and/or other priorities), split incentives (having other priorities for capital investments), and imperfect information (slim organization and lack of technical skill). This study also found that information in the form of a report was the main thing that companies gained from working on the project "Energy-Driven Business". Notably, the study involved companies that had participated in a local energy program and, still, companies face major barriers inhibiting implementation, indicating a need to further study other alternative policy models and how knowledge transfer can be improved. [ABSTRACT FROM AUTHOR]

In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the non-energy proportion of DRAM. Furthermore, modern servers usually use NUMA architecture to replace the original SMP architecture to increase its memory bandwidth. It is of great significance to study the energy efficiency of these two different memory architectures. Therefore, in order to explore the power consumption characteristics of servers under memory-intensive workload, this paper evaluates the power consumption and performance of memory-intensive applications in different generations of real rack servers. Through analysis, we find that: (1) Workload intensity and concurrent execution threads affects server power consumption, but a fully utilized memory system may not necessarily bring good energy efficiency indicators. (2) Even if the memory system is not fully utilized, the memory capacity of each processor core has a significant impact on application performance and server power consumption. (3) When running memory-intensive applications, memory utilization is not always a good indicator of server power consumption. (4) The reasonable use of the NUMA architecture will improve the memory energy efficiency significantly. The experimental results show that reasonable use of NUMA architecture can improve memory efficiency by 16% compared with SMP architecture, while unreasonable use of NUMA architecture reduces memory efficiency by 13%. The findings we present in this paper provide useful insights and guidance for system designers and data center operators to help them in energy-efficiency-aware job scheduling and energy conservation. [ABSTRACT FROM AUTHOR]

Improving energy efficiency in public buildings is one of the main challenges for a sustainable requalification of energy issues and a consequent reduction of greenhouse gas (GHG) emissions. This paper aims to provide preliminary information about economic costs and energy consumption reductions (benefits) of some considered interventions in existing public buildings. Methods include an analysis of some feasible interventions in four selected public buildings. Energy efficiency improvements have been assessed for each feasible intervention. The difference of the building global energy performance index (EPgl) has been assessed before and after each intervention. Economic costs of each intervention have been estimated by averaging the amount demanded by different companies for the same intervention. Results obtained show economic costs and the EPgl percentage improvement for each intervention, highlighting and allowing for the comparison of energy consumption reduction and relative economic costs. The research results come from data gathered from four public buildings, and as such they could not be used to generically identify cost-beneficial energy efficiency interventions for every context or building type. However, the data reveals useful cost based considerations for selecting energy efficiency interventions in other public buildings. [ABSTRACT FROM AUTHOR]

Increasing attention is being paid to the energy efficiency in metro systems to reduce the operational cost and to advocate the sustainability of railway systems. Classical research has studied the energy-efficient operational strategy and the energy-efficient system design separately to reduce the traction energy consumption. This paper aims to combine the operational strategies and the system design by analyzing how the infrastructure and vehicle parameters of metro systems influence the operational traction energy consumption. Firstly, a solution approach to the optimal train control model is introduced, which is used to design the Optimal Train Control Simulator(OTCS). Then, based on the OTCS, the performance of some important energy-efficient system design strategies is investigated to reduce the trains' traction energy consumption, including reduction of the train mass, improvement of the kinematic resistance, the design of the energy-saving gradient, increasing the maximum traction and braking forces, introducing regenerative braking and timetable optimization. As for these energy-efficient strategies, the performances are finally evaluated using the OTCS with the practical operational data of the Beijing Yizhuang metro line. The proposed approach gives an example to quantitatively analyze the energy reduction of different strategies in the system design procedure, which may help the decision makers to have an overview of the energy-efficient performances and then to make decisions by balancing the costs and the benefits. [ABSTRACT FROM AUTHOR]

Improved industrial energy efficiency is a cornerstone in climate change mitigation. Research results suggest that there is still major untapped potential for improved industrial energy efficiency. The major model used to explain the discrepancy between optimal level of energy efficiency and the current level is the barrier model, e.g., different barriers to energy efficiency inhibit adoption of cost-effective measures. The measures outlined in research and policy action plans are almost exclusively technology-oriented, but great potential for energy efficiency improvements is also found in operational measures. Both technology and operational measures are combined in successful energy management practices. Most research in the field of energy management is grounded in engineering science, and theoretical models on how energy management in industry is carried out are scarce. One way to further develop and improve energy management, both theoretically as well as practically, is to explore how a socio-technical perspective can contribute to this understanding. In this article we will further elaborate this potential of cross-pollinating these fields. The aim of this paper is to relate energy management to two theoretical models, situated action and transaction analysis. We conclude that the current model for energy management systems, the input-output model, is insufficient for understanding in-house industrial energy management practices. By the incorporation of situated action and transaction analysis to the currently used input-output model, an enhanced understanding of the complexity of energy management is gained. It is not possible to find a single energy management solution suitable for any industrial company, but rather the idea is to find a reflexive model that can be adjusted from time to time. An idea for such a reflexive model would contain the structural elements from energy management models with consideration for decisions being situated and impossible to predict. [ABSTRACT FROM AUTHOR]

The aim of energy efficiency is to use less energy to provide the same service. In hospitals, energy efficiency offers a powerful and cost-effective tool to reduce greenhouse gas emissions, fuel consumption, and also running costs. Over a six-month period, the six gas-fired boilers that provide both a hospital's heat and hot water were monitored. Analysis of the data obtained led to several actions being implemented in the hospital boiler room control system to improve the efficiency of the heat production system. Comparative studies were conducted, during similar weather periods, of the performance of the hospital's hot water production system before and after the controls were implemented. Results indicate that the control actions applied proved to be effective. Finally; the paper offers a financial; primary energy saving and CO2 reduction analysis that points to a 3,434.00 €/week savings in natural gas consumption; and a cut in CO2 emissions of 20.3 tons/week; as compared to the reference facility. [ABSTRACT FROM AUTHOR]

In the rapidly growing economies of Southeast Asia, energy consumption and energy costs in buildings continue to increase. Over the past decade, energy consumption from the commercial building sector in Thailand has increased at an average of 4% per annum and currently represents over 30% of total electricity consumption, second only to the industrial sector. Buildings that exist today will continue to represent most of both energy and greenhouse gas (GHG) emissions from the built environment, with newly constructed buildings representing only a small additional portion. This paper analyzes the environmental, technical, and financial characteristics of energy efficiency retrofit activities in commercial buildings in Thailand through detailed case studies of forty-two projects undertaken over the past 8 years. Our findings suggest that retrofits provide significant opportunities to reduce energy use, energy costs, and GHG emissions while also validating the economic feasibility of investments into such retrofit activities. Through this detailed analysis of past retrofit projects in Thailand, we found that the marginal abatement costs (MAC) relating to the key energy conservation measures (ECM) implemented within these retrofit projects all have negative costs. However, although these findings demonstrate positive economics and should be sufficient to instigate widespread adoption, in reality, this is not taking place. It is evident that greater public policy and leadership are needed to stimulate growth in the building retrofit sector to take advantage of the opportunities and benefits that building retrofits offer. [ABSTRACT FROM AUTHOR]

This paper investigates and outlines a cost-energy optimised pathway for the UK food manufacturing industry to attain the national Greenhouse Gas (GHG) emission reduction target of 80%, relative to 1990 levels, by 2050. The paper employs the linear programming platform TIMES, and it models the current and future technology mix of the UK food manufacturing industry. The model considers parameters such as capital costs, operating costs, efficiency and the lifetime of technologies to determine the cheapest pathway to achieve the GHG emission constraints. The model also enables future parametric analyses and can predict the influence of different economic, trade and dietary preferences and the impact of technological investments and policies on emissions. The study showed that for the food manufacturing industry to meet the emission reduction targets by 2050 the use of natural gas as the dominant source of energy in the industry at present, will have to be replaced by decarbonised grid electricity and biogas. This will require investments in Anaerobic Digestion (AD), Combined Heat and Power (CHP) plants driven by biogas and heat pumps powered by decarbonised electricity. [ABSTRACT FROM AUTHOR]

Given that global energy use today is still dominated by fossil fuels, there is an urgent need to rapidly reduce its use in order to avert serious climate change. However, the alternatives to fossil fuels—renewable and nuclear energy—are more expensive, and have so far done little to displace fossil fuels. Accordingly, reducing energy use must play an important part in both averting climate change and avoiding the depletion of high energy return easily recoverable fossil fuel reserves. This paper examined both the potential and barriers to the adoption of energy reduction measures, with particular attention to domestic energy and passenger transport. The main finding was that energy efficiency approaches alone are unlikely to deliver anywhere near the energy reductions needed in the limited time available. Instead, most energy reductions will have to come from energy conservation, involving less use of energy-using devices, including private vehicles. Achieving such reductions will require changes in lifestyles, especially for residents of OECD nations. [ABSTRACT FROM AUTHOR]

Since energy efficiency and energy improvement are viewed as two of the most important keys of sustainable management, research on energy has become popular and captured much more attention. The current paper aimed to measure the energy efficiency of 25 countries with carbon dioxide (CO2) emissions as well as their energy efficiency improvement. First, a data envelopment analysis (DEA) slack-based model (SBM) was employed to obtain efficiency scores. Second, the Malmquist Productivity Index (MPI) was then used to examine the improvement during the period of 2010–2017. Findings of this study showed that developed countries had a more balanced development between gross domestic product (GDP) growth and CO2 emissions by using the same inputs as developing countries. Additionally, the findings revealed that India and China, being the two largest population countries, achieved improved energy intensity during 2010–2017; however; their energy consumption and CO2 emissions continued to grow, leading them to being the two worst countries in terms of energy efficiency. [ABSTRACT FROM AUTHOR]