Three units in literature

Thesis (Ed.M.)--Boston Universit

Three units in literature

Thesis (Ed.M.)--Boston Universit

Impact of spatiotemporal heterogeneity in heat pump loads on generation and storage requirements

This paper investigates how spatiotemporal heterogeneity in inflexible residential heat pump loads affects the need for storage and generation in the electricity system under business-as-usual and low-carbon emissions budgets. Homogeneous and heterogeneous heat pump loads are generated using population-weighted average and local temperature, respectively, assuming complete residential heat pump penetration. The results of a storage and generation optimal expansion model with network effects for spatiotemporally homogeneous and heterogeneous load profiles are compared. A case study is performed using a 3-bus network of London, Manchester, and Glasgow in Britain for load and weather data for representative weeks. Using heterogeneous heating demand data changes storage sizing: under a business-as-usual budget, 26% more total storage is built on an energy and power basis, and this storage is distributed among all of the buses in the heterogeneous case. Under a low-carbon budget, total energy storage at all buses increases 2 times on an energy basis and 40% on a power basis. The energy to power ratio of storage at each bus also increases when accounting for heterogeneity; this change suggests that storage will be needed to provide energy support in addition to power support for electric heating in high-renewable power systems. Accounting for heterogeneity also increases modeled systems costs, particularly capital costs, because of the need for higher generation capacity in the largest load center and coincidence of local peak demand at different buses. These results show the importance of accounting for heat pump load heterogeneity in power system planning.Comment: 6 pages, 4 figures, to be published in the proceedings of the IEEE Power and Energy Society General Meeting 202

Data-based, high spatiotemporal resolution heat pump demand for power system planning

Decarbonizing the residential building sector by replacing gas boilers with electric heat pumps will dramatically increase electricity demand. Existing models of future heat pump demand either use daily heating demand profiles that do not capture heat pump use or do not represent sub-national heating demand variation. This work presents a novel method to generate high spatiotemporal resolution residential heat pump demand profiles based on heat pump field trial data. These spatially varied demand profiles are integrated into a generation, storage, and transmission expansion planning model to assess the impact of spatiotemporal variations in heat pump demand. This method is demonstrated and validated using the British power system in the United Kingdom (UK), and the results are compared with those obtained using spatially uniform demand profiles. The results show that while spatially uniform heating demand can be used to estimate peak and total annual heating demand and grid-wide systems cost, high spatiotemporal resolution heating demand data is crucial for spatial power system planning. Using spatially uniform heating demand profiles leads to 15.1 GW of misplaced generation and storage capacity for a 90% carbon emission reduction from 2019. For a 99% reduction in carbon emissions, the misallocated capacity increases to 16.9-23.9 GW. Meeting spatially varied heating load with the system planned for uniform national heating demand leads to 5% higher operational costs for a 90% carbon emission reduction. These results suggest that high spatiotemporal resolution heating demand data is especially important for planning bulk power systems with high shares of renewable generation

A national data-based energy modelling to identify optimal heat storage capacity to support heating electrification

Heating decarbonisation through electrification is a difficult challenge due to the considerable increase in peak power demand. This research proposes a novel modelling approach that utilises easily accessible national-level data to identify the required heat storage volume in buildings to decrease peak power demand and maximises carbon reductions associated with electrified heating technologies through smart demand-side response. The approach assesses the optimal shifting of heat pump operation to meet thermal heating demand according to different heat storage capacities in buildings, which are defined in relation to the time (in hours) in which the heating demand can be provided directly from the heat battery, without heat pump operation. Ten scenarios (S) are analysed: two baselines (S1–S2) and eight load shifting strategies (S3–S10) based on hourly and daily demand-side responses. Moreover, they are compared with a reference scenario (S0), with heating currently based on fossil fuels. The approach was demonstrated in two different regions, Spain and the United Kingdom. The optimal heat storage capacity was found on the order of 12 and 24 h of heating demand in both countries, reducing additional power capacity by 30–37% and 40–46%, respectively. However, the environmental benefits of heat storage alternatives were similar to the baseline scenario due to higher energy consumption and marginal power generation based on fossil fuels. It was also found that load shifting capability below 4 h presents limited benefits, reducing additional power capacity by 10% at the national scale. The results highlight the importance of integrated heat storage technologies with the electrification of heat in highly gas-dependent regions. They can mitigate the need for an additional fossil-based dispatchable generation to meet high peak demand. The modelling approach provides a high-level strategy with regional specificity that, due to common datasets, can be easily replicated globally. For reproducibility, the code base and datasets are found on GitHub

A national data-based energy modelling to identify optimal heat storage capacity to support heating electrification

Heating decarbonisation through electrification is a difficult challenge due to the considerable increase in peak power demand. This research proposes a novel modelling approach that utilises easily accessible national-level data to identify the required heat storage volume in buildings to decrease peak power demand and maximises carbon reductions associated with electrified heating technologies through smart demand-side response. The approach assesses the optimal shifting of heat pump operation to meet thermal heating demand according to different heat storage capacities in buildings, which are defined in relation to the time (in hours) in which the heating demand can be provided directly from the heat battery, without heat pump operation. Ten scenarios (S) are analysed: two baselines (S1–S2) and eight load shifting strategies (S3–S10) based on hourly and daily demand-side responses. Moreover, they are compared with a reference scenario (S0), with heating currently based on fossil fuels. The approach was demonstrated in two different regions, Spain and the United Kingdom. The optimal heat storage capacity was found on the order of 12 and 24 h of heating demand in both countries, reducing additional power capacity by 30–37% and 40–46%, respectively. However, the environmental benefits of heat storage alternatives were similar to the baseline scenario due to higher energy consumption and marginal power generation based on fossil fuels. It was also found that load shifting capability below 4 h presents limited benefits, reducing additional power capacity by 10% at the national scale. The results highlight the importance of integrated heat storage technologies with the electrification of heat in highly gas-dependent regions. They can mitigate the need for an additional fossil-based dispatchable generation to meet high peak demand. The modelling approach provides a high-level strategy with regional specificity that, due to common datasets, can be easily replicated globally. For reproducibility, the code base and datasets are found on GitHub

Factors associated with completion of bowel cancer screening and the potential effects of simplifying the screening test algorithm

BACKGROUND: The primary colorectal cancer screening test in England is a guaiac faecal occult blood test (gFOBt). The NHS Bowel Cancer Screening Programme (BCSP) interprets tests on six samples on up to three test kits to determine a definitive positive or negative result. However, the test algorithm fails to achieve a definitive result for a significant number of participants because they do not comply with the programme requirements. This study identifies factors associated with failed compliance and modifications to the screening algorithm that will improve the clinical effectiveness of the screening programme. METHODS: The BCSP Southern Hub data for screening episodes started in 2006–2012 were analysed for participants aged 60–69 years. The variables included age, sex, level of deprivation, gFOBt results and clinical outcome. RESULTS: The data set included 1 409 335 screening episodes; 95.08% of participants had a definitively normal result on kit 1 (no positive spots). Among participants asked to complete a second or third gFOBt, 5.10% and 4.65%, respectively, failed to return a valid kit. Among participants referred for follow up, 13.80% did not comply. Older age was associated with compliance at repeat testing, but non-compliance at follow up. Increasing levels of deprivation were associated with non-compliance at repeat testing and follow up. Modelling a reduction in the threshold for immediate referral led to a small increase in completion of the screening pathway. CONCLUSIONS: Reducing the number of positive spots required on the first gFOBt kit for referral for follow-up and targeted measures to improve compliance with follow-up may improve completion of the screening pathway

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Abstract Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions. </jats:sec

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570