Large Savings Research Articles

Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data

Heat pumps play an important role in the energy transition. They can extract renewable energy from the air or ground and increasingly replace fossil heating systems in buildings. In operation, however, heat pumps often consume more electricity than necessary due to incorrect settings and installation deficiencies. Although many setting and installation issues are easy to fix, problems often go unnoticed, and the saving potential from quick fixes remains unclear. In a study with 297 Swiss households (41 treatment, 256 control) running for four years, we investigated an energy efficiency campaign in which the treatment group received a professional heat pump inspection and user training. We found considerable heterogeneity with respect to the savings achieved. We derived two criteria based on smart meter data that enable utilities to identify relevant households and thus boost the impact of such efficiency campaigns: For example, pre-selecting half of the households based on available information results in average savings of 1,805 kWh (15.2%) per year and household in the high-potential group compared to no savings in the low-potential group. Thus, heat pump inspections among pre-selected households can lead to large, cost-effective electricity savings, and we show that common smart meter data makes such pre-selection feasible.

Optimization of service frequency and vehicle size for automated bus systems with crowding externalities and travel time stochasticity

Public transport is considered as one of the most suitable candidates to benefit from autonomous driving technologies. In this research, we develop a mathematical modeling framework to optimize service frequency and vehicle size for automated bus systems, while accounting for both user and operator costs. We explicitly consider travel time stochasticity, time-dependent passenger flows, vehicle capacity limitations (extra waiting time due to denied boarding), and in-vehicle discomfort externalities for both sitting and standing passengers at a microscopic level. We attempt to provide a thorough assessment of the service and cost implications of the deployment of automated buses. Hence, a broad range of experiments are simulated by combining different deployment cases: (i) vehicle technology (human-driven or automated vehicles), (ii) travel time assumptions (deterministic or stochastic travel times), and (iii) crowding externalities (considering or ignoring in-vehicle crowding costs). The model applicability is assessed on two real-world bus corridors in Regensburg (Germany) and Santiago (Chile). Results show that, with crowding externalities, optimal vehicle size is increased at a similar rate for both human-driven and automated bus services, whereas optimal service frequency is increased at a higher rate for automated buses. Thus, under optimal levels of supply, automated vehicles are operated with lower occupancy levels than human-driven vehicles, increasing the quality of service. Besides, the deployment of automated bus systems can significantly alleviate or eliminate denied boardings. The effects of automation on travel time volatility and dwell time regularity are studied. The consideration of stochastic travel times increases optimal frequencies at a higher rate for automated services relative to human-driven vehicles. Interestingly, we find that even though the operator benefits from automation are more pronounced in high-income countries (due to a greater potential for human driving cost savings), the final outcome is counterbalanced by the actual public transport demand level, because large user cost savings from automation are reachable in crowded routes even in situations in which labor costs are lower (as in developing countries).

Ngaaminya (find, be able to see): summary of key findings from the Which Way? project.

Ngaaminya (find, be able to see): summary of key findings from the Which Way? project.

Performance investigation of a vertically configured LHTES via the combination of nano-enhanced PCM and fins: experimental and numerical approaches

Thermal energy storage using Phase Change Materials (PCM) with low thermal conductivity presents one of the barriers to ensuring the storage and release of large heat quantities in a short time suitable for solar applications. One of the best techniques to overcome this obstacle is the inclusion of nanoparticles into the PCMs. Furthermore, the use of finned storage units can significantly boost thermal performance. In this paper, A comprehensive 3D numerical study is presented to investigate the performance of a vertically-configured-cylindrical copper LHTES using Nano-Enhanced PCM (NEPCM) with both outer and inner longitudinal fins. Based on the enthalpy-porosity technique, the numerical model is established taking into account the natural convection effect and transient variations in the thermo-physical properties of NEPCM. An experimental setup is built to analyze the thermal behavior of LHTES with CuO and Al2O3 based NEPCM, and to validate the numerical model. Once validated, the numerical model is employed to investigate the combining effect of using fins and NEPCM based on CNT 1% and Al2O3 2% nanoparticles. Transient numerical simulations are conducted for both charging and discharging cycles for six scenarios corresponding to several NEPCM and configurations (with and without longitudinal fins). Both experimental and numerical investigation show that the NEPCM ensures a great improvement, resulting in large time savings during both charging and discharging phases compared to pure PCM. Moreover, the results show that placing six outer and inner longitudinal fins in the wall of LHTES shortens discharge and charging times by 71% and 62%, respectively, as compared to the reference case (pure PCM without fins). Furthermore, using NEPCM with 1% CNT nanoparticles by weight dispersed in PCM combined with six outer and inner longitudinal fins reduces discharge and charging times by 89% and 84%, respectively. Although CNT is very effective by highly enhancing the PCM thermal characteristics, it is very expensive compared to metal oxide nanoparticles. However, it was discovered that using 2% Al2O3 for finned LHTES can achieve nearly the same results as using 1% CNT.

NOMA-Enabled Computation and Communication Resource Trading for a Multi-User MEC System

In this article, we establish a novel framework for a multi-user mobile edge computing (MEC) network in which a set of users with high downlink rate demands and a set of users with intensive computation tasks can collaborate to achieve a mutually-beneficial scenario such that completion time of the tasks is reduced and the base station (BS) can send more information at a higher rate to the downlink users. Specifically, by leveraging non-orthogonal multiple access (NOMA) for uplink and downlink traffic, the user with the computation task can offload shares of the computation task to the edge cloud and the downlink user. At the same time, this user forwards the information it receives from the BS to the downlink user. In this set up, we jointly optimize the communication resources, computational resources at the edge cloud and user devices, pairings among the two sets of users, the shares of computation tasks, and relay bits to minimize the total task completion time while satisfying downlink users’ incentive requirements. For a network with a single computation demanding user and a single downlink user, the optimal solution to the problem is provided. For a network with multiple users, the problem is non-convex and computationally challenging. Hence, we propose an efficient, low complexity algorithm that utilizes the bottleneck matching algorithm, convex optimization, and the block coordinate descent scheme to obtain a locally-optimal solution. Simulation results demonstrate that, as compared with the state-of-the-art, the total task completion time is greatly reduced (32%–51%), and a large computational energy savings at the edge cloud (38%–55%) is achieved. Simultaneously, the downlink users’ rates improve compared to the orthogonal transmission.

Corporate Ownership Structure and Cash Holdings in the Vietnamese Market

This study examines the relationship between corporate ownership structures and cash holdings in Vietnam using panel regression. We use a sample of 646 non-financial firms listed on the Ho Chi Minh City Stock Exchange from 2010 to 2018. Our main analysis employs firms’ state and foreign ownership status as the explanatory variables and firms’ cash holdings as the response variable. Both state ownership and foreign ownership exert a statistically significant positive influence on the investee firms’ internal cash reserves. Our baseline result implies that both state and foreign investors are likely to demand high cash ratio based on precautionary motives. To address endogeneity issues, we also include a firm’s cash policy in the past three years in the analysis. Both types of ownership and cash holdings are significantly positively related, hinting that our results are robust to autocorrelation. This positive link reveals that firms are likely to accumulate large cash savings in a weak business environment characterized by poor investor protection and high levels of political uncertainty and information asymmetry. These results indicate a possibility that different management preferences of domestic and foreign shareholders may be overridden by an adverse business environment. One important policy implication is that regulatory agencies should adopt a uniform accounting standard for financial reports, preferably under the international financial reporting standards (IFRS), to improve the information transfer between outside investors and shareholders. This will enhance minor shareholders’ rights and values and induce more effective monitoring mechanisms to enter the market, thereby creating a healthier business environment.

Ureteroscopy with thulium fiber laser lithotripsy results in shorter operating times and large cost savings.

PurposeProlonged ureteroscopy (URS) is associated with complications including ureteral perforation, stricture, and urosepsis. As laser lithotripsy is one of the most common urologic procedures, small cost savings per case can have a large financial impact. This retrospective study was designed to determine if Thulium fiber laser (TFL) lithotripsy decreases operative time and costs compared to standard Holmium:YAG (Ho:YAG) lithotripsy without pulse modulation.MethodsA retrospective review of URS with laser lithotripsy was conducted for 152 cases performed from August 2020 to January 2021. Variables including cumulative stone size, location, chemical composition, prior ureteral stenting, and ureteral access sheath use were recorded for each case. A cost benefit analysis was performed to show projected cost savings due to potentially decreased operative times.ResultsCompared to Ho:YAG, use of TFL resulted in an average decrease of 12.9 min per case (p = .021, 95% CI [2.03–23.85]). In subgroup analysis of cases with cumulative stone diameter less than 15 mm, the difference was 14.0 min (p = .007, CI [3.95–23.95]). For cases less than 10 mm, the mean difference was 17.3 min in favor of TFL (p = .002, 95% CI [6.89–27.62]). This ~ 13 min reduction in operative time resulted in saving $440/case in direct operating room costs giving our institution a range of $294,000 to $381,900 savings per year.ConclusionsTFL has a significantly shorter operative time and decreased cost when compared to the standard Ho:YAG for equivalent kidney stone and patient characteristics. Longer term follow up is needed to see if recurrence rates are affected.

Climate and the productive structure of the urban water industry

ABSTRACT Climate is likely to affect the productive structure of urban water supply systems through its effects on reservoirs’ volume, water quality, and consumption. This paper investigates these effects by analyzing the role of temperature and rainfall in water utilities’ costs with a multiple-equation cost function model and a rich firm-level database that describes the operations of 3845 firms from 2008 to 2018 in Brazil. Results reveal the presence of causal effects of rainfall and, in some cases, temperature on costs, with small firms being more vulnerable to cope with adverse (dry) weather. Results also suggest significant economies of scale and density yet to be realized by the industry. Considering the highly fragmented Brazilian urban water industry, the findings show potentially large cost savings associated with an eventual regional consolidation of operations, particularly under the realization of climate change scenarios that show hotter and drier weather conditions.

If you were a policymaker, which treatment would you disinvest? A participatory value evaluation on public preferences for active disinvestment of health care interventions in the Netherlands.

Currently, it is not known what attributes of health care interventions citizens consider important in disinvestment decision-making (i.e. decisions to discontinue reimbursement). Therefore, this study aims to investigate the preferences of citizens of the Netherlands toward the relative importance of attributes of health care interventions in the context of disinvestment. A participatory value evaluation (PVE) was conducted in April and May 2020. In this PVE, 1143 Dutch citizens were asked to save at least €100 million by selecting health care interventions for disinvestment from a list of eight unlabeled health care interventions, described solely with attributes. A portfolio choice model was used to analyze participants' choices. Participants preferred to disinvest health care interventions resulting in smaller gains in quality of life and life expectancy that are provided to older patient groups. Portfolios (i.e. combinations of health care interventions) resulting in smaller savings were preferred for disinvestment over portfolios with larger savings. The disinvestment of health care interventions resulting in smaller health gains and that are targeted at older patient groups is likely to receive most public support. By incorporating this information in the selection of candidate interventions for disinvestment and the communication on disinvestment decisions, policymakers may increase public support for disinvestment.

The scope for radiology to contribute to the NHS net zero target: findings from a survey of radiology staff in the UK

To assess attitudes towards the climate emergency among radiology staff and to identify current practices that may contribute towards the National Health Service (NHS) net zero target. An online survey of radiology staff was conducted assessing current attitudes to the climate emergency. Further questions focused on staff travel, home working, virtual conferences, and recycling. Two hundred and forty-two responses were received from all staff groups within radiology. There were high levels of concern about the climate emergency among radiology staff. Active travel accounts for a relatively small proportion of commuting related to provision of radiology services. Some energy-saving measures are implemented commonly in radiology departments but these are likely to account for only a small proportion of energy use within a department. There is significant scope for reducing the carbon footprint of radiology services by reducing travel, both for work and for radiology education. We discuss the potential for large savings related to energy-saving measures.

Spatial epidemiology and adaptive targeted sampling to manage the Chagas disease vector Triatoma dimidiata.

Widespread application of insecticide remains the primary form of control for Chagas disease in Central America, despite only temporarily reducing domestic levels of the endemic vector Triatoma dimidiata and having little long-term impact. Recently, an approach emphasizing community feedback and housing improvements has been shown to yield lasting results. However, the additional resources and personnel required by such an intervention likely hinders its widespread adoption. One solution to this problem would be to target only a subset of houses in a community while still eliminating enough infestations to interrupt disease transfer. Here we develop a sequential sampling framework that adapts to information specific to a community as more houses are visited, thereby allowing us to efficiently find homes with domiciliary vectors while minimizing sampling bias. The method fits Bayesian geostatistical models to make spatially informed predictions, while gradually transitioning from prioritizing houses based on prediction uncertainty to targeting houses with a high risk of infestation. A key feature of the method is the use of a single exploration parameter, α, to control the rate of transition between these two design targets. In a simulation study using empirical data from five villages in southeastern Guatemala, we test our method using a range of values for α, and find it can consistently select fewer homes than random sampling, while still bringing the village infestation rate below a given threshold. We further find that when additional socioeconomic information is available, much larger savings are possible, but that meeting the target infestation rate is less consistent, particularly among the less exploratory strategies. Our results suggest new options for implementing long-term T. dimidiata control.

Targeted advertisements and incentive for market consolidation in next-generation TV

The next-generation television (TV) standard will give over-the-air (OTA) broadcasters the ability to target advertisements. This could give a competitive advantage to broadcasters with more channels and hence create incentive for consolidation. Consolidation in the OTA TV industry could concern policy-makers. We construct a model to estimate revenues and costs of targeted advertising and derive profit-maximizing strategies. We find that profit is maximized by sending targeted advertisements via fixed broadband, even on devices that are watched for only a few minutes per week, but until costs drop significantly, not via mobile broadband in most cases. Our results show that targeted advertisements would not create strong incentive for consolidation in the scenarios that we consider most likely, so policy-makers should be sceptical of arguments that consolidation should be allowed on the grounds that consolidation leads to large cost savings. However, we do identify plausible scenarios where broadcasters with more channels would be significantly more profitable.

Assessing the environmental performance of ICT-based services: Does user behaviour make all the difference?

Reducing overall household energy consumption through the application of information and communication technologies (ICT) can play an important role in the transformation towards sustainable consumption patterns, e.g. through the optimisation of energy-consuming processes. The challenge in the environmental assessment of ICT applications is to also consider their use-specific environmental effects, as these can be decisive for overall results. Using the example of smart heating, we therefore analyse the environmental performance of a sample of 375 smart home systems (SHS) in Germany and show how the life cycle assessment (LCA) can be extended to include various use-specific effects such as choice of products and individuals' behaviour when using the product. In an interdisciplinary study design, we combine life cycle modelling and behavioural science to systematically include use-specific parameters into the modelling, and to interweave these results with user characteristics such as sociodemographics and user motivation. Our results are heterogenous: For the impact category Climate Change (GWP) we find that having smart heating can lead to large savings in particular cases. On average, however, smart heating does not lead to significant benefits for GWP, but neither does it represent an additional burden. For Metal Depletion Potential (MDP), we find that smart heating is always an additional burden, as heating optimisation has almost no reduction potential for MDP. Our results have a wide range due to large differences in use patterns in the sample. Depending on the impact category, both number of devices of the SHS as well as heating temperature are decisive. Regression analysis of our assessment results with user characteristics shows that differences in MDP and GWP of SHS size can be explained by income, and, in addition, differences in GWP of net heating energy savings can be explained by user motivation. Our results thus underline that the standard scenarios for user behaviour assumed in LCA modelling should be well justified. Future interdisciplinary research should further explore the links between use-specific approaches in LCA and users' environmental behaviour and motivation.

On-line motion profile optimization for reciprocating mechanisms

Reciprocating mechanisms are widely used in industry because a complex movement is achieved by a simple rotation of the driven axis. Given the tendency to evolve towards more energy-efficient machines and flexible production, motion profile optimization offers a cost-effective solution as it results in large energy savings without any hardware adaptions. However, the existing optimizers are used off-line because the position-dependent parameters such as load torque and inertia of the system model must be known in advance. When the actual machine differs from the model, or when parameters change during operation due to process flexibility, the off-line determined motion profile is no longer optimal and results in unnecessary energy consumption.This paper therefore presents an on-line approach in which the varying inertia is estimated on the actual machine and used for updating the motion profile. The sliding discrete Fourier transform is proposed for real-time estimation and a gradient-based algorithm combined with Chebyshev polynomials is proposed for on-line optimization. Experimental validation on an industrial pick-and-place unit proves that the presented method leads to similar energy savings as off-line optimizers, but without prior knowledge of the parameters, and is moreover capable of handling mass changes during operation.

Interpreting the uncertainty of model-based and design-based estimation in downscaling estimates from NFI data: a case-study in Extremadura (Spain)

ABSTRACT Remotely sensed data are increasingly used together with National Forest Inventory (NFI) data to improve the spatial precision of forest variable estimates. In this study, we combined data from the 4th Spanish National Forest Inventory (SNFI-4) and from the 2nd nationwide Airborne Laser Scanning (ALS) survey to develop predictive forest inventory variables (total over bark volume (V), basal area (G), and annual increase in total volume (IAVC)) and aboveground biomass (AGB) models for the eight major forest strata in the region of Extremadura that are included in the Spanish Forest Map (SFM). We generated maps at 25 m resolution by applying an area‐based approach (ABA) and 758 sample plots measured with good positional accuracy within the SNFI-4 in Extremadura (Spain). Inventory performance is mainly influenced by spatial scale and vegetation structure. Therefore, in this study, we conducted a comparative analysis of statistical inference methods that can characterize forest inventory variables and AGB uncertainty across multiple spatial scales and types of vegetation structure. Predictions at pixel level were used to produce county, provincial, and regional model-based estimates, which were then compared with design-based estimates at different scales for different types of forest. We developed and tested both methods for forested area (cover, 19,744.15 km2), one province (9126.78 km2), and two counties (1594.42 km2 and 2076.76 km2, respectively) in Extremadura. The resulting relative standard error (SE) for regional level forest type-specific model-based estimates of V, G, IAVC, and AGB ranged from 3.34%–14.46%, 3.22%–12.50%, 4.46%–16.67%, and 3.63%–12.58%, respectively. The performance of the model-based approach, as assessed by the relative SE, was similar to that of the design-based approach at regional and provincial levels. However, the precision of SNFI model-based estimates was higher than that of estimates based on only the plot observations in small areas (e.g. at county level). The standard errors (SE) for model-based inferences were stable across the different scales, while SNFI design-based errors were higher due to the small sample sizes available for small areas. The findings indicate that SNFI-model based maps could be used directly to estimate forest inventory variables and AGB in the major forest strata included in the Spanish Forest Map, leading to potentially large economic savings.

Is Technology Enhanced Learning Cost-effective to Improve Skills?: The Monash Objective Structured Clinical Examination Virtual Experience.

Objective Structured Clinical Examinations (OSCEs) are an accepted technique for evaluation of clinical competence in healthcare. However, the economic imperative requires faculty to control cost, using innovative educational strategies such as virtual simulation. The objective of this study was to evaluate the cost implications of implementing an online interactive learning module [Monash OSCE Virtual Experience (MOVE)]. All fourth-year pharmacy students enrolled in Monash University in 2017 were provided access to MOVE. Cost-minimization analyses were performed to evaluate the cost of introducing MOVE in the pharmacy course using the smallest cohort size (Malaysia campus) of 40 students as the base case. We also determined under what circumstances MOVE would be more cost-effective, considering the different operational situations such as when student numbers increased or when the number of simulation modules created were increased. The overall cost of setup and implementation of MOVE in the first year of implementation among 40 students was US $94.38 per student. In comparison, the face-to-face workshop cost was US $64.14 per student. On the second year of implementation, the ongoing cost of operation of MOVE was US $32.86 per student compared with US $58.97 per student using face-to-face workshop. A net benefit using MOVE was observed after the third year of implementation. Larger savings were noted when the cohort size extends larger than 100 students. Monash OSCE Virtual Experience was a flexible and cost-effective approach to aid students in preparation for an OSCE and enhanced students' learning experience. The wider applicability of these findings will need to be explored in other settings.

Optimal Use of Lignocellulosic Biomass for the Energy Transition, Including the Non-Energy Demand: The Case of the Belgian Energy System

Biomass is a key renewable resource for energy transition and climate change mitigation. It can be used for either energy purposes (production of heat, electricity, and fuel) or non-energy demand (e.g., chemicals). This raises the question of the optimal use of biomass in energy systems. In the literature, this optimal use is often determined for one specific situation in terms of greenhouse gas emissions and rarely considering the non-energy demand. The non-energy demand is defined as the demand for energy products used as raw materials. Given the expected simultaneous changes in all industrial sectors, it is important to include the non-energy demand in the models of energy systems as they will share common resources. This paper 1) studies the optimal use of lignocellulosic biomass within an energy system including the non-energy demand and 2) analyzes the evolution of its role throughout the energy transition. Belgium is taken as a case study as it presents a non-energy demand corresponding to ∼15% of its primary energy mix. The energy system is modeled with EnergyScope TD which optimizes whole-energy systems in terms of costs under greenhouse gas emission constraints. Local and imported biomass is considered with two potential scenarios. Fourteen biomass-converting technologies are included in the model. It is shown that high-temperature heat remains a significant application for biomass in all scenarios and increases when moving toward carbon neutrality. For greenhouse gas savings below 50%, biomass is largely used for low-temperature heat. However, when aiming at reducing greenhouse gas further (>50% reduction), biomass is substantially exploited for the non-energy demand. Electricity from biomass also appears, to a lesser extent, for large greenhouse gas savings only. The integration of the non-energy demand in the simulations impacts the allocation of biomass in the system, depending on the scenario of potential considered.

A Novel Method to Reduce ELISA Serial Dilution Assay Workload Applied to SARS-CoV-2 and Seasonal HCoVs.

Assays using ELISA measurements on serially diluted serum samples have been heavily used to measure serum reactivity to SARS-CoV-2 antigens and are widely used in virology and elsewhere in biology. We test a method using Bayesian hierarchical modelling to reduce the workload of these assays and measure reactivity of SARS-CoV-2 and HCoV antigens to human serum samples collected before and during the COVID-19 pandemic. Inflection titers for SARS-CoV-2 full-length spike protein (S1S2), spike protein receptor-binding domain (RBD), and nucleoprotein (N) inferred from 3 spread-out dilutions correlated with those inferred from 8 consecutive dilutions with an R2 value of 0.97 or higher. We confirm existing findings showing a small proportion of pre-pandemic human serum samples contain cross-reactive antibodies to SARS-CoV-2 S1S2 and N, and that SARS-CoV-2 infection increases serum reactivity to the beta-HCoVs OC43 and HKU1 S1S2. In serial dilution assays, large savings in resources and/or increases in throughput can be achieved by reducing the number of dilutions measured and using Bayesian hierarchical modelling to infer inflection or endpoint titers. We have released software for conducting these types of analysis.

Saving tax on renovations

While improvements and renovations can be expensive, clinics that follow the rules set down by HM Revenue and Customs can make large savings on their expenditure, says Adam Bernstein

Which policy instrument do citizens and civil servants prefer? A choice experiment on Swedish marine policy

Abstract In the choice between alternative environmental policy instruments, economists tend to favor policies capable of attaining cost-efficiency, but other considerations may be more important to stakeholders. We perform a choice experiment modeled on Swedish water and marine policy to estimate preferences for different policy instruments among citizens and municipal civil servants. Both the modal citizen and the modal civil servant prefer direct regulation and subsidies to nutrient trading. Moreover, nutrient trading is unlikely to deliver sufficiently large cost savings for civil servants to prefer it to other instruments. These results are consistent with the apparent reluctance to adopt water quality trading in Europe.