Search

Research has revealed the existence of an energy-efficiency gap – the difference between optimal and actual energy end-use, suggesting that energy efficiency can be improved. Energy management (EnM) is a means for improving industrial energy efficiency. However, due to various barriers, the full potential of EnM is not realised. Several studies have addressed drivers and barriers to energy efficiency but few to EnM. This study aims to identify EnM practices, the most important perceived drivers and barriers for EnM, and relations among them in the energy-intensive Swedish pulp and paper industry (PPI), which has the longest experience internationally of practising EnM systems, and has worked according to the standards since 2004. Our results show that, altogether, the PPI works regularly and continuously with EnM, with a clear division of responsibilities. The highest maturity for EnM practices was for energy policy, followed by organization, investments, and performance measurement. The study also shows that communication between middle management and operations personnel has potential for improvement. The most important categories of drivers were economic, whereas for barriers they were organizational. Nevertheless, knowledge-related barriers and drivers were amongst the most important, suggesting that the absorptive capacity for energy issues could be improved. Image 1029 • Energy is managed continuously, with clear policies and responsibilities. • The main drivers are economical while main barriers are organizational. • Knowledge related barriers and drivers are amongst the next most important. • Employees' absorptive capacity for energy issues could be improved. • Link between energy policy and performance measurement could be improved. [ABSTRACT FROM AUTHOR]

The Swedish pulp and paper industry (PPI) must increase energy efficiency to remain competitive on the global market, which has experienced entries from countries with cheaper energy and raw material supplies. Interactions among variables for energy use, production, energy management, electricity price and firm characteristics (FC), in different types of mills, i.e., pulp, paper and integrated mills, in Sweden from 2006 to 2015 indicate that correlations among the studied variables were different in different types of mills. This difference between types of mills seemed to originate partly from varying accessibility to production residue that could be used for energy. For all types of mills, variation of electricity prices did not correlate significantly with energy efficiency during the study period. The studied FC were firm's age, number of employees, number of companies in company group, net sales and profit for the year. Energy efficiency was more affected by the variables characterizing energy and production compared to the variables representing FC. This study also suggested presence of possible discrepancies between FC that were perceived as barriers to energy management towards energy efficiency, according to previous studies, and what was shown by the data combining variables representing energy use, production and FC. [ABSTRACT FROM AUTHOR]

The pulp and paper industry faces several challenges linked to climate and environmental impact, resource efficiency, rising energy prices, increased competition for biomass resources, and declining demand for traditional printed paper products. However, these challenges also offer strategic opportunities for the industry to develop into a competitive, resource-efficient, and low-carbon industry in line with a biobased economy. Against this background, this paper aims to analyse current energy strategies in the pulp and paper industry in Sweden. Specifically, the paper analyses how companies combine continuous process efficiency to reduce energy costs with activities that could be developed into new energy-related products to increase revenue. Most of the analysed companies work to various degrees with both these strategies, employing methods that include improving energy efficiency, energy security, and energy conversion, as well as developing a wide range of biobased energy products. However, our study indicates that there is an untapped potential associated with energy product development, and we conclude that energy efficiency measures can free up resources, enabling the development of new energy products. Finally, several potential managerial outcomes and implications are outlined. • The paper analyses the energy strategies in the pulp and paper industry in Sweden. • Energy strategies focus both to improve energy efficiency and develop new energy-products. • The companies' energy strategies combined exploitation and exploration. • A number of managerial implications are presented. [ABSTRACT FROM AUTHOR]

This research paper presents a novel technique for improving load-shedding in DC microgrids by incorporating a binary number generator (BNG). Load shedding, a controlled strategy utilized to maintain equilibrium between power supply and demand within a microgrid when the aggregate demand surpasses generated power, is widely employed. Nevertheless, conventional load-shedding methods frequently encounter challenges, notably over-shedding and voltage deviations, particularly in scenarios involving numerous controllable loads. To overcome these challenges, an enhanced algorithm is proposed, which integrates the BNG technique. Simulation results conclusively demonstrate the effectiveness of the proposed algorithm in ensuring microgrid stability during periods of supply-demand imbalances. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative decision support system for improving ship energy efficiency. It combines an engine optimization model and an artificial neural network (ANN). Real-time data regarding the ship and engine performance is obtained along a specific ship navigation, and an engine optimization model is built using Ricardo Wave software. This model is validated with high accuracy. Ship-specific parameters are derived, and fuel consumption is estimated using ANN models with different structures. The study identifies the most suitable ANN model with 1 hidden layer and 5 neurons based on error metric evaluation where the 0.99697 R2, 0.00035 RMSE, and 0.06470 MAPE scores are calculated. This approach offers a cost-effective solution for shipping companies to monitor critical engine parameters in real-time without investing in sensors or data collection systems. Thus, it contributes to dealing with the problem of the scarcity of analyzable data in the maritime literature, which is one of the significant issues in the papers related to energy efficiency, machine learning, and deep learning. It is an innovative approach since the parameters that are related to real-time operations rather than considering only instruction book information are aggregated, and the produced data is analyzed by an intelligent tool. • A system is proposed to control ship energy efficiency level by combining an optimization model and a neural network • A simulation model is created in the Ricardo Wave tool and the engine model is validated by actual data. • The ship fuel consumption is estimated by an artificial neural network based on the derived input parameters. • The prediction process is evaluated by error metrics to determine its success. [ABSTRACT FROM AUTHOR]

In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

The customers of textile wet processing plants have committed to reduce their greenhouse gas emissions from outsourced manufacturing activities. The textile brands directly use specific energy consumption values to analyze and set steep, time-bound emission intensity reduction targets for the energy intensive textile wet processing plants. However, the direct use of specific energy consumption values to evaluate energy savings can be misleading. In this paper, the authors propose a methodological framework to systematically evaluate energy performance and monitor energy savings in the textile wet processing plants. Further, the approach was extended to analyze the energy performance monitoring practices and identify energy conservation measures. The proposed framework was developed based on thorough analysis of the manufacturing process of textile wet processing plants and the principles of ISO 50001. A textile wet processing plant was chosen as a case study for illustrating the effectiveness of the framework using multiple regression method. Bottom up approach for benchmarking was used and yet significantly simplified by the introduction of an innovative parameter "program mix factor" and thereby evaluate "equivalent specific energy consumption". The predicted values for specific energy consumption were found to be within a close error range of ±10 % of the actual data. The proposed methodological framework is therefore innovative, simple and yet comprehensive to conduct internal benchmarking in textile wet processing plants. The textile brands are suggested to use equivalent specific energy consumption instead of specific energy consumption for energy performance monitoring of their textile wet processing plant suppliers. The authors also conducted a survey in fifteen textile wet processing plants to assess the prevailing energy monitoring practices. The results of the survey suggests that only 20 % of the plants are practicing basic level energy performance monitoring, while the remaining 80 % are at minimal level. • Textile wet processing plants were analyzed to identify the parameters required to normalize specific energy consumption • A simplified methodological framework was developed for the textile wet processing plants and the textile brands • The framework serves as a useful tool to evaluate, monitor the realistic energy performance & identify conservation measures • The textile brands are suggested to use equivalent specific energy consumption to monitor energy performance • The study identified the low levels of energy monitoring practices in textile wet processing plants in South Asian countries [ABSTRACT FROM AUTHOR]

Over the recent years, multimedia applications have begun to be used over wireless sensor networks (WSN), which hitherto has been primarily used to carry small amount of data. To meet the demand for higher throughput and real-time characteristics of multimedia contents, the routing protocol need to be simplified and optimized. In this paper, we present a routing algorithm that provides a low end-to-end packet delay and low packet loss, referred to as smart, greedy forwarding algorithm based on throughput and energy-awareness (SGFTEM). This algorithm routes multimedia packets across a WSN by choosing high- throughput paths rather than always choosing the shorter path to the sink. When it encounters network holes, a network void-bypass is applied, which enhances the reliability of the network. Energy management is also implemented to extend sensor node lifetime by way of reducing the radio transmission coverage to a suitable distance reachable by the sensor nodes The simulation results shows that, SGFTEM reduces the end-to-end delay by 40% and packet loss ratio by 35% and maintain energy consumption against other algorithms. With energy management, the residual energy of sensor nodes are made to be equally distributed across the entire network which results in load balancing. The performance of SGFTEM are also compared via simulation against AGEM, TPGF, GPSR, and AODV showing superior performance under similar scenarios i.e. low packet end-to-end delay, low packet loss and load balancing of routing paths. [ABSTRACT FROM AUTHOR]

From an environmental point of view, reduced use of energy remains a cornerstone in global greenhouse gas mitigation. However, without full internalization of external costs, greenhouse gas mitigation as such may not be highly prioritized among business leaders. Rather, it is the magnitude of production costs and ultimately the size of market revenue that articulates success or failure for business leaders. Nevertheless, reduced energy use or improved energy efficiency can have a vast impact on profitability even for companies with low energy costs, as the reduced energy costs directly lead to increased profits. In this paper, a review of ten years of empirical research in the field of industrial energy management in Swedish industry is presented. Based on the review, the paper proposes success factors for efficient energy management, factors which could help guide individual energy managers as well as policy makers in order to close the energy efficiency and management gaps. The paper also presents an overview of important industrial energy management tools, which would facilitate in-house energy management in industry. [ABSTRACT FROM AUTHOR]

The energy benchmarking has been recognised as an effective analytical methodology and a significant management tool that helps to improve the efficiency and performance of the energy utilisation. Studies on energy benchmarking has been worldwide carried out in many areas for different objectives. However, there are few systematic theories to support the development of a reasonable energy benchmarking and to provide efficient application measures in machining systems. To overcome these challenges, based on previous studies we propose two significant rules of energy benchmarking in machining systems contributing to the development of the energy benchmarking and application. This paper describes the concept, content and scope of the energy benchmarking rules laying a solid theoretical foundation for the energy benchmarking research in the machining field and giving the research directions. Meanwhile, through application analysis of the rules, the energy benchmarking rules have wide application prospects in machining systems and play an important role in the energy-efficient production. [ABSTRACT FROM AUTHOR]

• TIP-EMS enhances EV energy efficiency by integrated prediction and energy management. • Significant driving economy boost; 1.6%-4.2% better than state-of-the-art PEMS. • TIP-EMS shows robust performance with varying prediction weight adjustments. To enhance the energy efficiency of electrified vehicles (EVs), developing effective energy management strategies (EMS) for hybrid storage systems is essential. Predictive EMS (PEMS) that foresee future vehicle speeds have demonstrated substantial potential in boosting EMS performance. However, traditional PEMS models, employing a sequential approach of speed prediction followed by energy allocation, are hampered by cumulative errors. These errors from the initial speed predss this issue, this paper introduces a novel solution: the trainable integrated preiction negatively impact the efficiency of subsequent energy management. To addrediction and energy management strategy (TIP-EMS). Contrasting with conventional sequential PEMS, TIP-EMS features a dual-branch, integrated neural network, which is fully trainable. This network processes driving status inputs via attention layers, with one branch dedicated to energy management objectives using a reinforcement learning (RL) algorithm, and the other to vehicle speed prediction. Both branches are trained simultaneously, but post-training, only the RL branch is activated for energy management. Implemented with a soft actor-critic RL algorithm, TIP-EMS is applied to a fuel cell EV for optimized energy management. The validation involved training TIP-EMS using 27 driving profiles, which developed its prediction and energy management capabilities, followed by tests in untrained scenarios. The results show that TIP-EMS surpasses conventional sequential PEMS by up to 4.2% in scenarios where prediction accuracies are comparable, highlighting the efficacy of the trainable integrated mechanism. In addition, TIP-EMS exhibits superior energy conservation compared to non-predictive RL strategies. Lastly, TIP-EMS exhibits robustness to adjustments in the weight given to the prediction objective, further confirming its practical applicability. [ABSTRACT FROM AUTHOR]

This paper reports the use of low cost off-the-shelf components to develop a wireless energy monitoring system for the purpose of non-intrusive appliance load monitoring. The system comprises hardware design where a standard open source WiFi-connected embedded system board is used as the core component, an analog front end for interfacing between the voltage and current sensors and the embedded board and also a server to store data for further processing. The software side consists of algorithms for performing data partitioning and Naive Bayes classifier. Non-intrusive appliance load monitoring (NIALM) is a methodology used to disaggregate total power consumption into individual electrical appliance power usage. In this paper, the average power consumptions of electrical appliances are obtained from the system setup through the identification of switching ON or OFF events of appliances. The Naive Bayes classifier is deployed for appliances’ classification. This work demonstrates the feasibility of utilizing low cost and standard components to develop a wireless energy monitoring system. It is also observed that the developed classifier algorithm is able to classify individual electrical appliances with satisfactory accuracy level using few training examples. The novelty of this paper is that it developed a data set consisting of 4 types of appliances from the application of embedded networking device. This paper also shows that satisfactory classification accuracies can be achieved using few training examples with generic classifiers (Naive Bayes) and one feature (the average power). It provides an example of how NIALM can offer feedback to appliances’ energy consumption and therefore promote energy efficiency. [ABSTRACT FROM AUTHOR]

Network end-user devices such as laptops and desktop PCs are often left powered ON 24/7 while they remain idle most of the time. The main reason behind this is maintaining network connectivity for remote access, VoIP, instant messaging and other Internet-based applications. The Network Connectivity Proxy (NCP) emerged as a quite promising strategy for significantly reducing network energy waste by allowing devices to sleep without losing their presence over Internet. It impersonates presence of devices during their sleeping periods at all layers of TCP/IP stack. The NCP can successfully proxy basic networking protocols (e.g., ARP, PING, DHCP, etc.) but faces challenges in proxying TCP sessions and proprietary closed-source applications with encrypted packets. To overcome the limitations of NCP concept, this paper proposes a new strategy for reducing network energy waste through intelligent coordination among a user's devices (e.g., smartphone, laptop, desktop PC, etc.). In the proposed system, a user's daily used devices autonomously and seamlessly communicate with a centralized control server that decides which user device will maintain presence of applications at a given instant. To allow devices to sleep and wake them up whenever necessary, the proposed system also uses a light-weight Home Gateway Proxy (HGP) with very basic set of practically realizable features. The communication framework for HGP is designed to achieve auto-discovery, seamless networking and communication features. This paper also practically evaluates the proposed system and estimates energy saving for fixed as well as mobile network devices. [ABSTRACT FROM AUTHOR]

This paper focuses on energy management in an ultra-energy efficient vehicle powered by a hydrogen fuel cell with rated power of 1 kW. The vehicle is especially developed for the student competition Shell Eco-marathon in the Urban Concept category. In order to minimize the driving energy consumption a simulation model of the vehicle and the electric propulsion is developed. The model is based on vehicle dynamics and real motor efficiency as constant DC/DC, motor controllers and transmission efficiency were considered. Based on that model five propulsion schemes and driving strategies were evaluated. The fuel cell output parameters were experimentally determined. Then, the driving energy demand and hydrogen consumption was estimated for each of the propulsion schemes. Finally, an experimental study on fuel cell output power and hydrogen consumption was conducted for two propulsion schemes in case of hybrid and non-hybrid power source. In the hybrid propulsion scheme, supercapacitors were used as energy storage as they were charged from the fuel cell with constant current of 10 A. • Driving strategy to minimize energy consumption was determined at given restrictions. • Driving energy is related to acceleration phase when average speed is determined. • Fuel cell degradation requires modified energy management strategy. • Hydrogen consumption was evaluated for hybrid and non-hybrid propulsion. [ABSTRACT FROM AUTHOR]

Context: Definition of a comprehensive facility data model is a prerequisite for providing more advanced energy management systems capable of tackling the underlying heterogeneity of complex infrastructures, thus providing more flexible data interpretation and event management, advanced communication and control system capabilities. Objective: This paper proposes one of the possible implementations of a facility data model utilizing the concept of ontology as part of the contemporary Semantic Web paradigm. Method: The proposed facility ontology model was defined and developed to model all the static knowledge (such as technical vendor data, proprietary data types, and communication protocols) related to the significant energy consumers of the target infrastructure. Furthermore, this paper describes the overall methodology and how the common semantics offered by the ontology were utilized to improve the interoperability and energy management of complex infrastructures. Initially, a core facility ontology, which represents the generic facility model providing the general concepts behind the modelling, was defined. Results: In order to develop a full-blown model of the specific facility infrastructure, Malpensa and Fiumicino airports in Italy were taken as a test-bed platform in order to develop the airport ontology owing to the variety of the technical systems installed at the site. For the development of the airport ontology, the core facility ontology was first extended and then populated to reflect the actual state of the target airport facility. Conclusion: The developed ontology was tested in the environment of the two pilots, and the proposed solution proved to be a valuable link between separate ICT systems involving equipment from various vendors, both on syntax and semantic level, thus offering the facility managers the ability to retrieve high-level information regarding the performance of significant energy consumers. [ABSTRACT FROM AUTHOR]

Energy management systems are considered as appropriate instruments to identify and realize energy efficiency potentials in industrial plants. Studies point out a largely untapped potential for energy efficiency in industry through the adoption of systematic energy management. We suggest introducing qualitative and quantitative modelling tools into energy management to facilitate a focused process to set priorities and identify effective measures. This paper describes the case of voestalpine Austria Draht GmbH, an Austrian wire rolling mill. voestalpine Austria Draht GmbH at present is implementing a knowledge based energy management system. Within the work described in this paper, first an overview of energy flows using Sankey diagrams was elaborated. Then a qualitative systems analysis was developed for the plant and a gap analysis done for priority areas. Subsequently physical input–output models for several energy intensive units were prepared. The paper describes the models for the cooling water system and product cooling. This study revealed a significant potential to save electricity by optimizing the control of cooling water pumps along the milling train and to recover heat from the final products. 2 GWh of electricity can be saved annually. The biggest single energy loss in the mill is the heat from air cooling the products on hook conveyors. These heat flows contain about 30–50 % of the energy input for heating up the billets. Following a theoretical analysis of the potential, a demonstration plant was developed and pilot tests were run to characterize the realistic potential of heat recovery on the hook conveyor. Based on the test results, feasibility studies for large scale plants were carried out. As a result, 0.8 GWh of heat can be recovered annually. The method was found useful because it helped to structure the existing information with a reasonable effort mostly by the operators themselves in their work and to build a conceptual model of energy flows and energy efficiency of the total plant. [ABSTRACT FROM AUTHOR]

• Allowing for energy-efficient controls adaptive to diverse production disturbances. • Modeling the system dynamics of serial production lines using max-plus algebra. • Designing an adaptive energy-efficient control policy based on opportunity windows. • The diversity of production disturbances significantly affects energy waste. • Achieving more energy savings with less throughput loss than other control methods. The energy-efficient control has emerged as one of the most promising measures to reduce the unproductive energy consumption of machines during production disruptions. Diverse production disturbances (PDs) are the fundamental cause of production interruptions that result in unproductive energy consumption. In this scenario, the diversity and randomness of PDs necessitate elaborative consideration in energy-efficient controls. This consideration is crucial to the effectiveness of energy-efficient controls, yet it has been generally overlooked. To this end, this paper presents an adaptive energy-efficient control (AEC) methodology to generate adaptive control decisions when machines encounter diverse PDs in serial production lines. As a first step towards AEC, a PD identification method driven by Markov Logic Network is introduced to identify ongoing PDs. To then estimate the system performances in terms of energy savings and throughputs, a system dynamics model for serial production lines is established based on max-plus algebra. Finally, an AEC policy is formulated to optimize unproductive energy consumption on a nearly global scale while maintaining throughputs. A case study was performed on a die-casting production line in order to validate the effectiveness of the methodology. The results indicated a 96.1% F 1 score for PD identifications. Based on this, the AEC policy resulted in a 61.12% reduction in unproductive energy consumption, with a corresponding decrease in throughputs of only 0.65%. It was confirmed that the AEC methodology achieved greater energy savings while minimizing throughput losses compared to conventional energy-efficient control methods. [ABSTRACT FROM AUTHOR]

Abstract: Turkey is one of a number of countries who still lack a national management standard for energy. Industrial energy consumption accounts for 42% of Turkey''s total energy consumption. With the help of a questionnaire and analytical framework, this paper investigates Industrial Energy Management Practice in Turkey and highlights significant bottlenecks and shortcomings of energy intensive industries in terms of energy management application. The survey was carried out as a multiple case study of the Turkish iron, steel, cement, paper, ceramics and textile industries. Outcomes of the questionnaire are evaluated according to the analytical framework which covers company characteristics, regulations, external relations of the companies and internal organizational conditions. After analyzing these elements on the basis of a minimum requirement list, it was found that only 22% of the surveyed companies actually practice corporate energy management in Turkey. The main barriers to proper energy management implementation were identified as lack of synergy between the stakeholders, the extent and scope of energy manager courses, and inadequate awareness of and lack of financial support for energy management activities. As a guideline to overcome present obstacles, a set of policy options are offered: strengthening and restructuring of legal and institutional frameworks, promotion of energy efficiency, education, training and capacity building and facilitating implementation of the international energy management standard ISO 50001. [Copyright &y& Elsevier]

Machining workshop is a widely distributed manufacturing system that consumes massive energy in a low efficiency. In recent years, the increasing pressure from energy price and environmental directive have forced machinery manufacturers to address energy efficiency monitoring and management to improve economic benefits and environmental performance. However, due to the complicated energy flow and dynamic energy changes of the machining workshop, machinery manufacturers still lack an effective method to monitor and manage the energy efficiency in a practical manner. To this end, this paper proposes an energy efficiency monitoring and management system with the support of the newly emerging Internet of Things (IoT) technology. Firstly, the energy characteristics and energy efficiency indicators of the machining workshop are analyzed and defined. Then the framework of the IoT based energy efficiency monitoring and management system is proposed. The key approaches for energy efficiency monitoring and management are then illustrated. Finally, an industrial application is demonstrated to validate the effectiveness and benefits of the proposed system. With the application of the proposed system, potential opportunities for energy consumption decrement and energy efficiency improvement can be identified. Machinery manufacturers can easily reduce energy consumption and energy cost by managing the machining process. [ABSTRACT FROM AUTHOR]

Highlights • Analysis of possible energy savings in the German chemical industry. • Uncertainty analysis of costs and potentials of energy saving measures. • Evaluation of marginal cost curves of energy savings with uncertainties. • Determination of important model parameters using sensitivity analysis. Abstract In 2014, 19.3% of Germany’s industrial final energy consumption could be allocated to the chemical industry. Energy efficiency measures with focus on the chemical industry could thus contribute to reaching the German goal of reducing greenhouse gas emissions. To achieve this goal, energy planners and industries alike require an overview of the existing energy efficiency measures, their technical potential as well as the costs for realizing this potential. Energy efficiency opportunities are commonly presented in marginal cost curves, which rank these measures according to specific implementation costs. Existing analyses, however, do not take uncertainties in costs and potentials sufficiently into account. The aim of this paper is to create a marginal cost curve of energy efficiency measures for the chemical industry in Germany, while quantifying the uncertainties of the results and identifying the most influential input parameters. The identification of energy efficiency measures and the quantification of the associated technical potentials and costs were identified based on literature data and own assessments. Based on these findings a cost curve was created for the current technical potential. This potential was found to be 24.4 PJ per year, of which 23 PJ had negative lifetime costs. To investigate the uncertainties of these results, Monte Carlo simulations were performed to quantify the standard deviations of the implementation potential and costs. Furthermore, a sensitivity analysis, based on Morris Screening and linear regression, was conducted in order to identify the most influential model input parameters. With the applied approach, it was shown that uncertainties have a non-negligible impact on the final energy saving potential and costs, as well as the shape of marginal cost curves. The standard deviation of the energy saving potential was found to be 3.1 PJ. Furthermore, it is possible to systematically prioritise efforts in refining data. [ABSTRACT FROM AUTHOR]

Abstract The more efficient use of energy is a policy issue worldwide. Smart use of technology and management of information is becoming crucial for increasing energy efficiency. The 7th Framework Program of the European Union supported international research to fulfill the potential of Information and Communications Technologies for Energy Efficiency. Using Social Network Analysis, this paper analyzes this research network and explores the links and influences in the cross-country knowledge flows generated. The analysis identifies some important differences in the position that countries hold on the network. Results highlight the importance of countries acting as hubs and gatekeepers in the promotion of research and the improvement of energy efficiency. Highlights • The network of the 7th Framework Programme on Information and Communication Technologies for energy efficiency is studied. • Countries with a central position in the research network benefit from energy efficiency gains. • A fast access to knowledge does not guarantee efficiency improvements. • Climate-resilient countries tend to have more adaptation in terms of efficiency. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the method and results of a survey of 27 of the 33 Australian universities teaching engineering education in late 2007, undertaken by The Natural Edge Project (hosted by Griffith University and the Australian National University) and supported by the National Framework for Energy Efficiency. This survey aimed to ascertain the extent of energy efficiency (EE) education, and to identify preferred methods to assist in increasing the extent to which EE education is embedded in engineering curriculum. In this paper the context for the survey is supported by a summary of the key results from a variety of surveys undertaken over the last decade internationally. The paper concludes that EE education across universities and engineering disciplines in Australia is currently highly variable and ad hoc. Based on the results of the survey; this paper highlights a number of preferred options to support educators to embed sustainability within engineering programs, and future opportunities for monitoring EE, within the context of engineering education for sustainable development (EESD). [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to conceptually analyze the cost-effectiveness of voluntary energy efficiency programs targeted at the industrial sector. In the paper a broad methodological framework for such an assessment is outlined, and this is applied empirically to discuss the potential cost-effectiveness of the ongoing Swedish energy efficiency program PFE. The focus lies on the presence of asymmetric information and bounded rationality, and the paper discusses how these factors may influence the cost-effectiveness of these types of programs. We also highlight the impact of the self-selection mechanism on the program''s cost-effectiveness. The results show that the presence of information inefficiencies and asymmetries represents one of the major motives for policy intervention in the industrial energy efficiency field, but the substitution of energy management systems for electricity taxes—such as that achieved in the Swedish PFE program—does not necessarily address these asymmetries entirely cost-effectively. First, the presence of firm-government information asymmetries implies that electricity taxes could do a better job in energy-intensive companies while an energy management system could be more effective in companies with a low energy-intensive production process due to the lack of prior experience of energy efficiency measures. The current set-up of PFE induces the reverse situation. Second, although firm-internal information asymmetries may well exist in the participating energy-intensive companies—implying that energy management systems could do a good job in detecting cost-effective measures—this is likely to be even more true for the non-participating companies (again due to their comparatively low accumulated knowledge in the energy efficiency field). It should however also be acknowledged that this analysis is static, and in the long-run voluntary energy efficiency programs may lead to significant learning impacts and—given the public good characteristics of this new knowledge—to important spillover effects. [Copyright &y& Elsevier]

Implementing machine-learning models in real applications is crucial to achieving intelligent building control and high energy efficiency. Over the past few decades, numerous studies have attempted to explore the application of machine-learning models to building energy efficiency. However, these studies have focused on analyzing the technical feasibility and superiority of machine learning algorithms for fitting building energy-related data and have not considered methods of implementing machine learning technology in building energy efficiency applications. Therefore, this review aims to summarize the current practical issues involved in applying machine-learning models to building energy efficiency by systematically analyzing existing research findings and limitations. The paper first reviews the application status of machine learning-based building energy efficiency research by analyzing the model implementation process and summarizing the main uses of the technology in the overall building energy management life cycle. The paper then elaborates on the causes of, influences on, and potential solutions for practical issues found in the implementation and promotion of machine learning-based building energy efficiency measures. Finally, this paper discusses valuable future machine learning-based building energy efficiency research directions with regard to technology opportunity discovery, data governance, feature engineering, generalizability test, technology diffusion, and knowledge sharing. This paper will provide building researchers and practitioners with a better understanding of the current application statuses of and potential research directions for machine learning models in building energy efficiency. • The paper is written from the perspectives of model application and promotion. • The paper summarizes current uses of ML-based building energy efficiency technology. • The paper discusses practical issues in applying ML to building energy efficiency. • The paper indicates future research directions for ML application and promotion. [ABSTRACT FROM AUTHOR]

This paper defines the diverging interests of multiple actors in typically achieving and advancing energy efficiency. Gaps in the literature include the short elaboration of energy efficiency factors and conditions and the lack of information about developed and developing countries and thorough consideration of their specific features, impeding the development and implementation of detailed energy efficiency management strategies. It is against this backdrop that this paper seeks to identify the essence of energy efficiency and developing specific recommendations for achieving the most beneficial effect and well-balanced energy efficiency on the global scale, within the achievements of international goals in sustainable development. The paper exposes the critical factors of energy efficiency, accurately models the best energy efficiency characteristics, and settles the best energy consumption structure. The methodological purpose is to find different energy efficiency scenarios and disentangle fundamental differences in energy efficiency in developed and developing countries. The paper indicates that the reasonable likelihood of noteworthy achievement results in energy efficiency with insignificant mid-term changes. We give recommendations about well-balanced energy efficiency on the global scale and global progress in sustainable development. • This paper disentangles key differences in energy efficiency in developed and developing countries. • We identify the essence of energy efficiency and develop recommendations for achieving balanced energy efficiency globally. • The paper models the best energy efficiency characteristics and settles the best energy consumption structure. • We give recommendations about well-balanced energy efficiency in sustainable development. • The study shows energy consumption optimization in terms of GDP structure, energy consumption, and sustainability. [ABSTRACT FROM AUTHOR]

With the growing urbanization and environmental concerns over buildings' energy consumption and carbon footprint, the demand for energy-efficient building design is greater than ever. This paper addresses these concerns by presenting a novel method for estimating and optimising the thermal load (i.e. total energy load for heating and cooling) of a building within a real environment, provided by high-resolution LiDAR data, while considering long-term climatological parameters, estimated direct and anisotropic diffuse irradiance, shadowing from surroundings, and terrain topography. In the optimisation part of the method, the building's design is optimised regarding the estimated thermal load. The estimation was validated with the well-established EnergyPlus software. In experiments, a rectangular building's design was optimised on a flat and urban dataset. The effect of a building's design parameters on thermal load was inspected as well. On average, the proposed method improved a building's net heat gain by over 103 kWh/m 2 and reduced its thermal load by 234.18 kWh/m 2 when compared with the initial building design. [ABSTRACT FROM AUTHOR]

Measuring and targeting energy performances of manufacturing plants and their subsystems is the first, critical step to understand their energy behavior, to identify energy management opportunities and to evaluate energy savings. In addition, this activity has become always more important in the last decades, as Energy Management Systems and energy management practices based on continuous improvement and people engagement have been largely adopted, requiring the introduction of new energy consumption control systems capable to identify the standard operative energy behavior and performance of systems and machines and their energy baseline, to point out contingent deviations of energy performances from the baseline and to identify possible causes and clearly attribute responsibilities of such deviations. In this context, several attempts have been presented in literature trying to identify methods to create Energy Performance Indicators so as to satisfy these requirements, but most of them are focused either on a physical or on economical definition of the problem (and therefore either on a process/appliance level or on an aggregated level), neglecting the necessity to develop an integrated system to combine those two approaches to the problem and deliver appropriate information to each hierarchical level and function of the company. In addition, even when these indicators are identified, a proper system to monitor and control their evolution over time is neglected. In this paper, a novel methodology to manage Energy Performance by developing, analyzing and maintaining Energy Performance Indicators in manufacturing plants is presented, which has been created to fill this gap and taking into account ISO 50001:2011 and ISO 50006:2014 requirements, in order to be as general and widely applicable as possible. The proposed methodology allows an immediate identification of manufacturing plant's energy performance deviations through Energy Performance Indicators monitoring over time and an easy association of causes and responsibilities to such deviations, in order to allow companies to rapidly react defining action plans and resetting targets if necessary; it has also been validated through an industrial case study, which will eventually be presented. [ABSTRACT FROM AUTHOR]

Green building (GB) strategies are essential for mitigating energy wastage in the building sector, which accounts for nearly 40% of global energy consumption. However, due to the unpredictable nature of occupants' behavior and inadequate energy management, actual power consumption in GB can exceed intended values by up to 2.5 times. Building Automation Systems (BAS) are increasingly important in improving energy efficiency in GB. This study, therefore, aims to comprehensively review 143 articles published from 2008 to 2022 to explore the nexus between BAS and GB. This paper systematically illustrates 1) BAS applications throughout the lifecycle of GB; 2) BAS applications in supporting GB indoor human comfort, including thermal comfort, visual comfort, ventilation comfort, and acoustic comfort; 3) a research framework for reducing the energy performance gap in GB; 4) five BAS and GB integration methods for improving energy efficiency; and 5) limitations, challenges and future research directions in the BAS-GB domain. The findings reveal that current research in the BAS-GB domain is insufficient and predominantly concentrates on improving energy efficiency and occupant comfort. There are four challenges to achieving comprehensive integration of BAS and GB: uncertainties, long-term prediction and control, BAS-supported sustainability goals, and privacy and security. This study provides essential guidance on BAS implementation for GB development. The five BAS-GB integration approaches lay the groundwork for future research into achieving trade-off objectives between energy efficiency and occupant comfort. • Building automation systems (BAS) applications in green buildings (GB) have been comprehensively reviewed. • Model predictive control (MPC) integrating with BAS for improving energy efficiency of GB has been explained. • Four integration methods for achieving a trade-off objective have been discussed. • Challenges and trends in the BAS-GB domain have been highlighted. [ABSTRACT FROM AUTHOR]

Interoperability issues on networks of heterogeneous devices create a relevant and complex challenge. The Word Wide Web Consortium (W3C) develops a series of specifications, called the Web of Things (WoT), to address this challenge. WoT is focused on integrating smart things into the application layer of a system using on Web technologies. Thus, WoT is expected to have a great impact on the smart retrofit of buildings once data from existing and future planned systems are able to be gathered and analysed seamlessly. In this paper, we (i) analyse the application of the W3C WoT on the core of the Building Energy Management System (BEMS) to enable the universal integration of both private and public systems; (ii) propose a novel architecture for the BEMS based on the W3C specifications; and (iii) present a real-world application based on this architecture. The application covered in this paper allows data gathering from sensors with standard commands, enabling data analysis with a simple collecting process. By applying these specifications, smart building retrofit can be benefited from: (i) the ability to merge and scale different systems and devices; (ii) the easiness to access data; (iii) the reduction of development and maintenance costs; and (iv) offering standard interfaces to the BEMS. • Interoperability issues on networks of heterogeneous devices create a complex challenge. • Web of Things increases interoperability among Internet of Things platforms. • Smart retrofit of buildings can be foster with the adoption of Web of Things approaches. • Time and cost are saved when the smart retrofit of buildings adopts Web of Things. • The ability to scale building energy management systems is improved using Web of Things. [ABSTRACT FROM AUTHOR]

Water-energy nexus plays a vital role to re-phase, plan and develop an urban region for the present and future demands. This phenomenon is complex because of many inter-connected variables of technical and non-technical contexts. This paper reviewed the scope, aims, and approaches from the perspective of water-energy nexus studies in urban water system. The aim is to provide insights to minimize water-energy consumption and achieve maximum efficiency in urban water system management. A systematic review methodology was used to study 94 research papers, selected from relevant literature through the lens of water-energy nexus and energy efficiency. This research focuses on methodologies, models and affecting factors of water-energy nexus in different urban water system. The finding shows that most of studies used different frameworks and optimization approaches to achieve maximum energy efficiency. Integral Theory Framework (ITF) was used to find the inter-connectivity among existent variables of water-energy nexus for future demands. The ITF covers all aspects of water-energy nexus, not only for technological assessments, but also for other variables; technological, environmental, socio-economical, and geographical dimensions. It was concluded that water and energy management have a big gap between policy and implementation. A systematic understanding of relationship and interactions between water and energy was needed not only for researchers, but the managers as well. This study recommended that optimum water-energy efficiency is attainable only when almost all variables and integral sections of water-energy nexus are integrated according to the existent conditions, which are different from locality to locality and system to system. Image 1 • A systematic review on water-energy nexus was conducted in urban water systems (UWS). • Efficiency control measures were proposed to describe the water-energy nexus. • Integral Theory Framework was used to frame the inter-connectivity of existent variables in WEN for future demands. • Maximum energy efficiency can be achieved if all variables are integrated with water-energy nexus. [ABSTRACT FROM AUTHOR]

• An overall panorama of the school buildings in Brazil was presented. • Energy billed data and survey evidence were used to build a statistical stock model. • The Weibull distribution was the most adequate to represent the continuous variables. • kWh/student·year was more suitable than kWh/m2·year to model Brazilian school buildings stock. • Thermal performance is an issue to be greatly improved in schools in Brazil. Understanding the actual conditions in school buildings regarding energy usage and environmental satisfaction gives way to the development of consistent building stock modelling. In the Brazilian context, a deep-rooted inefficient structure of energy management implies a lack of mapping the actual conditions of the public schools. Therefore, this paper aimed to assess the actual energy performance of school buildings in Brazil. This paper innovates by integrating questionnaire responses and billed energy data to allow the construction of an evidence-based stock model through a statistical approach, which was never performed for the Brazilian building stock. Moreover, the association of energy use intensity (EUI) with the core aspects of building characteristics, occupancy, environmental satisfaction and necessary improvements mapped the relevance of such aspects in energy usage patterns. Additionally, a discussion of the EUI indicators was addressed. Results showed an unprecedented broad panorama of the school building stock in Brazil and its main features. In terms of statistical analysis, the Weibull distribution was appropriate for representing the continuous variables of the stock. The EUI as a function of the number of students was more suitable than the floor-plan area to achieve a reliable energy performance analysis. Several tests were performed to assess if the energy management, environmental satisfaction and maintenance practices impacted the EUI or not. Finally, the main conclusion was that the stock model obtained was simple and fit the energy management structure in the Brazilian scenario. [ABSTRACT FROM AUTHOR]

The concept of energy management (EnM) became a topical issue in industrial settings as a result of the energy crises that affected the global community in the 1970s. However, EnM was not implemented within industry with all its potential to improve energy security, raise the maturity level of EnM and increase sustainability. According to the results of previous empirical investigations, the expected interest in energy programs is not found and there is no clear understanding about program adoption criteria within an industry. Keeping in mind the adoption of energy investment through conformation with financial analysis and choosing the investments through contextual factors in the organization (e.g. organizational energy culture, power relationships, EnM system, expertise availability, managers’ mindset) together with characteristics of EnM program as two macro perspectives in energy efficiency literature, this paper aims to understand the main driving factors which lead organizations to either adopt or not adopt a particular program (always with respect to energy management). Moreover, it aims to express the impact of those driving forces of implementing a successful EnM program which could contribute to better understanding of suitable EnM configuration. The investigation has been conducted as a multiple case study involving 15 manufacturing companies of varying size and in different sectors located in Sweden. After analyzing the minimum required steps to establish EnM, assessing the adoption of practices according to their energy strategy, and through assessing EnM maturity level, we found a low level of risk (which arises from lack of certainty and awareness) and the program's alignment with the core business as prominent driving factors for all sizes which foster positive investment decision making through top management. On the contrary, complexity of industry (for large manufacturing companies) and access to capital (for small and medium-sized companies) are the main barriers to adopting those programs. [ABSTRACT FROM AUTHOR]

The shipping sector’s emissions and energy efficiency are attracting increasing international scrutiny, with the International Maritime Organization (IMO) actively promoting better energy management by implementing mandatory Ship Energy Efficiency Management Plans (SEEMP). Key potential measures to improve energy efficiency and reduce emissions are speed optimization and improved communication with charterers and ports to work towards ‘just in time’ operation when there are known delays in port (Virtual Arrival). In this paper we assess empirically, for the first time, the potential reduction in fuel consumption and emissions from the implementation of a Virtual Arrival policy in a global context based on ship position data from the Automated Identification System (AIS). We evaluate 5066 voyages performed by 483 Very Large Crude Carriers (VLCCs) between 44 countries for the period 2013–2015 and estimate the potential for fuel savings if unproductive waiting time at the destination ports can instead be utilized to reduce the average sailing speed. We find that even if only 50% of the estimated waiting time can be avoided, the consequential slow-down in average sailing speeds leads to an average reduction of 422 tonnes of CO 2 and 6.7 tonnes of SO x emissions per voyage. Our findings are important for policy making and the optimization of voyage management in shipping companies as they illustrate the substantial savings on fuel costs and emissions from the broad implementation of Virtual Arrival compared to the prevailing first-come first-served berthing policy and the standard charterparty term of sailing with ‘utmost dispatch’. [ABSTRACT FROM AUTHOR]

In the Smart Grid context, the involvement of end-users is a key element for the implementation of demand response, as a way to enhance the energy efficiency of the electricity infrastructure also enabling to cope with the intermittency of renewable energy sources. Although the participation of end-users may result in higher complexity of system management, it may have a positive impact on mitigating the volatility of electricity prices. End-users may also be a key component in the provision of ancillary services using demand side resources to offer the system operator additional means to enhance system flexibility, robust planning, constraint management and operation scheduling, contributing to the balance between load and supply under a load follows supply paradigm. Demand response is seen as an effective and reliable strategy for the successful integration of renewable energy sources, in a perspective of integrated energy resource management, handling the demand curve using load flexibility whenever the system requires it. This embodies the possibility of changing/controlling the load profile by optimally time deferring the use of some equipment. This paper focuses on the role of energy management systems aggregators, both concerning actual practice in industry as well as research, which can be seen as relevant players contributing to that endeavour. A review of recent literature and projects is made, putting in perspective the role of energy management systems aggregators in the Smart Grid context, in association with demand response programs and technologies, involving the participation of end-users in the provision of ancillary services. The aim is recognizing trends, opportunities, challenges and potential barriers regarding the creation of energy management systems aggregators to improve overall system performance, characterizing the services provided by aggregators and identifying potential research gaps. [ABSTRACT FROM AUTHOR]

Energy management strategy and battery capacity are the primary factors for the energy efficiency of range-extended electric buses (REEBs). To improve the energy efficiency of REEBs developed by Tsinghua University, an optimal design method of global optimization-based strategy is investigated. It is real-time and adaptive to variable traction battery capacities of series REEBs. For simulation, the physical model of REEB and key components are established. The optimal strategy is first extracted by the power split ratio (PSR) from REEB simulation result with dynamic program (DP) algorithm. The power distribution map is obtained by series simulations for variable battery capacity options. The control law for developing optimal strategy are achieved by cluster regression for power distribution data. To verify the effect of the proposed energy management strategy, characteristics of powertrain, energy efficiency, operating cost, and computing time are ultimately analyzed. Simulation results show that the energy efficiency of the global optimization-based strategy presented in this paper is similar to that of the DP strategy. Therefore, the overall energy efficiency can be significantly improved compared with that of the CDCS strategy, and operating costs can be substantially reduced. The feasibility of candidate control strategies is thereby assessed via the employment of variable parameters. [ABSTRACT FROM AUTHOR]

This paper presents Slovenian experiences related to a customized educational solution called EUREM (European Energy Manager) involving the training of energy experts in the field of energy efficiency. The EUREM training program is offered in 27 countries around the world and covers nearly all the energy-relevant issues that can arise in public and private companies. The final output of the practical training is a company-specific prefeasibility study that deals with energy weak points and energy efficiency measures that have a high implementation potential. The presented curriculum of the EUREM training program provides a solid basis for increasing the knowledge and skills of energy managers and was developed with an emphasis on practical experiences related to the deployment, demonstration, measurement and verification of energy-efficient solutions in industry and buildings. Regular surveys and communications involving former training participants indicate that the EUREM training program has stimulated Slovenian energy managers to make significant energy savings in their companies. Around 55% of the Slovenian EUREM training participants confirmed that in addition to their energy concepts, they had also realized additional energy efficiency projects after they finished the training course. Based on the experience gained during the past 8 years of the training program's implementation in Slovenia we can conclude that the energy experts really appreciated their practical education and training with on-the-job support from professional coaches. The future challenges of the education and training program are related to follow-up activities, the development of interactive tools and the curriculum's customization to meet the constantly growing needs of energy experts from industry. [ABSTRACT FROM AUTHOR]

Given the self-declared energy and environmental protection objectives of many car manufacturers responsible companies must use energy-efficient production technologies. The running costs of production sites are a decisive factor in the overhead of automotive production. Therefore, it is important for many operators to reduce those costs in a sustainable way. For this purpose, they attempt to reduce both the energy consumption costs and CO 2 emissions of production systems. However, most components of the energy costs are determined during the very early phases of the product creation process. To achieve an estimation of the energy consumption in this early planning stage, a new suitable forecasting method is required. Therefore, this paper presents an approach for determining the prospective energy consumption by using Methods-Energy Measurement combined with defined energy reference cycles for manufacturing technologies. With this approach, key performance indicators are defined, and the production technologies are divided into basic energy consumers. The average energy values will be determined empirically by using the defined energy reference cycles. With these data, the energy demands for different scenarios are calculated. Thereby, it is possible to estimate the potential energy consumption of complex manufacturing cells. The designed method is validated within a case study of a modern automotive body shop. In summary, the approach contributes to identify and realize sustainable solutions in advance and thus increase the profitability of a factory. [ABSTRACT FROM AUTHOR]

Energy management has been considered in the global agenda as a way to improve energy performance and greenhouse gas reduction in organizations. Industries account for a significant part of energy use worldwide and present opportunities for energy efficiency improvements. Within the industry, energy management is a complex task, regarding scenarios with variables related to the following perspectives: economics, contingency, technological change and behavioural. This paper aims at analyzing the influencing factors on energy management in industries from these perspectives. A survey with 40 variables was carried out with middle managers from different industrial sectors in Brazil. The variables were divided into three groups: drivers for investments in energy efficiency; organizational processes and actions in energy management; involvement of middle managers. Initially, an exploratory factor analysis technique was employed aiming at specifying the main factors influencing energy management. In the sequence , a confirmatory factor analysis was used to associate the variables to the main factors as well as to know how the factors relate to each other. The study showed a positive correlation among all the factors identified. Statistical tests suggested that the factors could not be explained separately. Hypotheses tests were applied to verify the influence of the factors among the groups surveyed. The final model comprised eight factors into the three groups: organizational (strategic , operational), involvement (motivation, support), drivers (production, economics , competitiveness, environment). The results and the main implications of the study are discussed in the paper. • The main factors on energy management presented a positive correlation among them. • Middle managers' involvement influenced strategy and operation on energy management. • Middle managers' involvement depended on the support and motivation from superiors. • Operational factor on energy management influenced drivers for energy efficiency. • Production process was a driver for energy efficiency influencing energy management. [ABSTRACT FROM AUTHOR]

University campuses can be considered as small towns due to their size, number of users and mixed and complex activities, including numerous actions usually met in urban environments. The energy and environmental impact of universities could be considerably reduced by applying organizational, technological and energy optimization measures. The aim of the present paper is to present an efficient web based energy management system for Campuses which manages in an energy efficient way the Campus buildings and spaces of public use, monitors the energy load and performs energy analysis per building and for the Campus as a whole, as well as it interacts with each building’s BEMS and each user through questionnaires, e-mails and forms. The existing Campus IP infrastructure is exploited by using sensor networks, where nodes communicate their information using Web services, allowing direct integration in modern IT systems. To guarantee the system scalability and respect consolidated and diffused standards, the logical/architectural level of the whole Campus Energy Management System is linked with the existing infrastructure based on Internet Protocol (IP). The overall installation is tested via on line questionnaires to the building users showing a significant increase of the occupants’ satisfaction. Finally, the energy efficiency achieved by the proposed system is almost 20%. [ABSTRACT FROM AUTHOR]

The increasing demand for electrical energy, the depletion of fossil fuel based resources and environmental constraints have made it mandatory for the efficient use of electrical energy, energy saving applications and implementing an energy management program. In this paper, a user-friendly tool for tracking and analyzing the electric bills, suggesting the best electricity tariff, controlling the active and reactive power rates, increasing energy efficiency, allowing the consumer to compare the alternatives and avoiding any penalties is presented step by step. The proposed energy saving tool will also help the electrical and more particularly power engineers and consumers in industrial sector to reduce electricity consumption while maintaining the quality of service. The developed tool is applied and tested to determine the optimal design of electrical power system in a university hospital. Test results reveal the performance of the developed tool for an optimization of commercial and industrial plants under different scenarios of power consumption and load demand. The program is written in the Delphi programming environment XE3 to provide enhanced flexibility and runs on Windows. [ABSTRACT FROM AUTHOR]

Existing calculated benchmarking methods and main energy performance assessment schemes often lack the practical ability to manage the energy performance of a vast number of widespread telecommunication base stations (TBSs). Therefore, on the basis of a TBS survey, this paper puts forward the dynamic simulation and sensitivity analysis method to allow the new rule “one energy benchmark for a group of similar TBSs” rather than the traditional rule “one benchmark for one assessed building”. The new method reasonably limits the number of benchmarks and a feasible benchmark system is established for managing numerous TBSs. The results indicate that, first, more than one million TBSs distributed in a large area of China can be divided into 448 typical scenarios. Second, the benchmarks for reasonable energy use of these scenarios can be organized into four simple benchmarking charts. Third, the attempt to establish further challenging energy benchmarks shows that the most energy-saving measure in TBSs, i.e., ventilation cooling, can fully eliminate the negative impact of poor configurations of envelops and cooling coefficients of performance (COP). Finally, establishing telecom industrial standards for locating the reasonable TBS energy consumption level even in giant countries appears feasible. [ABSTRACT FROM AUTHOR]

Current research points to a large energy efficiency potential in industry which is still left unexploited. One of the most promising means of reducing energy consumption and related energy costs is implementing an energy management. This paper provides a systematic review of existing academic journal publications on energy management in industry. Five essential key elements of an energy management based on overarching themes are identified within the body of literature (strategy/planning, implementation/operation, controlling, organization and culture) and the specific findings relating to each key element are synthesized. Subsequently a conceptual framework of an energy management is developed which illustrates that a comprehensive approach is necessary in order to effectively exploit the existing energy efficiency potential. Finally implications for further research are described. [ABSTRACT FROM AUTHOR]

• Comprehensively reviewing of renewable energy based multi-generation systems. • Categorizing multi-generation systems into main four groups. • Listing top ten efficient systems according to energy and exergy values. • Investigating the effect of number of outputs on the efficiencies. In recent years it has gained a significance importance to decrease ecological footprint so to have a positive contribution to environmental quality. Renewable energy plays a significant role in future trends for efficiency and environmental issues. Efficiency of systems is to be increased to meet future demands in terms of sustainability with increased consumption. There is a need for new and innovative research studies on promising technologies, processes and strategies to have sustainable water and energy management in cities. This review paper investigates the use of energy sources in single or multiple forms with different system designs from simple to complex structures. The examined studies were presented in a tabulated form including energy and exergy efficiency values as well as the methods and tools used. The results indicated that the systems with the highest energy and exergy efficiency values had several useful outputs, such as hydrogen, fresh water, drying, heating and cooling etc. The maximum exergetic efficiency was determined to be 94% for a multiple energy sourced multi-generation system while the maximum energetic efficiency was calculated to be 111.3% for a solar assisted and heat pump integrated multi-generation system amongst the reviewed studies. To illustrate the obtained results from review, a geothermal energy based multi-generation system was considered. Some parametric studies were also undertaken to see the effects of geothermal water temperature and flow rates on efficiency values. For a single production case, they were determined to be 13.7% and 50%, respectively while they were obtained to be 98.6% and 67.7% for a multi-generation system, in which electricity, low grade hot water production, high temperature hot water production and hydrogen were useful outputs. However, it should be noted that there was a threshold about the number of products to have an optimum increase in the efficiency values. [ABSTRACT FROM AUTHOR]

Measuring energy efficiency performance of equipments, processes and factories is the first step to effective energy management in production. Thus, enabled energy-related information allows the assessment of the progress of manufacturing companies toward their energy efficiency goals. In that respect, the study addresses this challenge where current industrial approaches lack the means and appropriate performance indicators to compare energy-use profiles of machines and processes, and for the comparison of their energy efficiency performance to that of competitors’. Focusing on this challenge, the main objective of the paper is to present a method which supports manufacturing companies in the development of energy-based performance indicators. For this purpose, we provide a 7-step method to develop production-tailored and energy-related key performance indicators (e-KPIs). These indicators allow the interpretation of cause-effect relationships and therefore support companies in their operative decision-making process. Consequently, the proposed method supports the identification of weaknesses and areas for energy efficiency improvements related to the management of production and operations. The study therefore aims to strengthen the theoretical base necessary to support energy-based decision making in manufacturing industries. [ABSTRACT FROM AUTHOR]

This paper describes the development of a stationary hybrid power system consisting of a 3 kW proton exchange membrane fuel cell (PEMFC) module, a battery set, and solar cells. We design PEMFC control and power managements for the hybrid system, and construct a simulation model based on experimental data. The simulation model is then used to analyze performance and efficiency of the system, employing different power management strategies. The study comprises three parts: PEMFC control, power management, and the simulation model. First, we apply robust control to regulate the PEMFC temperature and current, and achieve root mean square errors of 0.06 °C and 0.07 A, respectively. Second, we integrate the hybrid power system and design power management strategies for sustainable operation. Third, we develop a Matlab™ SimPowerSystem model based on experimental data. The simulation results are shown to match the experiments with a deviation of 0.21%. Last, we apply the simulation model to discuss the impacts of different power management strategies on system efficiency. Based on the results, the designed controllers and power management strategies are deemed effective at improving system performance and efficiency. In addition, the developed simulation model can be applied in the future to develop customized hybrid power system. [ABSTRACT FROM AUTHOR]

There is a widespread assumption in energy statistics and econometrics that energy intensity and energy efficiency are equivalent measures of energy performance of economies. The paper points to the discrepancy between the engineering concept of energy efficiency and the energy intensity as it is understood in macroeconomic statistics. This double discrepancy concerns definitions (while engineering concept of energy efficiency is based on the thermodynamic definition, energy intensity includes economic measures) and use. With regard to the latter, the authors conclude that energy intensity can only provide indirect and delayed evidence of technological and engineering energy efficiency of energy conversion processes, which entails shortcomings for management and policymaking. Therefore, we suggest to stop considering subsectoral, sectoral and other levels of energy intensities as aggregates of lower-level energy efficiency. It is suggested that the insufficiency of energy intensity indicators can be compensated with the introduction of thermodynamic indicators describing energy efficiency at the physical, technological, enterprise, sub-sector, sectoral and national levels without references to any economic or financial parameters. Structured statistical data on thermodynamic efficiency is offered as a better option for identifying break-through technologies and technological bottle-necks that constrain efficiency advancements. It is also suggested that macro-level thermodynamic indicators should be based on the thermodynamic first law efficiency and the energy quality problem may be left to enterprise-level thermoeconomic optimization. [ABSTRACT FROM AUTHOR]

The proposed supervisory control system (SCS) uses a control map to maximize the powertrain efficiency of a hybrid electric vehicle (HEV) in real-time. The paper presents the methodology and structure of the control, including a novel, comprehensive and unified expression for the overall powertrain efficiency that considers the engine-generator set and the battery in depth as well as the power electronics. A control map is then produced with instructions for the optimal power share between the engine branch and battery branch of the vehicle such that the powertrain efficiency is maximized. This map is computed off-line and can thereafter be operated in real-time at very low computational cost. A charge sustaining factor is also developed and introduced to ensure the SCS operates the vehicle within desired SOC bounds. This SCS is then tested and benchmarked against two conventional control strategies in a high-fidelity vehicle model, representing a series HEV. Extensive simulation results are presented for repeated cycles of a diverse range of standard driving cycles, showing significant improvements in fuel economy (up to 20%) and less aggressive use of the battery. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates a hydrogen-based genset maximum efficiency tracking problem in the context of electric vehicle range extension. This genset is cheaper than fuel cells and has the desirable property of being greenhouse gas emission free in addition to being less pollutant than the conventional gasoline based gensets. Using Taylor's series, a parametric efficiency model is built iteratively. This model is used by a nonlinear optimization method which searches for the optimal operating conditions for a maximum achievable efficiency. The root-mean-square-error between experimental data and the model is less than 5 × 10−4. The hardware-in-the-loop simulation demonstrated that the proposed tracking approach is effective. In addition, it can improve the hydrogen-based genset efficiency up to 7.15% compared to the commonly used industrial method based on a constant speed drive approach. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate an adaptive energy management and power splitting system for a fuel cell hybrid electric vehicle. The battery pack is the main power source whereas the fuel cell is considered as a range extender that cannot sustain alone the vehicle traction power. In addition, the fuel cell contributes to reduce the battery pack degradation by limiting its depth-of-discharge (DoD). This energy management system is based on a two layer architecture in which the upper layer computes the anticipated end-of-trip DoD using online mass estimation. The lower layer is designed to split the driver power demand by minimizing a cost function which includes the hydrogen/electricity cost ratio. Therefore, the best trade-off between reducing battery pack degradation and using cost effective energy is provided. Furthermore, the system allows the fuel cell to operate at its maximum efficiency. Comparative study results indicate that using online mass estimation improves the overall fuel consumption efficiency whilst contributing at the same time to DoD reduction. [Copyright &y& Elsevier]

[Display omitted] • Distributed real-time optimal control was developed for typical HVAC systems. • Physical meaning in decomposition was enhanced in the proposed scheme. • Computation load was significantly distributed from BEMS to local computation unit. • Global convergence of the distributed optimal control was investigated. • Distributed and centralized optimal control led to similar energy performance. Real-time optimal control (RtOpt) is an efficient tool to improve the energy efficiency of heating, ventilating and air-conditioning (HVAC) systems. RtOpt is always centralized and solved entirely in building energy management systems (BEMSs). However, centralized optimization is not be an efficient solution because real-time operation data in local loops need to be sent to the central computation unit in BEMS for optimization. This paper, therefore, proposes a distributed RtOpt scheme for typical centralized HVAC systems, which uses a dual decomposition mechanism to break the centralized problem into one mater problem and several sub-problems that can be solved in parallel and independently. The mater problem is converted to a simple mean value calculation using a projected sub-gradient method, thus distributing the computation load from the central computation unit into local computation units. Unlike available decomposition schemes in literature, the proposed method considered the functionality and spatial distribution of the major components of HVAC systems, which could enhance the physical meaning and facilitate the application of the decomposition scheme. The proposed distributed RtOpt scheme was tested in case studies, with numerical analysis being used to demonstrate its potential benefits. [ABSTRACT FROM AUTHOR]