Air and Water Flowrate Optimisation for a Fan Coil Unit in Heat Pump Systems

The degradation in efficiency of auxiliary components in heating/cooling systems when operating at part load is frequently reported. Through the use of variable speed components, the supplied capacity can be reduced to match the required load and hence reduce unnecessary energy consumption. However, for fan coil units, difficulties can arise when optimizing fan and pump speeds at part load. Practically locating optimal water and air flow rates from readily available information and for varying supplied capacities is necessary, in order to reduce the fan coil power consumption. This research attempts to identify whether optimal fan and pump speeds exist for a fan coil unit and how they can be implemented, in a practical manner, in a system control applications. Using an empirical fan coil and pump model, the total power consumption (fan and pump) for different combinations of fan and pump speeds over a range of capacities was calculated. It was observed that, for a given capacity, an optimal combination of fan and pump speeds exists and there was a significant change in power consumption for different combinations of fan and pump speeds supplying the same capacity. A control strategy is described that utilizes a simple fan coil capacity estimation model, coupled with air and water flow rates, along with nominal design data. The pump speed is optimized using PID control to maintain the space temperature at the chosen set-point, which matches the supplied capacity to the required capacity. At set-time intervals, the capacity estimation model is utilized to optimize the water and air flow rates for the required capacity. The control strategy is evaluated, using a full building simulation model for a daily load profile and is compared to two baseline conditions: for no control of the fancoils/pump combination and for PID circulation control of the pump only. The optimal fan and pump speed control resulted in a 43% and 24% decrease in power consumption with compared to the no control baseline and the PID controlled circulation pump strategy, respectively

Development of a Soft Actor Critic Deep Reinforcement Learning Approach for Harnessing Energy Flexibility in a Large Office Building

This research is concerned with the novel application and investigation of `Soft Actor Critic' (SAC) based Deep Reinforcement Learning (DRL) to control the cooling setpoint (and hence cooling loads) of a large commercial building to harness energy flexibility. The research is motivated by the challenge associated with the development and application of conventional model-based control approaches at scale to the wider building stock. SAC is a model-free DRL technique that is able to handle continuous action spaces and which has seen limited application to real-life or high-fidelity simulation implementations in the context of automated and intelligent control of building energy systems. Such control techniques are seen as one possible solution to supporting the operation of a smart, sustainable and future electrical grid. This research tests the suitability of the SAC DRL technique through training and deployment of the agent on an EnergyPlus based environment of the office building. The SAC DRL was found to learn an optimal control policy that was able to minimise energy costs by 9.7% compared to the default rule-based control (RBC) scheme and was able to improve or maintain thermal comfort limits over a test period of one week. The algorithm was shown to be robust to the different hyperparameters and this optimal control policy was learnt through the use of a minimal state space consisting of readily available variables. The robustness of the algorithm was tested through investigation of the speed of learning and ability to deploy to different seasons and climates. It was found that the SAC DRL requires minimal training sample points and outperforms the RBC after three months of operation and also without disruption to thermal comfort during this period. The agent is transferable to other climates and seasons although further retraining or hyperparameter tuning is recommended.Comment: submitted to Energy and A

Environmental and economic benefits of building retrofit measures for the residential sector by utilizing sensor data and advanced calibrated models

The present paper investigates the energy savings associated with the implementation of retrofitting measures on Irish residential buildings. A detached residential dwelling, representative of approximately 40% of the residential stock in Ireland, was selected as experimental test bed. The building was progressively retrofitted to an all-electric dwelling. Retrofit measures included the installation of a photovoltaic array, a geothermal heat pump, an electric vehicle charging point, along with building fabric upgrades. The building was equipped with a home area network with more than 30 sensors with 15 min monitoring resolution. The experimental data collected during the experimental campaign aided the comprehensive calibration of an EnergyPlus model. This model was used to investigate the effectiveness of the implemented retrofit measures in terms of energy savings and CO2 reductions. Real-time data from the Irish power system operator was used to calculate the building carbon footprint for different levels of renewable energy penetration to the national grid. Results show that the all-electric retrofitted building can achieve energy savings of up to 45%, with CO2 reductions of approximately 29%, compared to the pre-retrofitted building. Implementing the retrofit measures at scale could potentially lead to carbon emission reductions up to 14% for rural areas in Ireland

Impact of intelligent control algorithms on demand response flexibility and thermal comfort in a smart grid ready residential building

The present paper investigates the impact of advanced control algorithms on harnessing building energy flexibility in a smart-grid ready full-electric residential building. The impact on thermal comfort is also analysed. The building is located in Ireland and is equipped with a geothermal heat pump and a thermal energy storage system. Two Energy Management systems, based on rule-based and intelligent optimisation algorithm approaches, are developed which use real-time building smart meter and weather data. This data is utilised by various dynamic flexibility metrics within the respective control algorithms. Different time of use tariffs, based on data from the Irish Commission for Energy Regulation and structured on the basis of peak, off-peak and night periods, are also used. Results show that energy cost reductions of up to 21% and 43% can be achieved by the rule-based and intelligent algorithm, respectively, without compromising the thermal comfort within the building. Moreover, total shifting and forcing flexibility potential of up to 34 and 54 kWh, respectively, based on the month of January, can be achieved by the adoption of the intelligent control algorithm

A fundamental unified framework to quantify and characterise energy flexibility of residential buildings with multiple electrical and thermal energy systems

To date, the energy flexibility assessment of multicomponent electrical and thermal systems in residential buildings is hindered by the lack of adequate indicators due to the different interpretations, properties, and requirements that characterise an energy flexible building. This paper addresses this knowledge gap by presenting a fundamental energy flexibility quantification framework applicable to various energy systems commonly found in residential buildings (i.e., heat pumps, renewables, thermal and electrical storage systems). Using this framework, the interactions between these systems are analysed, as well as assessing the net energy cost of providing flexibility arising from demand response actions where onsite electricity production is present. A calibrated white-box model of a residential building developed using EnergyPlus (including inter alia a ground source heat pump, a battery storage system, and an electric vehicle) is utilised. To acquire daily energy flexibility mappings, hourly independent, and consecutive demand response actions are imposed for each energy system, using the proposed indicators. The obtained flexibility maps give insights into both the energy volumes associated with demand response actions and qualitative characteristics of the modulated electricity consumption curves. The flexibility potential of each studied energy system is determined by weather and occupant thermal comfort preferences as well as the use of appliances, lighting, etc. Finally, simulations show that zone and water tank thermostat modulations can be suitably combined to shift rebound occurrences away from peak demand periods. These insights can be used by electricity aggregators to evaluate a portfolio of buildings or optimally harness the flexibility of each energy system to shift peak demand consumption to off-peak periods or periods of excess onsite electricity generation

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK.

BACKGROUND: A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. METHODS: This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. FINDINGS: Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0-75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4-97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8-80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3-4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. INTERPRETATION: ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. FUNDING: UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D'Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials

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