Estimates Of Savings Research Articles

Water conservation criteria in green building evaluation systems and estimation of possible water savings in the case of application of these criteria on a detached house

Water conservation criteria in green building evaluation systems and estimation of possible water savings in the case of application of these criteria on a detached house

Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.

Estimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods. We propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial. Our study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm. Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods. We explore the statistical considerations of the current method for estimating time savings. We proposed alternative methods that provide time savings estimations based on the observed absolute differences. By using various methods, a more comprehensive estimation of time savings can be achieved.

Assessing the environmental performance of green mortgage‐backed securities

AbstractThe green bond market is growing substantially, bringing with it a focus on economic and environmental performance. Yet while extensive work exists examining the former, there is little concrete evidence regarding the efficacy of green bond use‐of‐proceeds. Concurrently, the demand for ESG‐compliant investments provides an opportunity to direct capital toward the rehabilitation of one of the most energy‐intensive asset classes: real estate. One program in this space, the Fannie Mae Green Rewards green bond program, offers incentives to borrowers to increase multifamily building energy and water efficiency. Although all program participants must complete a set of preapproved projects targeting energy and water efficiency within 12 months of loan origination, there exists substantial variation in the realization of postorigination efficiency outcomes, and in the variation between projected and actual efficiency improvements. We find that fixed interest rates and supplemental financing loan structures are associated with postorigination energy efficiency improvements, as are newer, larger, and high‐quality assets. However, the ex ante estimates of efficiency savings provided to prospective investors prove unrelated to the efficiency outcomes. These findings highlight opportunities to improve program transparency and calibration across the green bond universe.

Towards Carbon Footprint Management in Hybrid Multicloud

Enterprises today aspire to optimize the operating costs and carbon footprint (CFP) of their IT operations jointly without compromising their business imperatives. This has given rise to a hybrid approach in which enterprises retain the dynamic choice to leverage private data centers and one or more public clouds in conjunction. While cloud service providers (CSPs) have long provided APIs for estimating, reconciling, and optimizing operating costs, they have only recently started exposing APIs related to CFP. Indeed, this is a step in the right direction. Nevertheless, our analyses of these APIs reveals many gaps that need to be addressed to facilitate sizing and placement decisions that can factor in carbon. First, there is a lack of standardized, transparent methodology for CFP quantification across different CSPs. Second, the coarse granularity of the CFP data provided today can help with post-facto reporting but is not suitable for proactive fine-grained optimization. Last, enterprises themselves are unable to independently compute the current CFP or estimate potential CFP savings since CSPs do not share the required power usage data. To address these gaps, enterprises have started developing their own carbon assessment methodologies and tools to estimate the CFP of workloads running on public clouds using the available user-facing APIs. These systems hold the promise for an independent and unbiased evaluation and estimation of relative savings between different deployment options by cloud users. We describe and analyze the details of CSP-native carbon-reporting tools and their quantification methodology, and the "outside-of-the-cloud" estimation approaches. Finally, we present opportunities for future research in the direction of trustworthy, fine-grained, public cloud workload CFP estimation, which is a prerequisite for meaningful realization of carbon optimization.

APPLICABILITY OF THE "TYPOLOGY OF RESIDENTIAL BUILDINGS IN BOSNIA AND HERZEGOVINA", AT A MUNICIPALITY OR CITY LEVEL, CASE STUDY - SINGLE-FAMILY HOUSES IN THE CITY DERVENTA

<p class="ABSTRACT">In order to make correct estimates of energy consumption for heating, reduction of energy consumption, and CO2 emissions by applying energy efficiency measures, it is necessary to know the structure and characteristics of the building stock. The Typology of residential buildings in Bosnia and Herzegovina identified the structure and characteristics of residential building stock through different periods at the level of Bosnia and Herzegovina. This paper analyses the differences between national and city or municipal typology. Conducted analysis for the City Derventa, shows that in the case of single-family houses, the application of national instead of local typology can result in certain deviations in the estimation of energy consumption, savings, and CO2 emissions.</p>

Impact of time resolution on estimation of energy savings using a copula-based calibration in UBEM

Urban Building Energy modelling (UBEM) has emerged in the last decade as an important tool to accelerate energy transition in the building sector. To fulfil one of its major purposes - forecasting energy savings for potential energy conservation measures at an urban scale, several challenges are still to be addressed. Two key challenges include: 1) the need to calibrate models with a large number of unknown parameters across numerous buildings (either individually or through archetype representation); 2) the limited availability of high-resolution measured data, which raises concerns about calibrated models based solely on yearly values for accurate energy savings forecast. This study addresses these challenges using a case study of 35 buildings in a district in Stockholm, Sweden. Firstly, a new iterative Approximate Bayesian Computation (ABC) method for calibration is proposed, incorporating a copula-based sampling process at each iteration. Secondly, the new calibration process is applied with three different time resolutions to examine the impact of data resolution on forecasted energy usage, particularly when applied to a classical energy conservation measure. Results demonstrate the efficiency of the new method across the 35 buildings, facilitating the rapid population of a final joint distribution for the nine unknown parameters considered in each building. While the marginals may be strongly influenced by the time resolution, the forecasted energy consumption remains identical across the three analysed time resolutions. However, a noticeable difference is observed when the ECM pertains to a formerly unknown or known parameter.

“Time Saved” Calculations to Improve Decision-Making in Progressive Disease Studies

BackgroundDisease modifying therapies (DMTs) may be most beneficial in early disease, when progression is slow and changes small, with clinical relevance difficult to interpret.ObjectivesTime component tests (TCTs) translate differences between treatments from mean change, vertical distance between longitudinal trajectories, into intuitively understood time saved, horizontal distance between trajectories, which can be readily combined across endpoints in a global TCT (gTCT).DesignThe value of composites, time savings estimates, and combination scores to optimize measurement and interpretation of DMTs are demonstrated, along with construction details and simulation studies.SettingTCT methods were applied to a randomized phase II clinical trial.ParticipantsPatients with early Alzheimer’s disease (N=332).InterventionThree treatment groups with AFFITOPE® AD02 and two control groups with aluminum oxyhydroxide, AD04.MeasurementsThe co-primary efficacy outcomes were an adapted ADAS-Cog (aADAS) and adapted ADCS-ADL (aADL), which were optimized composite scales specific to cognitive and functional domains. A composite based on these two scores was the study’s prespecified primary outcome. The CDR-sb and standard non-adapted ADCS-ADL and ADAS-Cog scales were prespecified secondary outcomes.ResultsThe AD04 2 mg group showed some statistically significant effects compared with other study arms. It is unclear whether the observed 3.8-point difference on the composite is clinically meaningful. TCT results show a time savings of 11 months in an 18-month study with AD04 2 mg.ConclusionThe relevance of 11 months saved is more universally understood than a mean difference of 3.8 points in the composite outcome. These results suggest that a combination of a composite approach and a time savings interpretation offers a powerful approach for detecting and interpreting disease modifying effects.

An Estimation of the Energy Savings of a Mainline Diesel Locomotive Equipped with an Energy Storage Device

The method of improving a two-section mainline diesel locomotive by using energy storage in the traction system is considered. A mathematical model was developed to study the movement of a diesel locomotive based on the recommendations and provisions of the theory of locomotive traction. For this purpose, the movement of a diesel locomotive as part of a train along a given section of a track was studied. It was determined that the use of an energy storage device on a diesel locomotive will allow up to 64% of the energy spent on train traction to accumulate. The use of energy storage in the accumulator during electrodynamic braking ensured a reduction in fuel consumption by about 50%, regardless of the options for equipping the traction system of the diesel locomotive with an energy accumulator. It is established that regardless of the options for equipping the traction system of the diesel locomotive with an energy storage device, the indicators characterizing the degree of use of the diesel engine do not change. These research results can be used in works devoted to the improvement of the control system of energy exchange between the accumulator and traction engines of diesel locomotives.

The inscrutable baseline and the problem of attribution

This paper examines the problem of attribution in the evaluation of energy efficiency program impact. The methodological problem concerns the observability of consumer behavior under the baseline condition of no program intervention. The statistical solution to the problem, which entails randomized exposure of targeted individuals to program influence, is not a viable alternative in most applications. Randomized opt-in and randomized encouragement designs do not conform to this requirement because all targeted individuals are encouraged to participate in the program, resulting in negative exposure bias. Quasi-experimental methods which utilize non-targeted individuals or targeted nonparticipants as baseline surrogates are further subject to selection bias of unknown magnitude and direction. Valid attribution in the general case of unrestricted eligibility depends on prior knowledge of the determinants of measure adoption and program participation. In default of such knowledge, evaluators must rely upon structural assumptions that have no foundation in empirical science. On the other hand, established measurement and verification methods which exploit scientific knowledge of the determinants of end-use energy consumption should be utilized to obtain unbiased estimates of individual measure and gross program energy savings.

Value of pharmacy services for common illness symptoms covered by universal coverage at drugstore compared to outpatient services at a hospital in Thailand.

Drug stores is an option that people can receive health care services for their common illnesses. This is the first study aims to estimate cost savings for 16 common illness symptoms to the Thailand's health system. This study gathered retrospective secondary data from several studies and surveyed the median cost of medicines. Cost savings of care provided by pharmacists at drug stores in comparison to out-patient department (OPD) services at hospitals were quantified using cost of illness approach. The average number of hospital visits for treatment for 16 common illness symptoms was 2,356 visits per month. The estimation of the cost savings per visit from three perspectives, including government, patient, and societal, at tertiary care hospitals were 12.7-19.4, 12.7-25.6, and 18.9-25.6 USD, and at secondary care hospitals were 6.0-12.7, 6.0-18.9, and 12.2-18.9 USD. Every $1 reimbursed at drug stores will save additional costs in Thailand's health system, ranging from $0.04 to $0.24 and $0.02 to $0.16 at tertiary care hospitals and secondary hospitals, respectively. Pharmacy services for 16 common illness symptoms can clearly save costs.

(253) Use of Online Pharmacy Tools May Lead to Significantly Reduced National Expenditures on Vaginal Estrogen

Abstract Introduction High medication costs for vaginal estrogen may create a barrier for patients seeking treatment for numerous urinary and vaginal symptoms and lead to poor medication adherence. The Mark Cuban Cost Plus Drug Company (CPD) and GoodRx tools offer patients a method to purchase prescription medications at a discount, which may lead to improved medication adherence and decreased national expenditures on such medications. Objective To compare the pricing of vaginal estrogen as advertised by retail pharmacies, Medicare, and discount listings through CPD and GoodRx. Methods A review of publicly available data from CPD and GoodRx was performed to obtain listed retail and discounted prices for Estrace (topical), Vagifem (tablet), and Premarin (topical). GoodRx prices were obtained using prices from Costco, CVS, Walgreens, and Walmart pharmacies in the most from populous zip code from each of the 3 most populous U.S. states: California, New York, and Texas. Prices were adjusted to account for dosage and prescribed quantity to estimate an average cost per dosage unit ($/adu). The Medicare Part D Drug Spending and Utilization data from 2021 were used to report the average spending per dosage unit and total expenditure for each of the listed medications. These data were compared to create an estimate of average national savings after use of CPD and/or GoodRx. Results Average spending per dosage unit for Estrace, Vagifem, and Premarin was lesser when discount tools were used (0.50 $/adu, 3.75 $/adu, and 4.30 $/adu respectively), compared to Medicare pricing (6.14 $/adu, 20.95 $/adu, and 10.10 $/adu respectively) or retail pricing (3.14 $/adu, 10.19 $/adu, and 5.43 $/adu respectively). When adjusted for total dosage units, use of CPD over Medicare pricing for the three medications would result in a combined annual national saving of $64.2M. Use of either CPD or GoodRx compared to retail pricing would similarly result in a combined annual national saving of $39.2M. Conclusions The utilization of CPD and GoodRx in the prescription of vaginal estrogen led to a substantial national average cost savings when compared to retail and Medicare pricing. CPD and GoodRx may offer a way to decrease the cost burden for patients seeking treatment for urinary and vaginal symptoms and significantly reduce national expenditures on medications. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: The utilization of CPD and GoodRx in the prescription of vaginal estrogen led to a substantial national average cost savings when compared to retail and Medicare pricing. CPD and GoodRx may offer a way to decrease the cost burden for patients seeking treatment for urinary and vaginal symptoms and significantly reduce national expenditures on medications.

The impact of formal care provision on informal care receipt for people over 75 in England.

In this study, we examine the relationship between formal care provision and informal care receipt from within the household for people over 75 years old using data from the British Household Panel Survey between 1991 and 2009. To address potential concerns about endogeneity of formal care we use a 'spatial lag' instrumental variable. We find a negative and statistically significant effect of formal care provision on informal care receipt from within the household, suggesting a substantial degree of substitutability between these two modes of care. These findings provide grounds for estimates of savings in the cost of informal care enabled by spending on formal care, which is important in light of the effects of the caregiving burden and associated responsibilities on carer's labour market participation.

(317) Significant Cost Savings for Erectile Dysfunction Medications are Available Using Discount Online Pharmacies Compared to Medicare

Abstract Introduction The Mark Cuban Cost Plus Drug Company (CPD) is an online retailer launched in January 2022 that sells generic prescription medications directly to consumers at cost of ingredients and manufacturing plus a fixed 15% margin in addition to a small pharmacy dispensing fee and shipping fee. GoodRx is an online tool which offers coupons redeemable at pharmacies for discounts on prescription medications. The combination of these two tools offers physicians a way to provide prescription medications to patients at lower costs, which may lead to improved medication adherence and lower medication expenditures nationally. Objective To compare the cost of various erectile dysfunction medications when purchased through retail pharmacies, reimbursed through Medicare, or obtained utilizing CPD and GoodRx. Methods A review of publicly available data from CPD and GoodRx was performed to obtain average retail and discounted prices for generic sildenafil, tadalafil, and vardenafil. GoodRx prices were obtained using prices from Costco, CVS, Walgreens, and Walmart pharmacies in the most from populous zip code from each of the 3 most populous U.S. states: California, New York, and Texas. Prices were adjusted to account for dosage and prescribed quantity to estimate an average cost per dosage unit ($/adu). The Medicare Part D Drug Spending and Utilization data from 2021 were used to report the average spending per dosage unit and total expenditure for each of the listed medications. These data were compared to create an estimate of average national savings after use of CPD or GoodRx. Results Average spending per dosage unit for sildenafil, tadalafil, and vardenafil was less when GoodRx or CPD were used (0.28 $/adu, 0.31 $/adu, and 6.17 $/adu respectively), compared to Medicare pricing (2.14 $/adu, 8.08 $/adu, and 27.84 $/adu respectively) or retail pricing (0.52 $/adu, 2.82 $/adu, and 8.35 $/adu respectively). When adjusted for total dosage units, use of CPD over Medicare pricing for the three medications would result in a combined annual national saving of $149M. Use of either CPD or GoodRx compared to retail pricing would similarly result in a combined annual nation saving of $40M. Conclusions The utilization of CPD and GoodRx in the prescription of common erectile dysfunction medications may lead to significant reductions in pricing compared to retail and Medicare estimates. Knowledge of these prescription tools may lead to significant reductions in national expenditures on medications and decreased cost burden for patients seeking treatment. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Advisory board and speaker for Coloplast; consultant for Cynosure; advisory board and speaker for Halozyme; intellectual property with Masimo; advisory board for Promescent; consultant for Sprout; advisory board for Xialla.

(003) Use of Online Pharmacy Tools May Lead to Significantly Reduced National Expenditures on Vaginal Estrogen

Abstract Introduction High medication costs for vaginal estrogen may create a barrier for patients seeking treatment for numerous urinary and vaginal symptoms and lead to poor medication adherence. The Mark Cuban Cost Plus Drug Company (CPD) and GoodRx tools offer patients a method to purchase prescription medications at a discount, which may lead to improved medication adherence and decreased national expenditures on such medications. Objective To compare the pricing of vaginal estrogen as advertised by retail pharmacies, Medicare, and discount listings through CPD and GoodRx. Methods A review of publicly available data from CPD and GoodRx was performed to obtain listed retail and discounted prices for Estrace (topical), Vagifem (tablet), and Premarin (topical). GoodRx prices were obtained using prices from Costco, CVS, Walgreens, and Walmart pharmacies in the most from populous zip code from each of the 3 most populous U.S. states: California, New York, and Texas. Prices were adjusted to account for dosage and prescribed quantity to estimate an average cost per dosage unit ($/adu). The Medicare Part D Drug Spending and Utilization data from 2021 were used to report the average spending per dosage unit and total expenditure for each of the listed medications. These data were compared to create an estimate of average national savings after use of CPD and/or GoodRx. Results Average spending per dosage unit for Estrace, Vagifem, and Premarin was lesser when discount tools were used (0.50 $/adu, 3.75 $/adu, and 4.30 $/adu respectively), compared to Medicare pricing (6.14 $/adu, 20.95 $/adu, and 10.10 $/adu respectively) or retail pricing (3.14 $/adu, 10.19 $/adu, and 5.43 $/adu respectively). When adjusted for total dosage units, use of CPD over Medicare pricing for the three medications would result in a combined annual national saving of $64.2M. Use of either CPD or GoodRx compared to retail pricing would similarly result in a combined annual national saving of $39.2M. Conclusions The utilization of CPD and GoodRx in the prescription of vaginal estrogen led to a substantial national average cost savings when compared to retail and Medicare pricing. CPD and GoodRx may offer a way to decrease the cost burden for patients seeking treatment for urinary and vaginal symptoms and significantly reduce national expenditures on medications. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Advisory board and speaker for Coloplast; consultant for Cynosure; advisory board and speaker for Halozyme; intellectual property with Masimo; advisory board for Promescent; consultant for Sprout; advisory board for Xialla.

Improvements in Work Productivity and Activity Impairment Among Adults With Anxiety or Depressive Symptoms Participating in a Relational Agent-Delivered Digital Mental Health Intervention.

The study aimed to assess changes between baseline and end of treatment in work-related absenteeism, presenteeism, productivity, and nonwork-related activity impairment and estimate cost savings associated with observed improvements. Data from 91 employed adult participants who enrolled in a single-arm, exploratory study of a relational agent-delivered digital mental health intervention and completed Work Productivity and Activity Impairment assessments were analyzed; overall work productivity improvement was multiplied by the overall and education-adjusted US median annual salary to arrive at potential cost savings estimates. Adjusted models indicated more than 20% improvements in presenteeism, work productivity impairment, and activity impairment, yielding cost-savings estimates between $14,000 and more than $18,000 annually. Relational agent-delivered digital mental health interventions may be associated with improvements in work productivity and activity impairment, which could result in a sizable cost savings.

A Cost and Waste-Savings Comparison Between Single-Use and Reusable Pulse Oximetry Sensors Across US Operating Rooms.

Operating room (OR) expenditures and waste generation are a priority, with several professional societies recommending the use of reprocessed or reusable equipment where feasible. The aim of this analysis was to compare single-use pulse oximetry sensor stickers ("single-use stickers") versus reusable pulse oximetry sensor clips ("reusable clips") in terms of annual cost savings and waste generation across all ORs nationally. This study did not involve patient data or research on human subjects. As such, it did not meet the requirements for institutional review board approval. An economic model was used to compare the relative costs and waste generation from using single-use stickers versus reusable clips. This model took into account: (1) the relative prices of single-use stickers and reusable clips, (2) the number of surgeries and ORs nationwide, (3) the workload burden of cleaning the reusable clips, and (4) the costs of capital for single-use stickers and reusable clips. In addition, we also estimated differences in waste production based on the raw weight plus unit packaging of single-use stickers and reusable clips that would be disposed of over the course of the year, without any recycling interventions. Estimated savings were rounded to the nearest $0.1 million. The national net annual savings of transitioning from single-use stickers to reusable clips in all ORs ranged from $510.5 million (conservative state) to $519.3 million (favorable state). Variability in savings estimates is driven by scenario planning for replacement rate of reusable clips, workload burden of cleaning (ranging from an additional expense of $618k versus a cost savings of $309k), and cost of capital-interest gained on investment of capital that is freed up by the monetary savings of a transition to reusable clips contributes between $541k (low-interest rates of 2.85%) and $1.3 million (high-interest rates of 7.08%). The annual waste that could be diverted from landfill by transitioning to reusable clips was found to be between 587 tons (conservative state) up to 589 tons (favorable state). If institutions need to purchase new vendor monitors or cables to make the transition, that may increase the 1-time capital disbursement. Using reusable clips versus single-use stickers across all ORs nationally would result in appreciable annual cost savings and waste generation reduction impact. As both single-use stickers and reusable clips are equally accurate and reliable, this cost and waste savings could be instituted without a compromise in clinical care.

Grey-box modeling of Air Handling Units for Analysis and Virtual Sensing

The optimization of control sequences in air handling units (AHUs) presents a significant opportunity for energy savings within HVAC systems. However, many building owners and operators require quantifiable estimates of potential energy savings before committing to retrofitting control systems. Valid estimates of energy savings require system models that consider capacity and limitations of the AHU, but in existing systems, scarce information hinders such modeling efforts. This lack of information complicates AHU modeling and the assessment of alternative control strategies. This paper demonstrates an approach that leverages time-series data from a newly constructed Danish AHU, equipped with multiple sensors for temperature, flow, and pressure, to construct a grey-box model of the unit, including component properties. The estimated parameters for the components are validated against data sheet information, and shows that the estimation procedure is accurate for parameter estimation. To analyze the energy-efficiency of the cooling coil, the model is used to estimate the latent cooling in the cooling coil, as Danish conditions rarely require dehumidification of supply air.

Measuring Space Efficiency and Estimating the Potential for Reduced Operational and Embodied Energy Use for Office Spaces

This paper explores how opportunities for reducing the total use of office space can be identified, investigates how the benefits in terms of energy savings from space efficiency measures could be calculated, and gives a first estimate of such values. A simple method to measure office space use is presented and tested at two university departments, and very low space efficiency is found. A variety of reasons for the low space efficiency are identified via interviews with property managers and heads of the concerned departments. These include the fact that the incentives for using space efficiently are small for the decision-makers, and the costs in terms of time and trouble are perceived as high. This suggests that interesting results can be achieved without large efforts. Moreover, we present a proof of concept of how to estimate the amount of energy that can be saved by reducing space use. We find a rough estimate of the potential energy savings of 2 MWh/m2 in embodied primary energy intensity (assuming that more efficient use of space leads to a decrease in new construction) and 200 kWh/m2/year in final energy intensity. Those numbers should be useful as rough estimates when looking at opportunities for saving energy by using space more efficiently.

Optimal energy management of grid-connected PV for HVAC cooling with ice thermal storage system

Studies have shown that reducing cooling energy costs and increasing operational efficiency may be achieved by utilizing ice thermal energy storage (ITES) technology while maintaining the thermal requirements in space cooling facilities. Optimal control of the ITES system and integration of renewable energy (RE) sources such as PV and geothermal, depending on the availability of resources and application, can further improve the operation of HVAC's cooling systems and mitigate the increased energy cost required for ice formation and overall cooling energy.This study presented optimal switching control of the ice-build chiller for ITES charging and PV power source. Inputs to the model, simulations, and validations were implemented using the available data, which include the historical exogenous meteorological data, temperatures at the inlet and exit of the plant components, manufacturer's information, and readings from the plant's SCADA chosen for the case study.The main aim of the study was to develop an optimal control model that minimizes the energy consumption and cost in the Ice built chiller and other devices, such as pump fans in the HVAC system, by optimal charge and discharge of the ITES and supplementary utilization of the greener energy source PV source under the time of use (ToU) tariff and desired cooling load demand. The case study for a healthcare building was considered in implementing the model.Simulations were implemented in the MATLAB optimization toolbox with the Solving Constrained Integer Programs (SCIP) solver, which was chosen to address mixed integer programming (MIP) problems. It incorporates algorithms like a branch and cut conflict analysis and pre-solving techniques to handle intricate optimization problems involving continuous and discrete decision variables.The optimal switching control model yields approximately 33 % of energy cost savings during the summer months that involve using the HVAC with ITES compared to the current system control (baseline). Additionally, the ITES temperature remained below 0 °C to maintain thermal requirements as an operation constraint. The inclusion of PV and battery options as a source of power to the pumps accounted for 10–15 % of the overall energy usage of the system. Optimal control of the system to utilize the stored energy during peak pricing and high demand periods eliminated the extreme dependence on grid energy in some instances. Despite the additional capital required for the controller, solar PV, and batteries installation, the study projects a return on investment within two years, with a 20-year lifetime energy cost savings estimate of 35 % if inflation and annual electricity price increases are estimated at 5 % and 10 %, respectively.

Baseline energy modeling for improved measurement and verification through the use of ensemble artificial intelligence models

Accurate estimation of energy savings is crucial for the effective implementation of energy conservation measures (ECMs). Simultaneously, the integration of Artificial Intelligence (AI) has revolutionized software engineering by imbuing software with intelligent capabilities and autonomy. In this paper, we propose an ensemble model for precisely estimating baseline energy consumption within the realm of AI-empowered autonomous software. The ensemble model combines predictions from three tree-based Machine Learning models, namely Random Forest, XGBoost, and LightGBM. Notably, our model emphasizes the provision of explainability, granting transparency and insights into the key factors influencing baseline energy consumption. To validate its effectiveness, we conduct experimental evaluations on a diverse cluster of real-world buildings in Latvia. The results demonstrate the superiority of our proposed ensemble model over individual models and even a deep learning network tailored for energy consumption estimation. These findings underscore the efficacy of AI-empowered models in the energy sector, offering a robust and interpretable solution for estimating energy savings.