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Building occupant behaviour is known to be an important factor that drives building energy use and the associated carbon emissions. A substantial body of work has investigated occupant behaviour and the underlying drivers. Yet it is generally known that some buildings allow only minimal behavioural intervention, such as on/off control of lights. Other buildings allow a much higher degree of intervention, for instance through setting of temperature set-points, ventilation fan speed control, the opening/closing of windows, and blind operation. This paper explores the constraints that buildings pose to the freedom of occupants to vary their behaviour and attempts to quantify these building-specific constraints. It reviews the literature on occupant behaviour with a focus on constraints and degrees of freedom that these occupants are allowed. The concept of "occupant behavioural freedom" (OBF) is introduced to capture and quantify these constraints. Case studies are presented to show the application of the concept to real buildings, and to explore how the available occupant freedom relates to actually observed behaviour. Residential cases show a high occupant behavioural freedom, in the order of 95 %. An industrial case has a significantly lower freedom, in the order of 25 % only. At the same time, empirical data show that further constraints limit how much of this freedom can actually be used to save energy: only around 25 % in the residential case, to virtually nothing in the industrial case. • Buildings impose constraints on potential behaviour of occupants. • Occupant behavioural freedom (OBF) is building attribute that quantifies prospects of intervention. • OBF depends on degrees of freedom as well as control freedom of each system. • Impact demonstrated for residential units and industrial building. [ABSTRACT FROM AUTHOR]

The massive deployment of microgrids could play a significant role in achieving decarbonization of the electric sector amid the ongoing energy transition. The effective operation of these microgrids requires an Energy Management System (EMS), which establishes control set-points for all dispatchable components. EMSs can be formulated as classical optimization problems or as Partially-Observable Markov Decision Processes (POMDPs). Recently, Deep Reinforcement Learning (DRL) algorithms have been employed to solve the latter, gaining popularity in recent years. Since DRL methods promise to deal effectively with nonlinear dynamics, this paper examines the Twin-Delayed Deep Deterministic Policy Gradient (TD3) performance – a state-of-the-art method in DRL – for the EMS of a microgrid that includes nonlinear battery losses. Furthermore, the classical EMS-microgrid interaction is improved by refining the behavior of the underlying control system to obtain reliable results. The performance of this novel approach has been tested on two distinct microgrids – a residential one and a larger-scale grid – with a satisfactory outcome beyond reducing operational costs. Findings demonstrate the intrinsic potential of DRL-based algorithms for enhancing energy management and driving more efficient power systems. • Application of Deep Reinforcement Learning for microgrid energy management. • A nonlinear battery-loss model is used seeking a realistic approach. • A realistic control system is considered in the model for robust results. • Operational costs are reduced by 2% over previously reported work. • Energy losses in the battery are reduced by 10% in the scenarios simulated. [ABSTRACT FROM AUTHOR]

Air-cooled chillers are extensively employed to meet cooling demand in commercial and tertiary sectors. To enhance their performance during part-load operation, variable-speed drives have been integrated into compressors and condenser fans. In existing systems, condenser fans are either operated at a fixed speed or modulated to maintain a predetermined condensing pressure or temperature difference between the refrigerant and outdoor air. In the search for increased efficiency, it is worth investigating innovative control strategies aimed at minimizing energy consumption. A preliminary mapping of chiller performance at different fan speeds, loads, and operating conditions is required to achieve this goal. In this respect, this paper investigates the operation of air-cooled chillers equipped with variable-speed condenser fans, both in the case of constant- and variable-speed compressors. An ad hoc matrix test is adopted to cover appropriate ranges conditions, in terms of load and outdoor air temperatures. Performance maps are developed for a 50-kW c chiller using a 1-D simulator. As the main findings, it may be stated that (i) in the case of the variable-speed chiller, the energy efficiency ratio increases almost linearly with fan speed, resulting in an 8.8% increase when increasing the speed from the nominal to the maximum; (ii) in the case of constant-speed chillers, the system exhibits a different behavior with the cooling capacity and the energy efficiency ratio increasing with the fan speed between 380 and 980 rpm and then decreasing (slightly or sharply, at full and part load respectively) with fan speed between 980 and 1280 rpm, and a percentage increase of EER in the range 7.8–45% is observed. Also, the sensitivity of such results to the system design is investigated, analyzing a chiller equipped with a larger condenser that resulted in achieving minimum energy consumption at an optimal 980 rpm fan speed. Finally, for a constant-speed chiller serving an office building in the Mediterranean, the proposed fan control strategy could yield an electricity saving of up to 12.1% compared to the base case, confirming the potential for energy savings through optimized and system-tailored management of condenser fan speed. • The effect of variable-speed fans on the performance of air-cooled chillers is investigated. • Maps are developed for chillers with both variable-speed and constant-speed compressors. • Fan speed significantly influences the cooling capacity of constant-speed chillers. • In variable-speed chillers, it is advisable to always run the condenser fan at high speed. • The enhanced fan strategy enables 12.1% energy savings for a chiller in an office building. [ABSTRACT FROM AUTHOR]

The construction industry consumes a significant portion of global energy, with space conditioning in buildings accounting for a substantial 34% of energy usage. Notably, the energy consumption of a building is significantly influenced by its envelope. Researchers widely acknowledge that incorporating phase change materials (PCM) into the building envelope is a promising way to enhance energy efficiency and mitigate CO 2 emissions in the building sector, owing to their high latent heat capacity. However, PCM must be completely charged after each cycle to exploit its full potential. Natural ventilation is a viable technique to facilitate the charging and discharging cycle of PCM within a 24-h period. To this end, the present study utilized EnergyPlus simulations to optimize the cooling energy savings of a residential building incorporating PCM into its envelope for PCM melting temperatures, considering various ventilation strategies across 45 cities in 15 climate zones worldwide. In order to evaluate the latent heat utilization of PCM and its improvement facilitated by natural ventilation, two novel indicators, namely HS and HR, were formulated to represent the heat stored and released by PCM during a 24-h cycle, respectively. In addition, following an economic analysis of PCM integration, a comprehensive environmental evaluation was carried out, which included the carbon intensities (CI) of all fuel sources contributing to power generation. The study's findings reveal substantial energy savings across all climate zones when controlled natural ventilation is coupled with PCM, and the newly proposed indicators precisely quantify the performance of PCM in all scenarios evaluated. In the arid climate zone (A), combining PCM and natural ventilation enhances energy savings, albeit to a similar extent as using ventilation alone. However, the integration of PCM with temperature-controlled ventilation yields striking energy reductions of up to 72.8%, 85.3%, and 61% in arid (B), warm temperate (C), and snow (D) climate zones, respectively. The cost-benefit analysis reveals a minimal return period of as short as five years in climate zone C. In the same climate zone C, the in-depth environmental analysis reveals a maximal reduction of 42,004 CO2-e kg/year in carbon emissions. In conclusion, this research study demonstrated that integrating PCM with controlled natural ventilation offers a practical, sustainable, and cost-effective solution with eco-friendly and energy-efficient outcomes. • Novel indicators (HS and HR) for PCM performance evaluation in buildings. • Impact of ventilation strategies on energy consumption of PCM-integrated buildings. • PCM combined with controlled ventilation yields the best energy savings. • A minimum payback period of 5 years is achieved in economic analysis. • PCM with natural ventilation saves a maximum of 42,004 kg CO 2 e/kWh per annum. [ABSTRACT FROM AUTHOR]

Hemp-based building envelopes have gained significant popularity in developed countries, and now the trend of constructing houses with hemp-clay blocks is spreading to developing countries like Morocco. Investigating the hygrothermal behavior of such structures under actual climate conditions is essential for advancing and promoting this sustainable practice. This paper presents an in-depth experimental characterization of a commercial hemp-clay brick that has been exposed to the outdoor environment for four years, in addition to field measurements on a building scale demonstration prototype. Additionally, the study simulates 17 representative cities to assess the hygrothermal performance and energy-saving potential in each of Morocco's six existing climate zones, using the EnergyPlus engine. The experimental campaign's findings demonstrate excellent indoor air temperature and relative humidity regulation within the hemp-clay wall building, leading to satisfactory levels of thermal comfort within hemp-clay wall buildings. This is attributed to the material's good thermal conductivity and excellent moisture buffering capacity (found to be 0.31 W/mK and 2.25 g/m2%RH), respectively). The energy simulation findings also point to significant energy savings, with cooling and heating energy reductions ranging from 27.7% to 47.5% and 33.7% to 79.8%, respectively, as compared to traditional Moroccan buildings. [Display omitted] • Experimental characterization of thermal conductivity, sorption isotherm, and moisture buffering capacity of hemp bricks. • Assessment of indoor thermal comfort and energy demand in a hemp-based building across 17 cities in Morocco. • Hemp-clay bricks demonstrated excellent humidity regulation with a moisture buffer capacity of 2.25 g/m2%RH. • Hemp-clay walls can achieve energy savings ranging from 27.7%–47.5% for cooling and 33.7%–79.8% for heating in Morocco. [ABSTRACT FROM AUTHOR]

Highlights • A method is presented to engage experts to obtain domain knowledge. • Virtual sensors are created from expert knowledge and sensor data. • Automated approach selects an optimal set of real and virtual sensors. • Machine learning is used to automatically build a data-driven fault detection model. • High fault detection performance can be achieved using only a few virtual sensors. Abstract Data-driven techniques that extract insights from sensor data reduce the cost of improving system energy performance through fault detection and system health monitoring. To lower cost barriers to widespread deployment, a methodology is proposed that takes advantage of existing sensor data, encodes expert knowledge about the application system to create 'virtual sensors', and applies statistical and mathematical methods to reduce the time required for manual configurations. The approach combines sensor data points with encoded expert knowledge that is generic to the application system but independent of a particular deployment, thereby reducing the need to tailor to individual deployments. This paper not only presents a method that detects faults from measured energy data, but also (1) describes an engagement method with experts in the energy system domain to identify data, (2) integrates domain knowledge with the data, (3) automatically selects from among the large pool of potential input data, and (4) uses machine learning to automatically build a data-driven fault detection model. Demonstration on a commercial building chiller plant shows that only a small number of virtual sensors is necessary for fault detection with high accuracy rates. This corresponds to the use of only five out of 52 original sensor data points features. With as few as four features, classification F1 scores exceed 90% on the training set and 80% on the testing set. The results are implementable and realizable using off-the-shelf tools. The goal is to design with domain experts an energy monitoring system that can be configured once and then widely deployed with little additional cost or effort. [ABSTRACT FROM AUTHOR]

Highlights • Radiant wall used as TES for a heat pump coupled to a PV array. • Deterministic control concepts were optimized for radiant wall pre-cooling. • Investment in PV panels was fully exploited only under solar control strategies. • A minimum of PV nominal power was required for optimizing solar controls. • Best solar control had lower operation cost than best peak load shifting control. Abstract Thermally activated building systems (TABS) can work as thermal energy storage (TES) systems, which are useful in shifting the energy use of space cooling and heating in buildings. The present study analyses and optimizes simple deterministic control concepts for radiant wall supplied by a heat pump for cooling purposes. First, the "solar" concept was studied, which was focused on exploiting the output of a photovoltaic (PV) array. Secondly, a "peak load shifting" concept exploiting the low electricity cost and high heat pump energy efficiency during night periods was evaluated. The results showed that the "solar" concept saved between 57% and 95% in comparison to a conventional control in different PV installed capacities. Moreover, the optimized "peak load shifting" concept had lower operation cost than the conventional control with most of the PV configurations proposed. Therefore, the study showed that the investment in the PV array was fully harnessed only with specific controls. Furthermore, the "solar" control concepts were found to help achieving the goals of net-zero energy buildings by maximising self-consumption of renewable energies in the building, as well as reducing the total imported/exported energy. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air-conditioning (HVAC) are among the major energy demand in the buildings sector globally. Improving the energy efficiency of such systems is a critical objective for mitigating greenhouse gas emissions and transitioning towards renewable sources of energy supply. The interest of this paper is to explore means to increase the efficiency of HVAC systems in accommodating occupants’ behavior in real time. For instance, rooms in office buildings are not always occupied by occupants during scheduled HVAC service periods. This offers an opportunity to reduce unnecessary energy demands of HVAC systems associated with occupants’ behavior. An in-depth analysis of occupants’ stochastic behavior within an office building is conducted in this paper. A demand-driven control strategy is proposed that automatically responds to occupants’ energy-related behavior for reducing energy consumption and maintains room temperature for occupants with similar performances as a static cooling. In this control strategy, two types of machine learning methods – unsupervised and supervised learning – are applied to learn occupants’ behavior in two learning processes. The occupancy-related information learned by the algorithms is used by a set of specified rules to infer real-time room setpoints for controlling the office's space cooling system. This learning-based approach intends to reduce the need for human intervention in the cooling system’s control. The proposed strategy was applied to control the cooling system of the office building under real-world conditions. Eleven case study office spaces were selected, representing three typical office uses: single person offices, multi-person offices, and meeting rooms. The experimental results report between 7% and 52% energy savings as compared to the conventionally-scheduled cooling systems. [ABSTRACT FROM AUTHOR]

This review deals with critical issues in the development of energy-efficient windows from two fundamentally different approaches, namely, spectral selectivity and photothermal effect. This review is therefore divided into two parts. The first part reviews the engineering considerations based on an ideal window concept in terms of spectral selectivity, glazing scale, seasonal factors, and related thermal transfer. In particular, spectrally selective window designs and metal-based thin films are introduced with optimized engineering parameters and physical properties. The second part introduces a new approach of thermal insulation via the photothermal effect of the nanostructured thin films and coatings. The key that limits the heat flow through windows is the thermal insulation, which is traditionally constructed by multi-pane structures with an insulating layer. A novel concept not relying on any insulating media, but photothermal effects of nanomaterial coatings has been recently proposed and experimental verified. Both concepts of spectral selectivity and photothermal effects are introduced for energy-efficient window applications. A new direction is proposed in the development of the energy-efficient windows via the photothermal effects in various nanostructures of thin films and coatings. [ABSTRACT FROM AUTHOR]

According to its ‘Energy Strategy 2050’ (case ‘new energy policy’) Switzerland aims to reduce its industrial electricity demand by 25% and 35% in 2035 and 2050 respectively compared to 2010. Electric motor driven systems in Swiss industry, which currently account for approximately 69% of the sector’s total electricity demand, are expected to contribute significantly to this strategy. This study assesses the potential of electricity savings for electric motor driven systems in industry and its associated specific costs and presents the results in the form of energy efficiency cost curves. For the short term, the economic potential for electricity savings in Swiss industrial electric motor systems is estimated at approximately 17%. The importance of accounting for additionality by using energy-relevant investment instead of total investment for the cost-benefit analysis in order to avoid underestimation of the economic electricity savings potential is demonstrated. The results of this analysis can serve as basis for formulating more effective policies and may also be applicable to other countries with similarly ambitious targets. [ABSTRACT FROM AUTHOR]

In spite of the remarkable development of technology, most studies for building energy controls to evaluate or estimate the energy performance have not accurately reflected actual building’s energy consumption patterns. For this issue, several techniques, such as simulation and calibration, comprehensive survey system, smart metering, and commissioning, have been attempted. However, in most studies, some factors in thermal systems derived from occupant behavior were perceived as fixed objects, and the factors were converted into simple numbers as parts of inputs into simulation templates. There was lack of studies on considerations that unpredictable responses derived from human anti-logic or common sense could deteriorate energy efficiency in theoretical analyses even though the systems were properly operated. This research proposes integrated energy supply models based on artificial intelligence responding to anti-logic or common sense that can reduce machine’s energy saving effects. By use of design scenarios assuming some unusual situations, a decision making model determines the extent to which the cause of the abnormal situations are associated with the occupant behavior. After the five-step phases in the decision making model, the actual outputs of the energy supply model for the buildings are determined, and the reciprocal communication between the thermal and decision making models mitigates thermal dissatisfaction and energy inefficiency. Comparative analysis describes the decision making model’s effectiveness that it improves thermal comfort levels by about 2.5% for an office building and about 10.2% for residential buildings, and that it reduces annual energy consumption by about 17.4% for an office building and about 25.7% for residential buildings. As a consequence, the integrated energy control model has advantages that it noticeably improves thermal comfort and energy efficiency, and that it properly respond to abnormal and abrupt indoor situations derived from human anti-logic or common sense. [ABSTRACT FROM AUTHOR]

The building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linear regression (AMLR) for the control of TABS in a passive seminar building. Detailed comparisons are shown between the standard TABS and AMLR strategies over a period of nine months each. In addition to the reduction of thermal energy use by approx. 26% and a significant reduction of the TABS pump operation time, this paper focuses on investment savings in a passive seminar building through the use of the AMLR strategy. This includes the reduction of peak power of the chilled beams (auxiliary system) as well as a simplification of the TABS hydronic circuit and the saving of an external temperature sensor. The AMLR proves its practicality by learning from the historical building operation, by dealing with forecasting errors and it is easy to integrate into a building automation system. [ABSTRACT FROM AUTHOR]

This paper presents a simulation study of three dynamic electrochromic window glazings, including a novel glazing capable of independently modulating its optical properties in both the visible and near-infrared spectrums. This capability allows this so-called “dual-band” technology to actively manage the solar heat and visible light transmitted into a building’s interior, and creates the potential for heating, cooling, and lighting savings vis-à-vis competing window technologies. In this study EnergyPlus is used to simulate annual energy performance of the dual-band electrochromic (DBEC) glazing in three building types and 16 U.S. climate regions. The savings potential of DBEC windows are presented relative to a conventional electrochromic glazing; a visibly transparent, near-infrared switching electrochromic glazings; and several static alternatives, including ASHRAE 90-2010 standard compliant windows. Results indicate that the DBEC glazings are capable of outperforming alternatives in a diverse set of locations and building types, including both heating and cooling-dominated regions. Relative to code-compliant static windows, the DBEC is capable of achieving annual primary energy savings between 6 and 30 kW h/ft 2 of window area from reduced heating, cooling, and lighting demand. Relative to other advanced glazings, the savings are significantly lower, ranging from 0 to 1.2 kW h/ft 2 . Regional DBEC energy cost savings versus high performance static windows are presented to identify early potential market entries based on energy savings. Finally, the impacts of widespread deployment of high-efficiency LED lighting on DBEC energy savings potentials are also presented. [ABSTRACT FROM AUTHOR]

Belt conveyors can be partially loaded due to the variation of bulk material flow loaded onto the conveyor. Speed control attempts to reduce the belt conveyor energy consumption and to enable the green operations of belt conveyors. Current research of speed control rarely takes the conveyor dynamics into account so that speed control lacks applicability. Based on our previous research, this paper will provide an improved three-step method to determine the minimum speed adjustment time. This method can be summarized as Estimation-Calculation-Optimization and ECO in short. The ECO method takes both the potential risks and the conveyor dynamics into account. It is expected to keep belt conveyors in good dynamic behaviors in transient operations. After discussing the ECO method, this research takes a long inclined belt conveyor of an import dry bulk terminal as case study. Based on the suggested acceleration time, a speed controller is built and computational simulations are carried out to evaluate the energy savings and the conveyor dynamics. Experimental results prove that the application of the ECO method ensures the healthy dynamic performance of belt conveyors under speed control in transient operations. Annually, the average electricity consumption of the single conveyor can be reduced by over 10% with around 90 tons reduction of CO 2 emission. The direct economic benefit can reach up to more than €10,000 in terms of the electricity utilization per year. [ABSTRACT FROM AUTHOR]

To “green” building envelopes is currently one of the most promising ways to provide energy savings in buildings and to contribute to the urban heat island effect mitigation. The shadow effect supplied by plants is the most significant parameter for this purpose. One way to characterize the potential shadow effect of greenery is to calculate the facade foliar density by means of the leaf area index (LAI). As LAI is commonly used in horizontal crops, their use in vertical greenery systems (VGS) has generated dispersion and uncertainty in previous studies both in terms of methodologies and results obtained. In addition, a lack of data relating to the influence of the facade orientation in the final contribution of vertical greenery to the energy savings has been observed in previous studies. This study aims at establishing a common and easy way to measure LAI and to lick it to the energy savings provided by VGS. Moreover, the energy savings achieved as well as the influence of facade orientation on the final thermal behaviour of two different VGS, a double-skin green facade and a green wall, was studied. From the results, it can be stated that the most simple and quick procedure to measure LAI in order to characterize the foliar density of VGS is the indirect method based on the amount of light transmitted through the green screen. From the experimental tests interesting energy savings were obtained (up to 34% for Boston Ivy pant specie with a LAI of 3.5–4, during summer period under Mediterranean continental climate). Moreover, the dependence on facade orientation was confirmed with representative contribution over the whole energy savings from East and West orientation. [ABSTRACT FROM AUTHOR]

Residential energy consumption is one of the main contributors to CO 2 emissions in the UK. One strategy aimed at reducing emissions is to increase retrofitting rates of buildings. In this paper, an alternative approach is discussed and its potential impact on energy use assessed, that of downsizing (moving to smaller homes). Reviews of previous research show that a wide range of what can be termed psychological barriers exist to downsizing, such as the loss of ownership and independence, concern about what to do with possessions, not having enough space for visitors, and attachment to one’s home. Benefits of downsizing from a personal perspective are economic, with lower bills and/or rent, release of capital, lower maintenance costs, and also potential lifestyle improvements including living in easier-to-maintain and more age-appropriate housing. Wider societal benefits include the potential to significantly reduce energy consumption, and mitigating the housing crisis in cities where not enough properties are available. Empirical analysis on a nationally representative sample in England showed that building size alone accounts for 24% of the variability in energy consumption (compared to 11% of household size). If single-person households with more than two bedrooms downsized by one bedroom, energy-savings of 8% could be achieved, and if single-person households occupied only one bedroom, savings of 27%. Data also showed a significant amount of underoccupation, with almost two-thirds of households having more bedrooms than considered necessary compared to the bedroom-standard. However, analysis also revealed a structural barrier to downsizing, namely the lack of available alternative, smaller houses. The evidence would suggest that downsizing could realize significant energy savings, and address a range of other social benefits. However, against this stand significant personal interests, inadequate alternative housing and other infrastructure issues. Promoting downsizing as a means to achieve energy policy goals is therefore a potentially significant but socially challenging policy option. [ABSTRACT FROM AUTHOR]

Due to the strengthening of regulations and codes on building energy performance, as well as with the application of national legislations regarding energy management and efficiency, existing industrial facilities are using thermal refurbishment and renovation as impetus for increasing their overall energy efficiency. This paper analyzes a building envelope refurbishment for a case study of an existing historical industrial facility. Critical parameters affecting energy performance of industrial buildings were identified by reviewing relevant literate. Two retrofit scenarios were developed and dynamic thermal simulation using EnergyPlus was implemented to evaluate the potential for improvement. Thereby the impact of interior loads was considered, determined by measurements conducted on factory machines, occupancy and lighting operation patterns. However, information regarding constructions of the existing facility and installed technical building services is limited. There is also uncertainty in the quantification of natural ventilation air change rate for such buildings. To overcome these limitations a study of various material databases was carried out, in order to assess data for building envelope composition. Input values for missing data were provided based on literature, allowing a fair comparison between refurbishment alternatives. Simulation results showed that the heating demand of the facility could be reduced up to 52%, indicating a significant potential for energy savings. Beyond that, thermal performance against summer overheating also depicted considerable improvements as regards to hours exceeding thermal comfort levels. [ABSTRACT FROM AUTHOR]

In this paper, 2D CFD models have been developed for a prototype refrigerated open type multi-deck display cabinet with and without integrated phase change material (PCM). The models can predict the effect of adding a PCM container on cabinet efficiencies, air temperature distributions, product temperatures and air flow patterns inside the cabinet at a range of operating conditions including space air temperatures and evaporator air velocities. To validate the cabinet models, the prototype cabinet was mounted in an air conditioned chamber and extensive experiments were conducted at constant space air temperature and relative humidity. The cabinet models have therefore been validated through comparison with experiment results for air temperatures at different locations of the airflow path and of food products. Simulation results show that significant energy can be saved through the installation of a PCM container. Further benefits include greater stabilization of product temperatures during defrost periods for the modified display cabinet. Consequently, the validated models can be used to explore and analyse the cabinet performance and control strategies at various operating and design conditions. [ABSTRACT FROM AUTHOR]

It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout programmes. [ABSTRACT FROM AUTHOR]

In Tunisia, the building sector is considered as a major issue of energy consumption. A special attention should be drawn to improve the thermal quality of the building envelope with real consideration of the Tunisian climate specificity. One of the most effective measures is the roof insulation. Therefore, the present study is concerned with the determination of the optimum insulation thickness and the resulting energy savings and payback period for two typical roof structures and two types of insulation materials. An efficient analytical dynamic model based on the Complex Finite Fourier Transform (CFFT) is proposed and validated in order to handle the nonlinear longwave radiation (LWR) exchange with the sky. This model provides a short computational time solution of the transient heat transfer through multilayer roofs, which could be a good alternative to some numerical methods. Both heating and cooling annual loads are rigorously estimated and used as inputs to a life-cycle cost analysis. Among the studied cases, the most economical one is the hollow terracotta-based roof insulated with rock wool, where the optimum insulation thickness is estimated to be 7.9 cm, with a payback period of 6.06 years and energy savings up to 58.06% of the cost of energy consumed without insulation. The impact of the LWR exchange component is quantified and the results show its important effect on the annual transmission loads and, consequently, on optimum insulation thickness. A sensitivity analysis shows the efficiency of cool roofs in the Tunisian climate context, where the cooling energy cost benefits outweigh the wintertime penalty. Comparison of CFFT results with those of sol–air Degree-Hours (DH) shows that optimum insulation thickness and energy savings are overestimated and payback period is underestimated using the latter model. The proposed CFFT model could be an efficient tool for the design and the energy analysis of building envelope components in various climatic locations. [ABSTRACT FROM AUTHOR]

The availability of smart metering and smart appliances enables detecting and characterising appliance use in a household, quantifying energy savings through efficient appliance use and predicting appliance-specific demand from load measurements is possible. With growing electric kettle ownership and usage, lack of any efficiency labelling guidelines for the kettle, slow technological progress in improving kettle efficiency relative to other domestic appliances, and current consumer attitudes, urgent investigation into consumer kettle usage patterns is warranted. From an efficiency point of view, little can be done about the kettle, which is more efficient than other methods of heating water such as the stove top kettle. However, since a majority households use the kettle inefficiently by overfilling, in order to meet energy targets, it is imperative to quantify inefficient usage and predict demand. For the purposes of scalability, we propose tools that depend only on load measurement data for quantifying and visualising kettle usage and energy consumption, assessing energy wastage through overfilling via our proposed electric kettle model, and predicting kettle-specific demand, from which we can estimate potential energy savings in a household and across a housing stock. This is demonstrated using data from a longitudinal study across a sample of 14 UK households for a two-year period. 1 The open-access REFIT Electrical Load Measurements dataset of the 14 UK households used in this study can be accessed via DOI 10.15129/31da3ece-f902-4e95-a093-e0a9536983c4 . 1 [ABSTRACT FROM AUTHOR]

Buildings today represent 40% of world primary energy consumption and 24% of greenhouse gas emissions. In our society there is growing interest in knowing precisely when and how energy consumption occurs. This means that consumption measurement and verification plans are well-advanced. International agencies such as Efficiency Valuation Organization (EVO) and International Performance Measurement and Verification Protocol (IPMVP) have developed methodologies to quantify savings. This paper presents a methodology to accurately perform automated envelope calibration under option D (calibrated simulation) of IPMVP – vol. 1. This is frequently ignored because of its complexity, despite being more flexible and accurate in assessing the energy performance of a building. A detailed baseline energy model is used, and by means of a metaheuristic technique achieves a highly reliable and accurate Building Energy Simulation (BES) model suitable for detailed analysis of saving strategies. In order to find this BES model a Genetic Algorithm (NSGA-II) is used, together with a highly efficient engine to stimulate the objective, thus permitting rapid achievement of the goal. The result is a BES model that broadly captures the heat dynamic behaviour of the building. The model amply fulfils the parameters demanded by ASHRAE and EVO under option D. [ABSTRACT FROM AUTHOR]

Window design is decisive in providing appropriate visual comfort for occupants and sufficient energy savings in electric lighting. In daylighting, visual comfort is dependent on the maximum daylight autonomy. Moreover, energy consumption in electric lighting relies on daylight autonomy. The aim of this research is to quantify these metrics in a residential room for different window models and analyze the results obtained. The surface reflectance and the geometry of the window are variable. DaySim 3.2 lighting program provides the simulations of the room model according to different orientations and weather conditions. Following the trials, it was concluded that daylight autonomy is proportional to the glass surface and reflectance of surfaces at the back of the room, while its influence near the façade is negligible. However, energy consumption does not depend on window shape. It is also concluded that windows located higher up result in higher illuminance at the back of the room than those in centered locations. The conclusions of this research are contrasted with the analysis of daylight metrics for different locations and orientations of the window. [ABSTRACT FROM AUTHOR]

This paper provides a systematic approach for quantifying the influence of building size, construction category, climate, occupancy schedule, setpoint, and deadband on HVAC energy consumption in office buildings. Simulating the DOE reference office buildings of three sizes and three construction categories in all United States climate zones, using the EnergyPlus, we conducted several N-way ANOVA analyses to study the interrelationships between setpoints, deadbands and several building related and environment related factors. In summary, daily optimal deadband selection of 0, 1, 2, 4, 5, and 6 K would result in an average energy savings of −70.0%, −34.9%, −13.7%, 9.6%, 16.4%, and 21.2%, respectively, compared to baseline deadline of 3 K. Selecting the daily optimal setpoint in the range of 22.5 ± 1 °C, 22.5 ± 2 °C, and 22.5 ± 3 °C would result in an average savings of 7.5%, 12.7%, and 16.4%, respectively, compared to the baseline setpoint of 22.5 °C. Additionally, we found that when the outdoor temperature is within −20 to 30 °C, the optimal setpoint depends on the building size. We also observed a range of outdoor temperatures (e.g., 9–14 °C for small buildings and 8–11 °C for medium buildings) where the setpoint selection would only slightly influence the energy consumption. However, the choice of setpoints becomes very influential (up to 30% of energy savings) where the outdoor temperatures are slightly outside the mentioned ranges on either direction. The potential savings from selecting daily optimal setpoints in the range of 22.5 ± 3 °C in different climates and for small, medium and large office buildings, would lead to 10.09–37.03%, 11.43–21.01%, and 6.78–11.34% savings, respectively, depending on the climate. [ABSTRACT FROM AUTHOR]

Reducing the energy consumption of distillation processes can lead to significant cost savings in refineries and the chemical process industry because distillation is a widely used and energy-intensive separation technology. A distillation column can be heat integrated with heat pumps to reduce the energy supplied by the utility, and it can also be integrated into the overall process to save energy for the overall process. However, previous studies have not adequately investigated the synergistic effect of integrating heat pump assisted distillation into overall processes. In this paper, a systematic design methodology is proposed for the simultaneous heat integration of distillation, its background process and heat pump systems. Such a holistic heat integration approach can lead to considerable energy savings for the overall process. The proposed methodology also includes systematic identification for the energy-optimum placement of the heat pump and its matching with process streams. Furthermore, the impacts of distillation process modifications on the holistic heat integration strategy are examined. A case study is presented to illustrate how the proposed design method is applied and to demonstrate its effectiveness in saving energy. For the case study, the hot and cold utilities are reduced by 61.5% and 20.6% compared to energy consumptions for the base case. [ABSTRACT FROM AUTHOR]

The energy and visual performances of the façades are defined by many parameters including façade size, properties of glazings and shadings, and their arrangements as well as control strategies. In this study, a number of combinations of internal woven roller shades and four double glazings have been proposed and assessed in integrated manner in order to improve the energy efficiency and visual comfort in new or existing office buildings. Office rooms facing south, east, north and west have been simulated for cold climate, by varying glazed areas and proposed glazing and shading alternatives. Results have been calculated, compared and analyzed in terms of the energy consumptions, energy saving potentials, daylight autonomy, useful daylight illuminance and discomfort glare free time, for each of the combinations. Simulation results show that the choice of glazing and shading alternatives can have substantial impact on energy and visual performances of the office space. Regardless of façade orientation, the maximum energy saving is achieved for a window-to-wall ratio (WWR) of 30%. Saving potential decreases significantly for larger glazed area and for each façade orientation. For all façade orientations and glazed areas (except for 30% WWR in the north wall), a bare low-e coated double glazing ( U = 1.616 W/m 2 K, SHGC = 0.209, τ v = 0.301) is found to be the most energy efficient choice. For 30% north glazing, the energy efficiency can be maximized with a different bare low-e coated double glazing ( U = 1.628 W/m 2 K, SHGC = 0.370, τ v = 0.581). Moreover, glare affected time, daylight autonomy and useful daylight illuminance in the office spaces with these glazing choices are estimated ⩾50%, between 46% and 99% and in the range of 53–88% respectively. Also, the visual comfort can further be improved just by deploying even a highly transparent fabric (50% transmittance, 20% reflectance, 45% average openness) as an interior roller shade with these glazing choices. [ABSTRACT FROM AUTHOR]

We present a methodology to evaluate the accuracy of baseline energy predictions. To evaluate the predictions from a computer program, the program is provided with electric load data, and additional data such as outdoor air temperature, from a “training period” of at least several months duration, and used to predict the energy use as a function of time during the subsequent “prediction period.” The predicted energy use is compared to the actual energy use, and errors are summarized with several metrics, including bias and mean absolute percent error (MAPE). An important feature of this methodology is that it can be used to assess the predictive accuracy of a model even if the model itself is not provided to the evaluator, so that proprietary tools can be evaluated while protecting the developer’s intellectual property. The methodology was applied to evaluate several standard statistical models using data from four hundred randomly selected commercial buildings in a large utility territory in Northern California; the result is a statistical distribution of errors for each of the models. We also demonstrate how the methodology can be used to assess the uncertainty in baseline energy predictions for a portfolio of buildings, which is an issue that is important for the design of utility programs that incentivize energy savings. The findings of this work can be used to (1) inform technology assessments for technologies that deliver operational and/or behavioral savings; and (2) determine the expected accuracy of statistical models used for automated measurement and verification (M&V) of energy savings. [ABSTRACT FROM AUTHOR]

A kind of heat conduction-enhanced shape-stabilized PCM (HCE-SSPCM) was utilized in the under-floor heating system for house heating in winter. This system charges heat by using cheap nighttime electricity and provides heating needs throughout all day. The effect of thermal conductivity of the PCM on energy savings and economic benefits of the system were theoretically and experimentally studied. HCE-SSPCM plates, made of (solid paraffin + liquid paraffin)/high density polyethylene/expanded graphite, were introduced to a test room with under-floor heating system. And the operating characteristics of the system were compared with that of the non-phase change energy storage system and the conventional air conditioning system. The results showed that enhancing the thermal conductivity of PCM in a certain range could significantly improve the energy efficiency of the heating system and reduce the thickness of thermal insulating materials. But the improving effect was not obvious when the thermal conductivity was beyond 1.0 W/m K. The phase change energy storage system had a comfortable temperature environment and the best economic benefits among the three different heating types especially when the ratio of peak-valley electric price was high. Therefore, increasing the thermal conductivity of SSPCM will be of great significance for house heating. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a methodology for optimizing the operation of compressors in parallel in process industries. Compressors in parallel can be found in many applications for example in compressor stations conveying gas through long pipelines and in chemical plants in which compressors supply raw or processed materials to downstream processes. The current work presents an optimization framework for compressor stations which describe integration of a short term and a long term optimization approach. The short-term part of the framework suggests the best distribution of the load of the compressors (where the time scale is minutes) and the long-term optimization provides the scheduling of the compressors for large time periods (where the time scale is days). The paper focuses on the short-term optimization and presents a Real Time Optimization (RTO) framework which exploits process data in steady-state operation to develop regression models of compressors. An optimization model employs the updated steady-state models to estimate the best distribution of the load of the compressors to reduce power consumption and therefore operational costs. The paper demonstrates the application of the RTO to a network of parallel industrial multi-stage centrifugal compressors, part of a chemical process in BASF SE, Germany. The results from the RTO application showed a reduction in power consumption compared to operation with equal load split strategy. [ABSTRACT FROM AUTHOR]

With the recent development of the IT technology, the demand for data centers has significantly increased, and modular data centers have attracted considerable attention because of their excellent stability, scalability, and economic feasibility. This research quantitatively analyzed the applicability of various air-side economizers and their energy-saving potential in modular data centers. A detailed cooling load estimation process was established for modular data centers, and annual cooling energy simulations were carried out using various air-side economizers. The various air-side economizers yielded cooling coil load savings of 76–99% in comparison to conventional cooling systems in data centers, and the total cooling energy savings of the economizers ranged from 47.5% to 67.2%. Indirect air-side economizers with high-effectiveness heat exchangers were found to yield significant energy saving (63.6%) and have simple system configurations. [ABSTRACT FROM AUTHOR]

Energy flow diagrams in the form of Sankey diagrams have been identified as a useful tool in energy management and performance improvement. However there is a lack of understanding on how such diagrams should be designed and developed for different applications and objectives. At the national level, a framework matching features of Sankey diagrams with various objectives of energy performance management provides better understanding how Sankey diagrams can be designed. As part of the framework, boundaries outlined around a group of facilities provide a refined representation of sub-systems that trace energy use in various conversion devices, products and services, which identifies potential areas for energy savings. There are some differences between energy flows and exergy flows represented in Sankey diagrams. Furthermore, exergy flow Sankey diagrams offer advantages in identifying potential areas for energy savings. This is illustrated at a national level, using UK’s industrial heating processes that overlays both energy and exergy flow diagrams. [ABSTRACT FROM AUTHOR]

Highlights: [•] LAMEEs can be used for air dehumidification and energy recovery in HVAC systems. [•] The economic benefits and environmental impacts of LAMEEs are reviewed. [•] LAMEEs can effectively improve indoor air quality. [•] Several topics are suggested for future research. [ABSTRACT FROM AUTHOR]

Highlights: [•] Effects of weather forecast uncertainty on a predictive control concept is investigated. [•] Two different years in a temperate climate are simulated for 24 building scenarios. [•] Energy savings demonstrated despite of weather forecast uncertainties. [•] Thermal indoor environment improved despite of weather forecast uncertainties. [ABSTRACT FROM AUTHOR]

Highlights: [•] Energy saving potential in historic wooden apartment buildings is up to 63%. [•] In historic wooden apartment buildings an economically viable energy saving level is 50%. [•] The largest energy saving potential lies in heat source and building service systems. [•] Of the building structures, insulation of the external wall has the highest potential. [•] New heating and ventilation systems must be installed to fulfill regulations limits. [Copyright &y& Elsevier]

Highlights: [•] We developed various models for the enhancement of vapor recompression heat pump. [•] Utilization of hot process or utility streams was considered in the models. [•] Efforts were made to minimize heat losses and heat pump size. [•] The thermoeconomic and environmental performances of the models were investigated. [•] The applications of the models will reduce total annual cost and emission rate. [Copyright &y& Elsevier]

Abstract: In subtropical Hong Kong, a certain amount of electricity is used to create visually comfortable interior spaces through electric lighting, which is the second major electricity-consuming item in commercial buildings, accounting for 20–30% of total electricity use. The burning of fossil fuels for electricity generation has many adverse effects on the environment. Daylighting is an important and useful strategy for enhancing visual comfort and reducing the need for the electricity consumed by light fittings. The rational use of daylight through tools such as photoelectric lighting controls can effectively reduce buildings’ electricity consumption and the related pollutants and greenhouse gas emissions. Daylighting design techniques are often best demonstrated via field measurements that provide reliable operational and energy performance data for establishing design guidelines. An atrium provides an environmentally controlled indoor public space that introduces daylight into the hearts of large buildings. In circulation areas such as corridors, people expect the way ahead to be sufficiently lit and daylight-linked lighting controls can deliver excellent energy savings. This paper presents the daylighting and energy performance of an atrium space using daylight-linked lighting controls. The cost, energy and environmental issues related to various daylight illuminances are estimated and design implications are discussed. [Copyright &y& Elsevier]

Abstract: An innovative idea on extracting clean energy from man-made wind resources with micro wind turbine system for power generation is introduced in this paper. This system generates on-site clean energy using a micro wind generation system. A vertical axis wind turbine (VAWT) with an enclosure is mounted above a cooling tower’s exhaust fan to harness the wind energy for producing electricity. The VAWT is positioned at a specific position at the cooling tower outlet to avoid a negative impact on the performance of the cooling tower. The enclosure can act as a safety cover and also enhance the performance of the VAWT. It is designed with several guide-vanes positioned at the up-stream side of the wind turbine to create a venturi effect and guide the wind before it interacts with the turbine blades. Moreover, the enclosure design is comprised of diffuser-plates that can draw more wind and accelerate the flow. Laboratory test conducted on a scaled model shows no measurable difference in the air intake speed and current consumption of the power-driven fan when the turbine was spinning above the cooling tower. Field test on an actual induced-draft cooling tower shows no significant difference on the outlet air speed of the cooling tower. A small difference was observed on the power consumption by the fan motor which is 0.39% higher with the presence of the VAWT. This system is retrofit-able to existing cooling towers and has very high market potential due to abundant cooling towers and other unnatural exhaust air resources globally. [Copyright &y& Elsevier]

Highlights: [•] Position and distribution of materials are analyzed for insulating performance. [•] Insulation for first and last layers improves insulating performance. [•] Equal distribution of insulation and thermal mass improves insulating performance. [•] Optimum configuration exists for wall with fixed resistance and capacitance. [ABSTRACT FROM AUTHOR]

• Data-driven dynamic harmonic coupled admittance matrix model is proposed for modern home appliances. • Recursive partial least squares method and the model adaptive update strategy are used for Characterizing the dynamic harmonics. • Harmonic voltage evaluation, line power loss calculation including harmonics and energy savings are realized by using the dynamic model. With the rapid development of power electronics technology and the enhancement of users' energy conservation awareness, the proportion of modern household appliances with power electronic devices is increasing year by year, which has become an important harmonic source. Together with the massive access of home photovoltaic and electric vehicles, the harmonics of the existing residential low-voltage distribution system (RLVDS) show higher distortions and stronger dynamics than ever before. Therefore, an accurate harmonic model of the modern household appliance is necessary for power quality analysis and improvement. This paper proposes a data-driven dynamic harmonic coupled admittance matrix model (HCAMM) based on measured voltage and current data. First, the parameters of the HCAMM are solved by the partial least squares method (PLSM), which can effectively overcome the matrix pathology problem in the solution process, and the HCAMM can reflect the coupling effect between each harmonic. Second, to address the voltage dynamics, the dynamic HCAMM is established by combining the recursive PLSM and the adaptive update strategy, which can accurately characterize the harmonics under different supply voltages. Finally, the accuracy, dynamics, and generality of the proposed harmonic model are verified by simulations and experiments, and the harmonic model is applied to the power quality harmonic evaluation, line power loss calculation with harmonics, and energy saving by reducing the harmonics. [ABSTRACT FROM AUTHOR]

[Display omitted] • Assessment of energy efficiency using stochastic non-parametric envelopment of data. • Average energy efficiency of Chilean wastewater treatment plants was 0.433. • Age and secondary treatment technology influence on the energy efficiency. Wastewater treatment is an energy-intensive process and therefore, improving the energy efficiency of wastewater treatment plants (WWTPs) is relevant from an economic and environmental perspective. Water companies managing WWTPs operate under monopolistic conditions and thus, benchmarking their performance using robust methods is fundamental for regulation. This study evaluates the energy efficiency of a sample of Chilean WWTPs using a newly developed technique, called stochastic non-parametric envelopment of data (StoNED). This technique integrates non-parametric (non-linear programming) methods with stochastic noise (parametric techniques) and therefore, it overcomes the limitations of both methodological approaches. Moreover, it allows exploring the influence of operating environment on the energy performance of WWTPs. Results evidenced that the Chilean WWTPs were considerably inefficient (average score was 0.433) presenting therefore significant opportunities to save energy (average savings were 203,413 MWh/year). Only 8 out of 203 facilities reported an average energy efficiency score which was greater than 0.81. It was also found that the age of the facilities negatively affected energy efficiency. Recently built WWTPs showed an average energy efficiency score of 0.489, whereas older facilities were found to be considerably inefficient, 0.340 on average. WWTPs using suspended-growth processes, i.e., conventional activated sludge and extended aeration, as secondary treatment were those with the lowest levels of energy efficiency on average. The results and conclusions of this study are useful for policy makers and WWTP operators who want to reduce energy consumption of WWTPs and therefore, their operational costs and environmental impacts. [ABSTRACT FROM AUTHOR]

• A novel valuation approach based on cost-benefit trade-offs is proposed. • We identify cost-effective and cost-optimal strategies of intervention. • We implement a two-criteria, additive-value decision model. • A graphical approach is proposed for the identification of the best retrofit solution. Directive 2018/844/EU promotes long-term renovation strategies to achieve the 2050 EU-wide energy and climate targets. As the building sector accounts for 40% of final energy consumption and 36% of CO 2 , buildings energy retrofitting and the valuation of related investments play a fundamental role in the successful implementation of the energy transition. The economic evaluation of buildings' energy retrofit projects is usually performed by implementing the Life Cycle Cost approach. Nonetheless, due to increased social awareness and environmental concerns, homeowners may be willing to invest in more energy-efficient solutions, rather than in the least-cost solution. This paper aims to provide a valuation framework to identify cost-effective and cost-optimal strategies of intervention, which match technological innovation in buildings energy renovations with environmental concerns and social awareness. In detail, we complement the Life Cycle Cost method with the Net Present Value rule and determine the best retrofit project by implementing a two-criteria (i.e., reduction in primary energy consumption and increase in the present value of net benefits compared to the status quo), additive-value decision model. We also propose a graphical approach, which provides a straightforward identification of the best compromise solution between Net-Present-Value maximizing and energy-saving maximizing buildings' energy retrofit projects. We tested the proposed approach on a real-world case study and found that it is less sensitive than other methodologies to uncertainty over discount rates and future energy prices. [ABSTRACT FROM AUTHOR]

Highlights: [•] First bottom-up energy model for NEI at 4-digit level of NACE for energy analysis. [•] Energy end-use modelling due to the unsuitability of end-product/process approach. [•] Analysis of heat recovery with HP on industrial processes up to 2020 in French F&D. [•] Energy consumption and emissions drop respectively by 10% compared to 2001 and 9% to 1990. [•] Results only achieved at heat temperature below 100°C, concentrated in 1/3 of F&D sectors. [Copyright &y& Elsevier]

Highlights: [•] Energy analysis of 20 South African mine cooling systems. [•] Energy savings and feasibility calculated for large-scale variable speed drive implementation. [•] An annual electricity saving of 144,721 MWh (32.2%) and CO2 emission reduction of 132 Mton can be realised. [•] Pump and fan application found more viable than chiller application. [•] Pilot implementation study shows pump electricity savings of 29.9%. [Copyright &y& Elsevier]

Abstract: Aquaculture has become an important sector of animal food production thanks to a fast and continuous growth over the last few decades. Both marine and fresh water fish can be reared in fish farms, and there are species that are mainly produced by aquaculture rather than capture. As most of the reared fish species are sensible to water temperature and its fluctuations, having the control of this parameter in fish farms becomes an important issue that has to be taken into account. In this paper, three different fish farms are studied by simulating the water temperature when a thermal energy storage (TES) system using phase change materials (PCMs) is implemented. The effect and the estimated amounts of PCM required in each particular case are also analyzed. The results show that appreciable effects can be obtained, especially when the TES unit is used in combination with auxiliary sources of energy, such as solar collectors. [Copyright &y& Elsevier]

Abstract: Published work on the heat integration of batch distillation is scare and mainly focuses on the continuous flow columns. This paper introduces a novel thermally integrated batch reactive distillation, in which, the rectification tower runs as usual at atmospheric pressure and the concentric reboiler operates under vacuum. It is inspected that the proposed thermally integrated batch reactive distillation with a concentric vacuum reboiler secures positive savings of energy and better economic figures than the conventional batch reactive distillation. Importantly, this scheme has the potential to enhance the product purity at steady state by the improvement of reaction conversion. For boosting both the energetic and economic performance of the proposed thermally integrated batch distillation scheme, in this contribution, we introduce further intensification by coupling the overhead vapor and the reboiler liquid. [Copyright &y& Elsevier]

Abstract: This paper describes the results from a performance comparison of different types of HVAC systems in a low energy residential building. There were five different HVAC systems which were investigated and evaluated: Ground Couple Heat Pump (GCHP); Ground Water Heat Pump (GWHP); Air-to-Water Heat Pump (AWHP); Air-to-Air Heat Pump (AAHP); and Boiler & Split (B&S) systems applied respectively for heating and cooling seasons. These HVAC systems were implemented in one residential-complex which consisted of a three-story block subdivided into 15 apartments with total floor area of 1050m2. Year-round dynamic simulations were carried out using Energy Plus based on three different climatic conditions from northern, central and southern Italy. The climates of cities Milan, Rome and Palermo were used respectively in order to estimate potential energy savings among HVAC systems for each site location. It was found that in Milan, AAHP & AWHP heat pump systems save 14.8% and 23.3% primary energy respectively compared to the B&S system, while GCHP and GWHP systems save 59.6% and 62.6% respectively. A techno-economic analysis for a twenty year period was also carried out for each specific case. It was observed that the GWHP case becomes economically feasible after 9 years with respect to other cases for the Milan case study. [Copyright &y& Elsevier]

Abstract: In this work, we have developed a direct one-step process design on an oxygenate production, namely, dimethyl ether (DME). DME can be used as a cetane-number booster for diesel, in addition to being capable of a substitute for liquefied petroleum gas (LPG). In order to analyze the independent chemical reactions involved in the reactor, it is necessary to carry out a study of the chemical reaction stoichiometry. And with a specific syngas feed, the following reactions are found: (1) CO2 +H2 =H2O+CO, (2) CO+2H2 =CH3OH, and (3) 3CO+3H2 =(CH3)2O+CO2. To gain an insight into the reactor design, we have also utilized the concept of thermodynamics, including equilibrium-constant method and the minimization of Gibbs free energy. Additionally, we have also united the pinch technology with the base-case design for heat exchanger network synthesis in order to compare the energy consumption and capital costs of the process with/without heat integration. Two kinds of software were used in the research–Aspen Plus and SuperTarget. The former was used for the process synthesis, design, and simulation; the latter was used to carry out the pinch analysis and the synthesis of heat exchanger network. [Copyright &y& Elsevier]

Abstract: The paper analyzes refrigeration/HVAC system energy consumption in a typical food retail store to study the effects of indoor space conditions. Refrigerated display cases are normally rated at a store environment of 24°C (75°F) and a relative humidity of 55%. If the store can be maintained at lower relative humidity, significant quantities of refrigeration energy, defrost energy, and anti-sweat heater energy can be saved. Calculations were done for a typical day in a standard store for each month of the year using the climate data for Tampa, Florida. This results in a 24h variation in the store relative humidity. Using these hourly values of relative humidity for a typical 24hday, the store relative humidity distribution was calculated for a full year. The annual average supermarket relative humidity was found to be 51.1%. It is shown that for a 5% reduction in store relative humidity, the display case refrigeration load is reduced by 9.25%, and that results in total store energy load reduction of 4.84%. The results were compared to available experimental data and found to have a good agreement. [Copyright &y& Elsevier]

Abstract: In 2007 the Class 1 project commenced. Originally, 442 dwellings were to be designed and constructed as “low-energy class 1” houses according to requirements set by the Municipality of Egedal/Denmark. This means that the energy consumption is 50% below the existing energy regulations. Sixty five dwellings and about 30 single family houses have been constructed. The Concerto community also includes a kindergarten (completed) and an elderly centre. Currently, because of the financial crisis, only about 200 new dwellings will be constructed. Therefore, a contingency plan (plan B) has been developed replacing some of the new dwellings with renovation projects for public buildings. Simultaneously the originally planned district heating network supplied from a relatively small bio-gasification plant has been substantially enlarged to cover a large part of the existing Stenloese town as well and a large wood-chip heating plant has been added. The project demonstrates the benefits of ultra-low-energy buildings integrated with biomass- and solar heating energy supply. The Class 1 project involves four other countries: Estonia, France, Italy and Romania. These countries develop training activities based on the results and experiences gained from the Danish housing projects. This paper describes the comparisons between measured and calculated energy consumption in a social housing settlement and in a detached single-family house. Results show relatively large discrepancies between measured and calculated results, and discussions on possible explanations are given. [Copyright &y& Elsevier]

Abstract: The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities’ electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model. [Copyright &y& Elsevier]