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Abstract This study aims at to make a heuristic analysis of energy efficiency performance of Indian paper industry in a non-parametric production theoretic approach. Using the data for 2004–05 to 2013–14, radial and non-radial variants of DEA were employed to estimate energy saving potential and identify the relative position of paper industry across the states. Preliminary analysis in terms of energy intensity scores showed declining trends of energy intensity over the period of analysis for most of the states except states like Assam, Chhattisgarh, Kerala and Punjab where it does not decline much. Assuming a variable returns to scale (VRS) technology under the conditions of inherent heterogeneity and market imperfection, the slack-based measure (SBM) reported a much higher energy saving potential than reported by other measures in the study. Further by taking scale efficiency into account, the study documented the higher contribution of pure energy inefficiency in explaining the total energy inefficiency within the paper industry relative to scale inefficiency. Finally, the study recommends the propagation of energy efficiency program through a market-based and regulatory mechanism along with consolidation and technological advancement of individual units, in order to tap vast energy saving potential and thereby ensure the growth and environmental sustainability. Highlights • The paper examined the energy efficiency performance of Indian paper industry. • Both radial (BCC) and the non-radial (SBM) measures of energy efficiency, were applied. • BCC measure reported an energy saving potential of 16%. • SBM measure reported an energy saving potential of 24%, higher than BCC measure. • Scale efficiency implied the relatively higher contribution of pure energy inefficiency. [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]

Abstract Water pumping systems are widely used in industrial and civil applications. During their operational life, they consume energy and materials (mainly for installation and replacement of components). The aim of this paper is to optimize the pump operations in order to save energy and enlarge the operational life of the pumps and their components. This paper addresses the multi-period (e.g. 24-hours time horizon) optimization of pumping systems. To this end, we have developed a simulation-based optimization approach including novel relevant technical features of a generic but realistic pumping system, namely cavitation and overflow. The proposed multi-period optimization differs further from the classic static optimization (i.e. at the design stage), proposing a new dynamic approach in which pump activation is steered dynamically for an optimal management of the variability of water inflow. Furthermore, the problem includes constraints on the number of pump activations allowed to reduce material strain. The performances of different meta-heuristic optimization algorithms (e.g. genetic algorithm, simulated annealing and particle swarm optimization) for solving the problem are compared. The numerical results show that energy savings are possible with the dynamic approach and that particle swarm optimization and simulated annealing algorithms provide the most suitable solutions for this problem. Highlights • Three algorithms are compared to minimize energy pump consumption. • The pump model includes energy, cavitation, overow and activation frequency. • Static and dynamic optimizations are investigated. • The dynamic optimization can reduce the energy consumption by 6.5%. [ABSTRACT FROM AUTHOR]

Energy extraction from renewable sources like hydrokinetic energy from the flowing water of rivers and canals is one of the affordable and clean energy generation technique. The current work is carried out towards performance enhancement of the Darrieus hydrokinetic turbine for open water channel utilization application. The investigation has been done using the flat and concave shape of blocking plate. Both blocking plates have been analyzed for different sizes as well as location at the upstream side of the turbine. The obtained results are reported after considering appropriate velocity correction. The blocking plates with projected width of 76 mm, 89 mm, 101 mm, 127 mm, 152 mm, and 203 mm are selected for the investigation. It is observed that 101 mm (Width Ratio , WR =0.36) with concave blocking plate provides maximum C p of 0.245 at 0.99 TSR. Also, the optimum region is found between 0.143 and 0.286 Distance Ratio (DR) from the top corner of the acrylic plate. The concave blocking plate enhance the performance more compared to flat blocking plate. The conclusion is made that, the performance with flat blocking plate with optimized width and location improve the power coefficient by 10.92% and that of concave blocking plate by 18.45%. • Energy extraction using Darrieus hydrokinetic turbine is one of the affordable and clean energy generation techniques. • The performance of the Darrieus water turbine has been compared with a bare rotor and with using two different types of blocking plates. • The concave and flat blocking plates have been experimentally analyzed, and its effect has been explored in the paper. • The different sizes of concave and flat blocking plates were placed at the upstream side of the Darrieus turbine to enhance the performance. • The paper also includes the optimum region of the optimized shape concave and flat blocking plates placed at the upstream location of the rotor. [ABSTRACT FROM AUTHOR]

Energy conservation in a highly resource restricted environment of Wireless Sensor Networks (WSNs) is a crucial task. This issue can be efficiently tackled by adopting the mechanism of clustering in sensor networks. The primary objective of any of the designed clustering protocols for WSNs is to obtain energy efficiency and to lengthen the network life duration. This achievement is made through the election of a single deserving node as a head node called cluster head. This paper suggested an evolutionary approach based clustering protocol named Modified-Invasive Weed Optimization Based Clustering Algorithm (M-IWOCA) for WSNs. M-IWOCA focuses on the selection of fittest node as a cluster head to enhance the network's lifetime as well as to address the issue of energy conservation in sensor networks. A fuzzy inference model is designed to evaluate the fitness of each node in the network. Simulation results for M-IWOCA depict significant reduction in dead nodes per round and results in minimizing the energy utilization of the sensors. Moreover, M-IWOCA enhances the network stability period by 45% in comparison to Artificial Bee Colony (ABC) protocol and by 18% in comparison to Quantum Artificial Bee Colony (QABC) protocol. [ABSTRACT FROM AUTHOR]

Research from economics and psychology suggests that behavioral interventions can be a powerful climate policy instrument. This paper provides a systematic review of the existing empirical evidence on non-price interventions targeting energy conservation behavior of private households. Specifically, we analyze four nudge-like interventions referred to as social comparison, commitment devices, goal setting, and labeling in 44 international studies comprising 105 treatments. This paper differs from previous systematic reviews by solely focusing on studies that permit the identification of causal effects. We find that all four interventions have the potential to significantly reduce energy consumption of private households, yet effect sizes vary immensely. We conclude by emphasizing the importance of impact evaluations before rolling out behavioral policy interventions at scale. [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]

The use of high temperature heat pumps (HTHPs) operating with natural fluids has been shown to be a potential environmentally friendly solution to increase energy efficiency in industrial processes. Industrial processes release a significant amount of energy as low quality waste heat to the environment. This paper reviews the research and development of efficient and cost effective HTHP technology that can utilize this waste heat. Natural fluids are of focus with consideration given to the comparable technologies using synthetic fluids. This review reveals the different challenges from fluid selection, component development to system optimization. The various innovative solutions to these challenges and promising technologies for further studies are discussed. The purpose of this paper is to serve as a start point for research by bringing together ideas, simulations and experimental results as a resource or reference tool for future development in HTHP using natural working fluids. [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]

The cost of heat savings in buildings increase as more heat savings are achieved and hence, alternatives other than savings typically become more economically feasible at a certain level of heat reductions. The challenge addressed in this paper is to identify when the cost of heat savings become more expensive than the cost of sustainable heat supply, so society does not overinvest in heat saving measures. This study first investigates the heat saving potentials for different countries in Europe, along with their associated costs, followed by a comparison with alternative ways of supplying sustainable heating. Furthermore, the levelised cost of supplying sustainable heat is estimated for both a single technology and from an energy system perspective. The results are analysed by assessing various parameters such as socio-economic costs and energy efficiency improvements in the national energy systems. The results demonstrate the economically feasible levels of heat savings and heat production for various European countries, highlighting differences in their national conditions and energy systems. The findings in this paper indicate that overinvestments in heat savings can be avoided by saving heat until a level around 30–50% of projected heat demands and supplying the remaining heat demand with sustainable heat sources. [ABSTRACT FROM AUTHOR]

This paper aims to present a novel smart grid adaptive energy conservation and optimization engine for smart distribution networks. The optimization engine presented in this paper tries to minimize distribution network loss, improve voltage profile of the system and minimize the operating cost of reactive power injection by switchable shunt Capacitor Banks using Advanced Metering Infrastructure data. Moreover, it performs Conservation Voltage Reduction (CVR) and minimizes transformer loss. To accurately weight the optimization engine objective function sub-parts, Fuzzification technique is employed in this paper. Particle Swarm Optimization (PSO) is applied as Volt-VAR Optimization (VVO) algorithm. Substantial benefits of the proposed energy conservation and optimization engine include but not limited to: adequate accuracy and speed, comprehensive objective function, capability of using AMI data as inputs, and ability to determine weighting factors according to the cost of each objective sub-part. To precisely test the applicability of proposed engine, 33-node distribution feeder is used as case study. The result analysis shows that the proposed approach could lead distribution grids to achieve higher levels of optimization and efficiency compared with conventional techniques. [ABSTRACT FROM AUTHOR]

A fundamental problem in the management of energy usage is the inability to clearly predict any possible energy saving opportunities. The cost of both under or overestimating potential returns on investment can be prohibitive to a decision maker. In recent years the simulation of energy usage using existing manufacturing simulation tools has increased in popularity among researchers, but it is decision makers who need to see the benefits of this discipline. This paper proposes an interactive manufacturing energy management toolkit which makes use of existing productivity simulation models for the prediction of energy usage. An interactive Microsoft ® Excel ® based toolkit is developed to control Lanner's WITNESS ® discrete-event simulation software using Microsoft ® Visual Basic ® for Applications. The toolkit has the ability to predict potential areas where energy saving opportunities can be made within a complex manufacturing line, and is accessible from management presentations and proposals. The interactivity of the toolkit provides an environment which facilitates efficient hypothesis testing. The paper includes an industrial case study where the approach was used to quantify theoretical savings from certain energy usage reduction scenarios within a complex automotive engine manufacturing line. [ABSTRACT FROM AUTHOR]

Big data applications have become increasingly popular with the appearance of cloud computing and green computing. Therefore, internet service providers (ISPs) need to build data centers for data storage and data processing under the cloud service pattern. However, data centers often consume a significant amount of energy and lead to pollutant emissions. In recent years, the high energy consumption and environmental pollution of data centers have become a pressing issue. This paper reviews the progress of energy-saving technologies in high-performance computing, energy conservation technologies for computer rooms and renewable energy applications during the construction and operation of data centers. From multiple perspectives of energy consumption, cost reduction, and environment protection, a comprehensive set of strategies are proposed to maximize data centers’ efficiency and minimize the environmental impact. This paper also provides energy-saving trends for data centers in the future. [ABSTRACT FROM AUTHOR]

Coal mining not only produces, but also consumes a large amount of energy. Coal production has an extremely high energy efficiency potential, and benchmarking is critical to discover this potential. To address problems such as ambiguity of coal production (e.g. underground mining), benchmarking range and absence of both indicators and standards for energy efficiency benchmarking, this paper makes use of product-based and process-based benchmarking. These two techniques are used to construct a benchmarking system for coal production with high energy efficiency, and improve the standards used at the eight coal mines owned by the Yankuang Group. Comparison and analysis of benchmarking in enterprises indicates that energy use during raw coal production could be reduced by 22.77%. Across China energy savings from coal production could reach 15.98–32.98 Mtce, with an equivalent 42–87 Mt of CO 2 emissions saved. Lastly, this paper provides measures to improve coal production energy efficiency. [ABSTRACT FROM AUTHOR]

Significant increases in industry energy efficiency are crucial for the transformation of the world's energy systems. Many production sites offer high energy savings capabilities, and if these are accompanied by short periods of economic amortization, companies should be willing to act. This case study provides a novel and extended energy assessment for plastics processing plants including primary energy, greenhouse gas emissions, and energy costs. The research distinguishes between the standard form of separate individual energy assessments and provides a more innovative holistic approach taking all relevant energy flows within the production system into account. Dynamic simulation offers a quick and effective way to predict the results of the possible energy saving measures highlighted in this analysis. The paper presents validated energy consumption simulations based on realistic processing conditions for two injection molding factories in different climatic zones. The results show that combining a number of separate energy saving measures can reduce the primary energy demand by around 26% for a German plant under temperate climate conditions and 20% for a Western Australian plant under Mediterranean conditions. However, when the separate energy saving measures are holistically combined the reduction in energy use significantly increases to 41% and 43% respectively. This holistic energy strategy involves incorporating better cogeneration and waste heat recovery options. For small and medium sized companies in particular major energy infrastructure investments may often be considered too expensive without examining the extended benefits from a holistic energy assessment perspective. In contrast, a holistic framework, like the one suggested in this paper could provide a number of new options for increasing energy efficiency that individually might normally not be accepted under conventional economic rate of return analysis. [ABSTRACT FROM AUTHOR]

Legislation targeting business carbon emissions typically excludes the significant portion of the economy comprised of small- and medium-sized enterprises (SMEs). As an alternative many governments have developed voluntary programs to assist SMEs to reduce emissions and increase their energy efficiency. To maximise benefits associated with such programs, this paper seeks to provide insights into key factors contributing to the design of successful voluntary energy efficiency programs for SMEs. This is achieved by comprehensively analysing the factors that impacted the uptake of energy savings measures by 202 SMEs which participated in the ClimateSmart Business Cluster Program (commencing in 2009). Expanding on previous research that has mostly focus on identifying inhibiting factors (barriers) to the uptake of energy savings measures, this paper offers a comprehensive assessment of barriers and motivating factors (motivators). A unique finding of this research is that SMEs experienced many different barriers and motivators while participating in the program, inferring great complexity to achieving the critical aim of reducing carbon emissions. Based on these findings, this paper argues that voluntary government energy efficiency programs should be flexibly designed and implemented to accommodate the many and various barriers. Motivating factors should be emphasised and barriers identified upfront so that the program can be tailored to the often idiosyncratic needs of SMEs. [ABSTRACT FROM AUTHOR]

A sustainable energy system can be treated as a development of the distributed generation concept. It meets energy demands locally from renewable energy or/and high-efficiency polygeneration production technologies, and is characterized by energy and cost efficiency, reliability, and environmental-friendliness. Distributed energy systems typically use renewable energy resources to supply all energy demands, such as heat, cooling, and electric power in an integrated way. However, it seems that too much emphasis is placed on power and associated renewable energy-based power technologies for dealing with sustainability issues in public discussion and the research community. Often, equally important thermal energy (heat and cooling) and polygeneration are ignored. Polygeneration is an energy-efficient technology for generating simultaneously heat and power as well as other energy products in a single integrated process. Energy efficiency contributes significantly to CO 2 emission reduction. This paper discusses the role of polygeneration in a distributed energy system and the contributions of polygeneration to the development of sustainable energy systems. The paper also stresses that efficient decision support tools for sustainable polygeneration systems are important to achieve sustainability. First, the joint characteristic of a polygeneration plant that defines the dependency between different energy products is reviewed. Then, typical methods for dealing with polygeneration systems are reviewed. The review attempts to highlight the complexity of polygeneration systems and potential of polygeneration systems to adjust output of different energy products. Next, the challenges of sustainable polygeneration energy systems are discussed. Then some practices for operating polygeneration plants are discussed. [ABSTRACT FROM AUTHOR]

The expected savings from energy efficiency projects are divided into two, direct savings and indirect savings. Direct savings refer to savings obtained through the personal effort of an individual implementing some energy efficiency measures. Indirect savings are achieved through information transmission of energy efficiency measures from an individual to his/her neighbours. In this paper information transmission is seen as human contribution for energy savings through interactions within the social network. This paper formulates a mathematical model that calculates an expected energy cost savings model that consists of direct and indirect savings. Indirect savings are made through social interactions of people in a network over time. Direct savings calculations are based on the Homeflex time of use tariff of South Africa. A case study of thirty-six households is used to illustrate the impact individuals have on the rest of their network in transferring information about the energy efficiency measures they have implemented. The results show that social interactions can improve energy efficiency savings and consequently reduce electricity cost. [ABSTRACT FROM AUTHOR]

Energy conservation in the real estate sector is claimed to possess significant possibilities for viable climate mitigation actions. Adopting the property investor's perspective, this paper focuses on financial performance of energy audit investments of existing office buildings. The study uses four property investment methods for assessing the financial performance of these investments. First, the paper adopts the traditional approach for assessing the profitability of an energy conservation investment: payback period, internal rates of returns and returns on investments of energy efficiency investments. Secondly, the scope is moved from energy investment to the property level and discounted cash flow (DCF) method is used to analyze the influence of the investments on the actual property value, something that has not been studied enough. The results reveal genuine financial advantages of energy efficiency investments at the building portfolio level, highlighting positive impacts on the property values of ca. 2.5 percent on average. Yet, the benefits of energy efficiency investments are currently not easily reached nor realized by investors. This is at least partly due to the mechanisms of distributing the potential returns of the investments between stakeholders, the lack of qualified service providers and poor understanding of overall value of energy conservation investments. [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]

In this paper, four energy control strategies are proposed and analyzed for the standalone Renewable/Fuel Cell Hybrid Power Source (RES/FC HPS). The concept of the load following (LF) and Maximum Efficiency Point Tracking (MEPT) is used to control the fueling rates. A standalone RES/FC HPS uses at least one Renewable Energy Sources (RES) and a Polymer Electrolyte Membrane (PEM) Fuel Cell (FC) as backup source. Photovoltaic (PV) array and wind turbines (WT) farm are used as RES and the surplus of energy during light load stages is stored in hydrogen tank via water electrolysis to fuel the PEMFC. Small-scale RESs and commercially available PEMFCs are interfaced to the common DC bus via power converters and then to the single-phase distribution grid through a voltage source inverter. RES/FC HPS seem to be an efficient alternative for supplying smart houses and isolated sites. This paper proposes a new supervision strategy of the Energy Management Unit (EMU) based on the LF control approach that assures a charge-sustaining (CS) mode for the Energy Storage System (ESS). So, the capacity of the batteries stack can be reduced at minimum if it is directly connected to the DC bus. The ultracapacitors stack compensates dynamically the power flow balance on the DC bus, regulating the DC voltage via a bidirectional buck-boost power converter. Thus, a semi-active hybrid topology is adopted for the ESS having the batteries stack. The MEPT loops ensure an optimized energy management of the RES/FC HPS. The LF strategy designed based on the power flow balance guarantees the load demand through the efficient management of the power flow from RES, FC and ESS, adapting FC energy production to load profile. The FC energy production is controlled via the fueling rates (one is controlled in the LF loop and the other is controlled in the MEPT loop) to maximize the energy consumption indicator: the ratio of the produced energy and the fuel consumed by the FC system during a load cycle. Thus, this paper evaluates the control performances of the four control topologies to fuel the FC stack during an variable RES and load profile. The MATLAB-Simulink® software package is used to model the RES/FC HPS and develop the four EMU strategies. Simulation results shown comparatively the performance of the EMU strategies proposed under different scenarios of RES power generation and load demand. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model is formulated to quantify the social impact an individual has on his/her community when he/she performs any energy efficiency project and transmits that information to his/her neighbours. This model is called the expected power savings model; it combines direct and indirect expected power savings of the energy efficiency project for each individual within the network. The indirect savings are quantified through the social interactions people in the network. The example used in this paper illustrates the effectiveness of the model by identifying the households who should have free solar water heaters installed in their residential houses based on their influence through interactions in their community. Two case studies are considered in this paper, single and multiple sources case studies. In the multiple source case study, the results show that it is not necessarily the people with the highest connections who provide the maximum expected power savings. [ABSTRACT FROM AUTHOR]

This paper describes the results of energy efficiency enhancement in 23 numbers of 210 MW coal fired power plants spread over India. Energy efficiency improvement of major auxiliary equipment with different plant load factors are summarized here with improved performance. The effect of plant load factor on all major auxiliary equipment and improvement in performance of auxiliary equipment are discussed in this paper. Operation of the plant at improved plant load factor reduced the specific auxiliary power from 11.23% at 70% PLF to 8.74% at 100% PLF that reduced the net auxiliary power by 9.1 MU/year that is an equivalent reduction of CO2 emission by 9500 t/year. Optimizing the excess air, controlling the furnace ingress, enhanced energy efficiency of individual equipment by proper maintenance, etc., improves the plant capacity and reduces the overall auxiliary power by about 1.5-2.1% of gross energy generation i.e., equivalent CO2 reduction of 23,000-32,400 t/year and release an additional power of about 3.5 MW (for a typical one 210 MW power plant) into grid. [ABSTRACT FROM AUTHOR]

Multistage centrifugal pumps are widely used, and improving their efficiency is an indispensable part of energy conservation. A multi-objective optimization method combining experimental design, surrogate model, and optimization algorithm is proposed to re-design impellers and diffusers for improving pump performance. In the paper, nine variables were selected by the Plackett–Burman design with the head and minimum efficiency index (MEI) as the optimization objectives. The Gaussian process regression (GPR) was used to establish the surrogate model, and multi-objective optimization of the impeller and diffuser was carried out by non-dominated sorting genetic algorithm II (NSGA-II). The optimization results show that head and efficiency at the designed point 1.0 Q d increased by 8.8% and 2.8% respectively, and C MEI decreased by 1.34%. Meanwhile, the energy loss and flow characteristics of the original and optimization models were analyzed with the entropy production theory. Compared with the original model, the energy loss was reduced, and the flow in the interaction area between the impeller and diffuser becomes more stable for the optimized model. Moreover, the influencing mechanism of the pump geometrical parameters on the hydraulic performance and flow characteristics were discussed and analyzed. • A PB-GRP-GA multi-objective optimization method is proposed. • Internal energy losses were identified by Entropy Production Rate. • Influence mechanism of geometry on performance was revealed. • Higher MEI of pump model was achieved and verified by experiments. [ABSTRACT FROM AUTHOR]

The energy conversion efficiency of coal utilization is a focal point in modern energy management practices and in academic literature. This paper explores life cycle energy efficiency of coal (LEEC), which encompasses six distinct stages from the design of coal mines to the comprehensive reuse of resources. First, the study analyzes improvements to the evaluation of efficiencies in energy systems. Secondly, it proposes a multi-stage energy efficiency analysis and constructs an innovative LEEC model for coal exploitation and utilization. Thirdly, the energy efficiency of coal exploitation and utilization was evaluated, and found that total efficiency in China increased from 33.11% in 2010 to 37.69% in 2014, saving 126 Mtce of energy. Finally, this study found that mine design is the most important stage in improving energy efficiency, followed by the coal processing stage. Moreover, we found that coal processing has an indirect contribution to other stages in the life cycle utilization of coal, such as reducing transportation capacity. The primary research contribution is the development of a comprehensive LEEC model for the entire life cycle of coal, rather than just single-stage evaluation. This lays the foundation for further studies on energy efficiency of industrial chains and across entire systems. • Exploration of energy efficiency across the entire coal life cycle. • The energy efficiency of coal exploitation and utilization increased annually. • Analysis shows the implicit contribution of coal processing to life cycle. • Mine design is a crucial stage for overall life cycle energy efficiency. [ABSTRACT FROM AUTHOR]

The global construction industry is expected to experience an average growth of 3.6% annually in construction outputs throughout 2018 to 2022. The surge of new building developments will create substantial demand for energy and therefore run the risk of higher carbon emissions. With the rising concern over climate change, it is imperative for buildings to have energy-saving strategies in place. Many research has discussed the use of energy efficient technologies as a solution, but overlook the role of energy-saving behaviour during the post-occupancy stage. Occupants' energy-saving behaviour is important in ensuring the optimisation of building technologies. A large part of human behaviour is characterised by habit, which is learned sequences of an act that have become automatic responses to specific ques and are functional in meeting certain needs. The study aims to establish the link between the behaviour of building occupants and their underlying habits. Adopting the Habit Theory as a premise, the study formulates a framework on strategies for behaviour change interventions that captures the underlying motivations to exhibiting energy-saving behaviour. The Effective Theory-Building design process was applied, which engages an axiomatic system to purposefully generate theory, evaluate its utility, and provide an effective representation of the observed phenomena. The theoretical framework addresses how energy-saving behaviour is cultivated through conditions of habits. This shows that the building occupant's behaviour is important for enabling energy efficiency and that it can be construed and explained by repetitive habitual actions of energy-saving practices. To have the greatest effect on a building's energy performance, building managers must examine the nuanced ways that habitual actions may shape the occupants' energy-saving behaviour and consider intervention strategies for changing habits. The paper provides a deeper understanding of building occupants' energy-saving behaviour from a sociotechnical perspective and creates a paradigm for future studies of building energy management. [ABSTRACT FROM AUTHOR]

Graphical abstract Decreased energy usage for the same grind size and therefore: lower wear rate of replaceable components and lower operating cost. Highlights • Cylindrical shaft spacers are used to separate the IsaMill™ grinding discs. • Alternative conical spacers have now been tested at lab, pilot and full scale. • In an operating IsaMill™, the new configuration reduced specific energy by 13–17%. • Further specific energy savings are possible at finer grind size targets. • The benefit can be realised as finer grind size or decreased power consumption. Abstract The IsaMill™ was specifically developed to address the energy efficiency issues associated with grinding to fine and ultrafine sizes. It has been doing this successfully for nearly 25 years in more than 125 installations. Recent efforts by Glencore Technology to further improve the energy efficiency of the IsaMill™ have resulted in the development of a new IsaMill™ shaft spacer design. The spacer was developed through laboratory, pilot and full scale testing prior to being commercialised. Full-scale results indicate that the new configuration was able to reduce the specific energy consumption by 13–17% in an M1000 gold application grinding to a P80 of 18 µm. The spacers were also shown to have no adverse impact on the shape of the product particle size distribution. This paper discusses the development process of the new spacers through lab, pilot and full scale trials, operating results and processing implications. [ABSTRACT FROM AUTHOR]

Highlights • Examine the coal use, CO 2 and pollutant emissions characteristics of China's wind-coal power system. • Model the impacts of wind penetration on them with high resolution output data. • Suggest future dispatch study from economical and environmental perspectives. Abstract China's power supply structure is dominated by coal-fired power. As China's renewable power expands, coal-fired power units are required to improve flexibility to balance power system. However, more flexible operation of coal power units increases energy consumption and pollutant emissions. This paper examines the energy efficiency, CO 2 and pollutant emissions characteristics of China's generic wind-coal combined power generation system, and discusses pollution-minimizing dispatch strategies by modeling three hypothetical scenarios of wind-coal combined power generation systems. For day-scale analyses, we find expected displacement rates of coal consumption and CO 2 emission decrease by wind fraction rate, indicating reduced energy savings from wind power per unit of increase in wind capacity. For NO x emission, we find that expected displacement rate reaches maximum value of 112% when wind fraction rate is equal to 0.27.For week-scale analysis, we simulate the coal consumption rate and emission factors with and without an operation of shutdown and startup of coal power units in the system. We suggest future study on dispatch decisions of startup/shutdown of coal power units to optimize power generation economically and environmentally. [ABSTRACT FROM AUTHOR]

Abstract With the continuous development of wireless networks, energy conservation and energy efficiency are becoming key factors in improving the network lifetime. In multi-antenna wireless networks, the energy conservation problem can be addressed using the trade-off between the transmit power and the circuit energy consumption. In this paper, we propose a cross layer protocol, MAC-LEAP, that selects the best transmission policy based on Multiple-Input Multiple-Output (MIMO) in both single-hop and multi-hop wireless networks. Various data transmission algorithms are presented in which many factors are considered in order to find the best transmission policy between each pair of nodes. An RTS/CTS handshake is used to exchange the required information to select the best transmission policy prior to data transmission. Moreover, we introduce a MIMO-based framework in Network Simulator 3 (ns-3) in which the wireless nodes may be equipped with more than one antenna. Using extensive simulations in ns-3, we compare the performance of MAC-LEAP with traditional protocols in terms of the network lifetime and the number of received packets. The simulation results show that MAC-LEAP outperforms the traditional protocols in both single-hop and multi-hop networks for various transmission distances and target Bit-Error-Rates (BER). [ABSTRACT FROM AUTHOR]

Abstract In this paper, energy efficiency for cooperative spectrum sensing in cognitive radio network is investigated and optimized. The novel mathematical formulation of energy efficiency maximization problem by considering number of secondary users, sensing time, and transmission time as design parameters with protection of primary user from SU transmission has been done. In order to solve the formulated problem, first the optimal expression for number of secondary users is formulated, then, an iterative sub optimal algorithm is proposed to obtain optimal sensing and transmission time. Numerical results and illustrative plots demonstrate the correctness and optimality of the proposed algorithm and show the improved performance over the state of arts. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the role of passive design strategies and using biogas in reducing energy consumption, annual energy cost and CO 2 emissions of a new productive country housing model in an ongoing sustainable community development project near Cairo, Egypt. The country housing character follows the vernacular architecture of such hot arid areas through the application of courtyards, vaults and domes with two different materials for the building envelop. The traditional 25 cm red bricks were used in the first case, whilst the second sustainable one is a prefabricated sandwich panel construction of 15 cm GRC walls. The opportunity of using 2 m3 biogas reactors is promising in such housing projects that have an area for raising domestic animals along with the waste supplies from each house agriculture zone. Design Builder simulations took place in present and future showed considerable reductions of energy consumption, annual energy cost and CO 2 emissions estimations in the sustainable option with the biogas passive house. [ABSTRACT FROM AUTHOR]

Highlights • Non-intrusive techniques are proposed to infer occupancy from existing HVAC sensors. • Reheat energy use is reduced by more than 38% with better nighttime setback schedules. • Derived a comprehensive set of candidate anomalous zones using unsupervised learning. • Proposed approach can be readily applied to any commercial building with a BMS. Abstract The Heating Ventilation and Air Conditioning (HVAC) system of commercial buildings traditionally runs on a fixed schedule that does not take occupancy into account despite its huge variation over space and time, thereby wasting a lot of energy in conditioning empty or partially-occupied spaces. Occupancy information is essential to eliminate wasteful energy use with imperceptible impact on building operations and human comfort. This paper investigates the application of non-intrusive techniques to obtain a rough estimate of occupancy from coarse-grained measurements of sensors that are commonly available through the building management system. Various static and adaptive energy-efficient schedules are developed based on this approximate knowledge of occupancy at the level of individual zones. Our experiments in three large commercial buildings confirm that the proposed techniques can uncover the recurring occupancy pattern of the zones, and schedules that incorporate these occupancy patterns can achieve more than 38% reduction in reheat energy consumption while maintaining indoor thermal comfort. [ABSTRACT FROM AUTHOR]

Abstract Within the context of the controversial use of the concept energy intensity to assess national energy performance, this paper proposes an innovative accounting framework: the energy end-use matrix. This tool integrates quantitative assessments of energy use of the various constituent compartments of socio-economic systems. More specifically it identifies, moving across levels of analysis, what compartments (or sub-compartments) are using what type of energy carriers for what type of end-use. This analysis is integrated with an assessment of labor requirements and the associated flows of value added. The end-use matrix thus integrates in a coherent way quantitative assessments across different dimensions and hierarchical scales and facilitates the development of integrated sets of indicators. In this way it contributes to a multi-criteria characterization of national or sectoral energy performance. The tool is illustrated with an analysis of three EU countries: Bulgaria, Finland and Spain. Challenges to improving the usefulness of biophysical analysis of the efficiency of the industrial sector are identified and discussed. Increasing the discriminatory power of quantitative analysis through better data standardization by statistical offices is the major challenge. Highlights • The energy end-use matrix is a tool to study national and sectoral energy performance. • It combines qualitative and quantitative variables into a multi-scale assessment. • It bridges top-down (national statistics) and bottom-up (technical) information. • Its use is validated by comparing the industrial sectors of Bulgaria, Finland & Spain. • The end-use matrix readily identifies the major determinants of energy performance. [ABSTRACT FROM AUTHOR]

Improving energy efficiency helps achieve energy conservation and emission reduction. Examining whether China's SO2 trading emission system (TES) reform can enhance energy efficiency will provide empirical evidence for the institutional benefit of market-oriented environmental regulation in environmental governance. This paper employs the difference-in-differences (DID) method to examine the effect of SO2 TES on energy efficiency using panel data from 285 Chinese cities from 2003 to 2018. The empirical results indicate that: (1) SO2 TES significantly promoted green total factor energy efficiency and reduced energy intensity. This conclusion is still valid after the prerequisite assumption test and robustness test. (2) SO2 TES significantly promotes local energy efficiency and has significant spatial spillover effects on surrounding cities. (3) Promoting green technological progress, resource allocation, and curbing energy consumption, are the primary mechanisms for SO2 TES to improve energy efficiency. (4) SO2 TES's improvement in energy efficiency comes more from eastern, developed, small, resource-based, and non-old industrial cities. • SO2 trading emissions system (TES) improves energy efficiency. • TES has a spatial spillover effect on nearby cities. • Green innovation, resource allocation and energy saving effects are the channels. • The effect of the TES on energy efficiency is heterogeneous. [ABSTRACT FROM AUTHOR]

Fifteen years after the publication of the article entitled "Energy Education: breaking up the rational energy use barriers" in 2004, what were the paths taken and scientific contributions made towards a rational energy use as regards energy education? This paper aims to answer this question by collecting data on the Web of Science database to identify publications citing the aforementioned article using different levels of approach. The selected papers were structured in clusters utilizing software for such a purpose, which allowed organizing and listing reviewed works from which a cluster of keywords has been structured to identify the most frequently cited terms. Once found, the following step was to perform a content analysis to allow organizing authorship and contributions. During this process, the term "barriers" in the context of rational energy use was not restricted to its class, but it was present in the analysis of other terms that constitute other classes. Energy education is presented as one of the ways to make society more aware and active while taking actions towards rational energy use. However, to achieve greater effectiveness of such an educational process, the human aspect requires special attention through a clearer definition of personal values, attitude, and behaviour because of its importance for activities aimed at energy issues. • Energy education is crucial for energy rational use. • Other approaches for energy education were identified. • Individual's psyche influence on energy rational use. • Several barriers permeate energy and its use. • Energy education enables energy planning. [ABSTRACT FROM AUTHOR]

In recent years, smart cities have emerged with energy conservation systems for managing energy in cities as well as buildings. Although many studies on energy conservation systems of smart homes have already been conducted, energy management at the city level is still a challenge due to the various building types and complex infrastructure. Therefore, this paper investigated the research themes on smart homes and cities through a quantitative review and identified barriers to the progression of smart homes to sustainable smart cities through a qualitative review. Based on the results of the holistic framework of each domain (smart home and city) and the techno-functional barriers, this study suggests that the following innovative solutions be suitably applied to advanced energy conservation systems in sustainable smart cities: (i) construction of infrastructure for advanced energy conservation systems, and (ii) adoption of a new strategy for energy trading in distributed energy systems. Especially, to reflect consumer behavior and energy in sustainable smart cities, the following responses to future research challenges according to the "bottom-up approach (smart home level to smart city level)" are proposed: (i) development of real-time energy monitoring, diagnostics and controlling technologies; (ii) application of intelligent energy management technologies; and (iii) implementation of integrated energy network technologies at the city level. This paper is expected to play a leading role as a knowledge-based systematic guide for future research on the implementation of energy conservation systems in sustainable smart cities. Image 1 • In terms of energy technology, a connection between smart home and city is lacked. • Through quantitative review, research themes on smart home and city are identified. • Through qualitative review, barriers of progression to smart cities identified. • Bottom-up approach for energy conservation system in smart city is proposed. [ABSTRACT FROM AUTHOR]

Within the building sector, schools have a major social responsibility because of their educational purpose. With the aim of providing a novel energy modelling process to evaluate the real energy performance of school buildings and potential energy savings, minimizing input data collection, this paper presents a new energy assessment method to support the decision-making process towards low-carbon energy schools. The novelty of this method is based on the integration of a coherent set of assumptions and procedures with respect to boundary conditions of schools, derived from their modular basis, common building configuration and space uses, and the model's iterative calibration procedure, based on real building performance, which achieves a high final accuracy. With a reduced set of inputs, hourly dynamic simulations can be performed. The method, integrated in the SchoolEnergy-ACT tool, was tested in two pilot schools. The results show that the method properly fits to schools' energy consumption profiles with high accuracy levels through calibration processes using energy bills, ensuring its feasibility for simulating the energy performance of schools, enabling comparison with other buildings, and informing end-users of potential energy savings. The accuracy of the model can be improved with an iterative, self-learning procedure and detailed energy data. [ABSTRACT FROM AUTHOR]

Tubular Daylight device (TDD) and solar water heater (SWH) are two power saving solutions that are commonly employed individually in residential and industrial premises. This paper proposed a novel merged power saving system consisting of TDD and SWH in one model, which is the first attempt to integrate these two systems. The idea of merging the TDD with SWH is based on utilizing the existing area around the TDD to implement the SWH around the TDD tube through a serpentine collector. The main purpose for such integration is to enhance solar energy saving, space area saving, and to decrease the fabrication cost. The illumination and thermal performance of the new proposed model were tested and analysed experimentally in different seasons in Cairo - Egypt to assess its performance in practical use. The obtained results indicated that the merged system succeeded in transferring an acceptable illumination rate and increasing the water temperature. The transferred internal illuminance has reached approximately to 6.5 W/m 2 that fulfils the required needs of lighting. Additionally, the system increased the water temperature up to 62 °C, with a performance instantaneous efficiency that reached 21.17% which is very satisfactory. Furthermore, the performance of thermosyphon SWH with different serpentine collector coil number of turns has been evaluated. The results proved that, the collector number of turns has significantly affected the SWH performance in a directly proportional relation. [ABSTRACT FROM AUTHOR]

Due to the rapid rise of power consumption of data centers in recent years, much work has been done to develop energy-efficient design, controls and diagnosis of their cooling systems, while the energy system simulation is used as an effective tool. However, existing models of information technology (IT) equipment of data centers cannot well represent the effects of IT equipment design and operation status on the data center cooling demand, and this hinders the development of the energy saving cooling technologies of data centers. To address this issue, this paper introduces a power consumption model of IT equipment in data centers with coefficients and modeling script provided for immediate use in data center energy system simulation. This energy model can be used to simulate energy performance of typical IT equipment in data centers under real-time dynamic operation conditions conveniently and effectively without the need of data other than the specifications of a data center design and IT equipment manuals. Its use with a commonly used building simulation program is demonstrated with a building model of a typical large office in a subtropical area. The results show that the model can represent the change of power consumption of data centers with different IT equipment designs and operation appropriately. [ABSTRACT FROM AUTHOR]

The energy-saving and emission-reduction performance of electric vehicle is closely related to its charging method and operation mode. In order to enhance the energy-saving and emission-reduction effect of electric vehicles, this paper develops a real-time battery swap pricing model for electric taxis in China from the perspective of system. The charging and swapping system covers various stakeholders who have significant impacts on battery swap pricing. So the proposed model includes five modules: power grid load monitoring, generator set dispatch, battery swapping station operation, electric taxi driver response and evaluation of all stakeholders' benefits. To reduce the carbon emissions of electric taxis' energy source and maximize the global benefits to all stakeholders, authors consider four battery swap pricing scenarios and two charging strategies for battery swapping station, and design a battery swap pricing mechanism in China according to the analysis results. The simulation results demonstrate that battery swap pricing based on a peak-valley time-of-use tariff with a decentralized charging strategy has the greatest energy efficiency and economic effects which can enhance 45371.15 kg carbon emissions reduction and 48220.86 yuan combine benefits to all stakeholders. [ABSTRACT FROM AUTHOR]

Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled from occupant influence. Furthermore, optimization usually presupposes existence of a detailed dynamics model for the hot water system. These assumptions lead to suboptimal energy efficiency in the real world. In this paper, we present a novel reinforcement learning based methodology which optimizes hot water production. The proposed methodology is completely generalizable, and does not require an offline step or human domain knowledge to build a model for the hot water vessel or the heating element. Occupant preferences too are learnt on the fly. The proposed system is applied to a set of 32 houses in the Netherlands where it reduces energy consumption for hot water production by roughly 20% with no loss of occupant comfort. Extrapolating, this translates to absolute savings of roughly 200 kWh for a single household on an annual basis. This performance can be replicated to any domestic hot water system and optimization objective, given that the fairly minimal requirements on sensor data are met. With millions of hot water systems operational worldwide, the proposed framework has the potential to reduce energy consumption in existing and new systems on a multi Gigawatt-hour scale in the years to come. [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]

This paper presents the methodological approach and findings of a simulation study of advanced energy conservation, generation and management technologies applied to two case study dwellings in the UK, so as to achieve net zero energy (NZE) target that includes a reduction of net regulated energy (HVAC) to 0 kWh/m 2 per year and energy generation of at least 50 kWh/m 2 per year. The performance of the dwellings are also tested for a change in energy use and risk of summertime overheating in future climates in the short (2030s), medium (2050s) and long term (2080s). The findings indicate that to meet the NZE targets, regulated loads need to reduce by about half (over current Building Regulations) with community (rather than building-level) renewables playing a major role. It is also found that the NZE targets, given current regulations, are not particularly difficult to achieve in design with regard to energy efficiency but are highly expectant with regard to renewable energy. Further, summertime overheating is projected to be a risk for net zero energy dwellings by the 2050s. Despite this the regulated energy use of both dwellings is projected to reduce by 11 kWh/m 2 /yr, accompanied by a small increase in renewable generation (2 kWh/m 2 /yr). [ABSTRACT FROM AUTHOR]

Australia’s commercial building stock exceeds 134 million m 2 of net lettable area, with retail buildings contributing 35% to this sector’s energy use. The energy intensity of retail buildings in hotter climates is higher than the national average, as is the energy intensity of smaller buildings (under 1500 m 2 ) that are not considered ‘high-end’ commercial properties. Little attention has been paid to improving the energy efficiency of these types of buildings through regulation (for new buildings) or through market mechanisms (for retrofitting). As many of these buildings are single storey ‘warehouse’ type buildings, their predominant heat load comes through the roof, and thus are well suited to benefit from cool roof technology. Despite this, there remains a deficiency in quantifying the benefit of such technology in the context of single-storey retail buildings in Australia. This paper reports on an experimentally validated numerical study aimed at addressing this deficiency. Results show that application of cool roof technology to a warehouse type building in a subtropical environment increases the energy efficiency by shifting space temperature towards the design set point (21–23 °C), and thus reducing cooling energy demand. This study also indicates an energy saving every month with the application of cool roof, with the largest saving in hotter months and no heating penalty in cooler months. Application of cool roof technology on warehouse style buildings across Australian buildings indicates energy savings can be achieved in all broad Australian climatic zones, with the greatest energy reduction associated with tropical, subtropical and desert environments. [ABSTRACT FROM AUTHOR]

Buildings consume substantial amounts of energy and require sophisticated control strategies to fulfill occupants' comfort requirements. In large spaces, various occupancy patterns result in uneven load distributions, requiring high-resolution occupancy information for sufficient system control. In recent years, the development of indoor positioning systems (IPS) enabled the possibility of more scientific and precise occupancy detection systems, leading to better operation of buildings' HVAC systems. This paper proposes a demand-driven control system for air conditioner control in large spaces based on IPS. The proposed system focuses on optimizing the ventilation rate based on number of occupants and their spatial distribution in an experimental space. A dual-network (Wi-Fi network and BLE network) indoor positioning system is installed to collect the occupancy data and guide the operation of Variable-Air-Volume (VAV) boxes. The energy-saving potential of the proposed system is examined with a computational fluid dynamics (CFD) model in terms of temperature distribution and energy consumption. This study also explores the interrelationship between cooling load variation and occupancy pattern under different control mechanisms. The final results show the proposed system has significant energy-saving potential by avoiding over-cooling in unevenly distributed occupancy conditions. [ABSTRACT FROM AUTHOR]

As an important driving force for energy efficiency, the digital economy plays an irreplaceable role in achieving the goal of energy conservation. Entrepreneurship, as an endogenous force driving economic growth, also has an important impact on energy efficiency. Therefore, this paper incorporates entrepreneurship into the analysis framework of industrial development, and discusses the main paths and theoretical mechanisms of digital economy affecting energy efficiency from the two dimensions of entrepreneurship's innovation spirit and entrepreneurial spirit. The current work has yielded the following results: (1) The digital economy has significantly improved energy efficiency, and after a series of robust tests, this conclusion is reliable. (2) The nonlinear regression results show that with the improvement of economic development level, the role of digital economy in promoting energy efficiency gradually increases. 3) The heterogeneity test found that the digital economy had a significant role in promoting energy efficiency in the sample of resource-based cities and central region, but this effect was not significant in the samples of eastern and western regions and non-resource-based cities. (4) Mechanism testing shows that entrepreneurship's innovation spirit is an important mechanism for promoting energy efficiency in the digital economy, while entrepreneurial spirit is not. (5) From the convergence model test, it can be seen that the regional convergence of energy efficiency objectively exists, and the digital economy has become a booster to promote its regional convergence. • The digital economy has significantly improved energy efficiency. • The effects of entrepreneurship's innovation spirit are crucial channels. • The regional convergence of energy efficiency objectively exists. [ABSTRACT FROM AUTHOR]

• The combination of active and passive strategies saves 13.5 % of the building cost. • This paper studies the economic payoff of making energy-efficient choices in a residential building over its life cycle. • This paper uses energy simulation tools along with Life Cycle Costing to study economic benefits. • This paper identifies opportunities and challenges for the realization of energy-efficient procedures. The residential building sector is very energy-intensive. With population growth and a rise in the number of homeowners, the effect is bound to worsen. A wave of green and sustainable strategies is on the rise, hoping to moderate some of the adverse effects on the environment. The construction industry is continually evolving into becoming more energy conscious. However, one of the biggest obstacles is a lack of awareness and a fear of initial costs among contractors, homeowners, and clients alike. The purpose of this research is to explore the potential of current Life Cycle Cost Analysis (LCCA) procedures as an evaluation tool for green building strategies by conducting energy simulations for different energy conservation measures (ECMs). This paper aims to establish the tradeoff between initial investment and long-term benefits for different energy conservation measures. Energy simulation models and life cycle cost models were developed. The developed models have been applied to a case of an apartment in a multi-family building. This research shows that a combination of passive and active energy conservation measures results in the lowest lifecycle cost. The results show a 13.5 % saving of the building cost employing a combination of passive design and active strategies. [ABSTRACT FROM AUTHOR]

There is a growing worldwide concern regarding emissions of energy-related greenhouse gases (GHGs). Policy, technology and human awareness provide opportunities for offsetting these effects through energy conservation, efficient appliances and solar generation in households as these have been the subject of increasing attention across the world in recent years. Solar rooftop generation, in particular, could deliver significant efficiency improvements and reductions of CO2 emissions through its diffusion, which also avoids losses in electricity transmission and distribution systems; energy efficiency contributes to the achievement of a sustainable future because it reduces the energy-infrastructure needs, increases competitiveness and improves consumer welfare; conservation would also reduce CO2 emissions in households. The purpose of this paper is to assess the combined effect of the diffusion of solar rooftop generation, energy efficiency and electricity conservation in the residential sector in Colombia. Simulation results for different policy scenarios indicate that rooftop generation, energy efficiency and conservation can together lead, under certain conditions, to important reductions in both electricity prices and emissions. [ABSTRACT FROM AUTHOR]