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Buildings account for over one-third of global emissions and energy use. Meeting climate pledges will require achieving high operational energy efficiency with low embodied impacts in new construction. Yet, a systematic identification of the relative influence of building design parameters on both operational and embodied efficiencies has rarely been attempted. In this paper we explore for the first time the sensitivity of a wide range of design and operation parameters in terms of embodied carbon, construction cost, as well as heating and cooling loads for multi-storey buildings. We devised a model to estimate the relative importance of a large set of input variables, describing a building’s shape, size, layout, structure, ventilation, windows, insulation, air, and use for residential and office multi-storey buildings, across different climates. We found that increasing building compactness, using steel or timber instead of concrete frames, lowering window-to-wall ratio, choosing the most suitable glazing, and employing mechanical ventilation with heat recovery are the most important measures to decrease embodied emissions and operational energy. The most significant trade-offs with construction cost were found for the choice of frame material and in the decision whether to install mechanical ventilation. We estimate that 28–44% of yearly heating and cooling energy and 6 Gt cumulative embodied CO2e until 2050 could be saved in multi-storey buildings, without employing new technologies.

Abstract The goal for performing heat exchanger network (HEN) retrofit is not only to reduce utility consumption but to ensure that the retrofit is economically viable. The problem of using heat transfer enhancement for retrofit lies with the uncertainty of the best location in which to apply enhancement, the augmentation level and dealing with downstream effects after enhancement is conducted. To solve these problems, a systematic methodology is proposed. The first step in this methodology is the identification of candidate heat exchangers. In the second step, two methods, sensitivity analysis and an area ratio approach are compared for the identification of the best candidate heat exchangers to enhance. Heat transfer enhancement is then performed on the best candidate heat exchanger and, a non-linear optimisation based model is used to deal with the downstream effects after enhancement, subject to meeting set constraints on the HEN, such as the stream target temperatures and heat transfer area. Following this approach, the problems posed by the use of enhancement for retrofit can be addressed in a simple and computationally inexpensive manner. Heat transfer enhancement is an attractive option for HEN retrofit as it can provide energy saving without the need for topology modifications and additional heat transfer area with an added benefit of reduced implementation time, as modifications can be carried out during normal shutdown periods.

Abstract Coal remains an important energy source. Nonetheless, pollutant emissions – in particular Oxides of Nitrogen (NOx) – as a result of the combustion process in a boiler, are subject to strict legislation due to their damaging effects on the environment. Optimising combustion parameters to achieve a lower NOx emission often results in combustion inefficiency measured with the proportion of unburned coal content (UBC). Consequently there is a range of solutions that trade-off efficiency for emissions. Generally, an analytical model for NOx emission or UBC is unavailable, and therefore data-driven models are used to optimise this multi-objective problem. We introduce the use of Gaussian process models to capture the uncertainties in NOx and UBC predictions arising from measurement error and data scarcity. A novel evolutionary multi-objective search algorithm is used to discover the probabilistic trade-off front between NOx and UBC, and we describe a new procedure for selecting parameters yielding the desired performance. We discuss the variation of operating parameters along the trade-off front. We give a novel algorithm for discovering the optimal trade-off for all load demands simultaneously. The methods are demonstrated on data collected from a boiler in Jianbi power plant, China, and we show that a wide range of solutions trading-off NOx and efficiency may be efficiently located.

Abstract This paper has arisen from a project which aims at developing a microcomputer-based fault-diagnostic instrument, for use with respect to the behaviours of most forms of refrigeration plant. The initial stage in the development of such an instrument is to compile a suitable software package, capable of calculating certain refrigerant and cycle properties from simple pressure and temperature inputs, at the four state-points of the cycle. This has been achieved using a BASIC program which can determine the following: • • the thermodynamic properties at the cycle state-points; • • component energy balances; • • isentropic efficiency of compression; and • • coefficient of performance. By evaluating the various arbitrary constants required in the equations used within the program, it is possible to estimate the properties of refrigerants R11, R12, R13, R14, R22, R113, R114, R500 and R502 as functiions of their characteristic parameters at any state-point. All the derived equations and characteristic constants are collated and presented in this paper. The computed properties of the refrigerants have been compared with pertinent published data, and the presented correlations provide good degrees of agreement between the calculated values and published data.

Abstract The weather is one of the main factors to consider when designing a building because it represents the most important boundary condition to affect the dynamic behaviour of the building. In the literature, many studies use the degree day to predict building energy demand. However, linking the results obtained from a generic building simulation tool with defined degree days, will not give reliable energy evaluation. The goal of this study is to demonstrate that the assessment of building energy demand through the use of the degree day is correct only if the determination of the climate index is a function of the same weather data. The relationship between Heating Degree-Day and heating energy performance was identified by determining some simple correlations, in order to obtain a preliminary evaluation of energy demands. The authors used Heating Degree Days based on three climate data-sets, developing different relationships and feedback. For the extraction of these correlations, numerous dynamic simulations on non-residential buildings characterized by high-energy performance were carried out. From the analysis of the results, it is clear that the relationships with higher correlation coefficients (higher than 0.9) are those that are a function of the degree calculated from the same climatic file used during the simulations. The proposed methodology, validated in this work for an Italian case study can be extended to any country and can be used to improve the reliability of any decision support tool based on climatic indexes.

Electricity cost has become a critical concern of data center operations with the rapid increasing of information processing demand. Data center microgrid (DCMG) is a promising way to reduce electric energy consumption from traditional fossil fuel generators and the billing cost, by effectively utilizing local renewable energy, e.g., wind power. However, uncertainties of wind power generation and real-time workload of data center would have significant impacts on the operational efficiency of DCMG, especially when it is in the island mode. For this reason, a novel affinely adjustable policy based robust multi-objective optimization model under flexible uncertainty set is proposed in this paper, which simultaneously optimizes wind power curtailment, the operation cost, and the over-plus level of computation resource, while considering uncertainties of both the wind power and real-time workload. Through numerical simulation studies, the validity of robust multi-objective optimization model for the island operation of DCMG is verified. Besides, the effectiveness of the proposed methods, i.e., the novel affinely adjustable policy and the flexible uncertainty set, in handling uncertainties are evaluated. Compared to the conventional robust multi-objective optimization model, the proposed approach reduces the operating costs of about 10% in average while maintaining similar reliability in numerical simulations. Moreover, the complex quantitative relationship among these multiple objectives is further investigated. Simulation results indicate the minimization of wind power curtailment and over-plus level of computation resource increases about 25% of the operation cost. These quantitative relationships can well support the decision making of DCMG operation management.

Abstract According to IEA projections, the penetration of electric vehicles in the world transportation sector is expected to increase in the next decades to comply with the future GHG emissions policy targets. The change in transport technology mix will cause a change the environmental and economic impacts of the transportation sector, switching it from flows to funds, that is, from the production and use of the fuel to the production of the fuel pathway and powertrain infrastructures. Therefore, due to their comprehensiveness, the use of Life Cycle Assessment models will be increasingly important with respect to Well-to-Wheels ones in assessing the impact of future transport technologies. In this paper, the Hybrid Input-Output analysis is proposed as the appropriate framework to assess the impact due to a change in transport technology mix from a LCA perspective. First, LCA and WTW approaches are theoretically compared. Secondly, the LCA model is applied for the analysis of the economic and environmental impact caused by the prospected penetration of Fuel Cell Electric Vehicles (FCEV) based on Proton Exchange Membrane Fuel Cell (PEMFC) for Germany in 2050. In addition to the production of the vehicles, the LCA model includes the infrastructures for hydrogen production and distribution and the prospected change in the national electricity production mix. Significant discrepancies have been found by comparing results of LCA with the ones obtained by well-established WTW models already available in the literature. It is found that the impact caused by infrastructures and production of vehicles could significantly offset the expected reduction in CO2 emissions and primary non-renewable energy consumptions.

The recent advances in miniaturized mechanical devices open exciting new opportunities for combustion, especially in the field of micro power generation, allowing the development of power-supply devices with high specific energy. The development of a device based on a catalytic combustor coupled with thermoelectric modules is particularly attracting for combustion stability and safety. Furthermore, when implemented in micro-meso scale devices, catalytic combustion allows fully utilization of the high energy densities of hydrocarbon fuels, but at notably lower operating temperatures than those typical of traditional combustion. These conditions are more suitable for coupling with conventional thermoelectric modules, preventing their degradation. In this work a novel catalytic meso-scale combustor fuelled with propane/air mixture has been coupled with two conventional thermoelectric modules. The wafer-like combustor is filled up with commercially available catalytic pellets of alumina with Platinum (1% weight). In order to calibrate the operating conditions, the analysis of the temperature values and distribution across the combustor surfaces have been carried out. Characterization of exhaust gases concentration and of pellet aging were performed in order to investigate combustor properties. The results of the combustor behavior characterization guided the coupling of the combustor with commercially available thermoelectric modules using at the cold side a water cooled heat exchanger. The system obtained has been characterized in different operating conditions measuring the delivered electric power in different operating conditions. Efficiency estimation proves that the system is suitable for small portable power generation.