Communicating about Contaminated Site Cleanup using Coordinated and Consistent Metrics: Opportunity and Challenge for the U.S. Department of Energy
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Mathematical Methods In Social Sciences↗
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Results for “Case Study”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles
The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.
42 ENGINEERING↗
Multi-objective optimization of peel and shear strengths in ultrasonic metal welding using machine learning-based response surface methodology
Ultrasonic metal welding (UMW) is a solid-state joining technique with varied industrial applications. Despite of its numerous advantages, UMW has a relative narrow operating window and is sensitive to variations in process conditions. As such, it is imperative to quantitatively characterize the influence of welding parameters on the resulting joint quality. The quantification model can be subsequently used to optimize the parameters. Conventional response surface methodology (RSM) usually employs linear or polynomial models, which may not be able to capture the intricate, nonlinear input-output relationships in UMW. Furthermore, some UMW applications call for simultaneous optimization of multiple quality indices such as peel strength, shear strength, electrical conductivity, and thermal conductivity. To address these challenges, this paper develops a machine learning (ML)-based RSM to model the input-output relationships in UMW and jointly optimize two quality indices, namely, peel and shear strengths. The performance of various ML methods including spline regression, Gaussian process regression (GPR), support vector regression (SVR), and conventional polynomial regression models with different orders is compared. A case study using experimental data shows that GPR with radial basis function (RBF) kernel and SVR with RBF kernel achieve the best prediction accuracy. The obtained response surface models are then used to optimize a compound joint strength indicator that is defined as the average of normalized shear and peel strengths. In addition, the case study reveals different patterns in the response surfaces of shear and peel strengths, which has not been systematically studied in the literature. While developed for the UMW application, the method can be extended to other manufacturing processes.
42 ENGINEERING↗
Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA
In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA
In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission
This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.
Li, Zhenning↗
Data for Filling the Cellulosic Bio-economy Gap by Utilizing a Wedge Approach Combined with Stakeholder Collaboration
The price gap between the market and breakeven prices of cellulosic biomass for farmers represents a significant barrier to the development of a low-carbon cellulosic bioeconomy. Using a bottom-up, agent-based modeling tool that replicates the behaviors and interactions of key stakeholders, this study analyzes the emergence of a cellulosic bioeconomy at the local scale through a wedge approach that examines an integrated portfolio of multiple policy options, including subsidies for small-scale bioproducts and environmental credits. The role of collaboration among multiple stakeholders, such as biomass producers (farmers), bio-refinery industry, government, and society, is assessed for filling the price gap. Using the Sangamon River Basin as a case study site, we evaluate the effectiveness of the wedge approach by comparing simulation results from multiple scenarios, each incorporating different combinations of bioeconomy wedges, with and without stakeholder collaboration. Results underscore that active collaboration among stakeholders acts as a catalyst enlarging the effectiveness of bioeconomy wedges. Including the carbon credits and environmental value in the policy portfolio is found to bridge the price gap through collective contributions from diverse stakeholders, where the cellulosic biofuel and bioproduct industry plays a pivotal role. Although this study is conducted at the local watershed scale, the methodology and findings offer valuable insights for market development in other watersheds and the potential scaling of local markets to regional and national levels.
Economics↗
Underground sources of drinking water chemistry changes in response to potential CO 2 leakage
The purpose of this study was to quantify changes to underground sources of drinking water (USDW) quality in response to potential CO 2 leakage from geologic CO 2 sequestration (GCS) reservoirs. Here, the developed a framework of combined laboratory experiments and reactive transport simulations and used this framework to evaluate the Ogallala aquifer overlying the Farnsworth Unit (FWU), an active GCS site, as a case study. Using chemical reaction parameters obtained from laboratory experiments and numerical simulations, site-specific mechanisms of CO 2 -water-sediment interactions at the USDW aquifer were interpreted. Long-term risks of potential CO 2 leakage were then evaluated with field-scale numerical models using the regional hydrogeological characteristics and reaction parameters obtained from our experiments and simulations. Results suggest that carbonate mineral impurity and cation exchange are key mechanisms for interactions between CO 2 and the aquifer sediment. Additionally, for a large leakage rate of 0.1 % injection from one leaky well, the leakage plume might impact an area of 300 m in diameter and significantly affect the local water quality by changing pH and cation concentrations (e.g., Zn, Ba and Sr). After leakage ceases, the zone of impacted fluids would not migrate significantly in subsequent decades due to a low regional groundwater flowrate (for this case study). The relatively small area of impact might not be detected in a monitoring well given the broader spacing in a typical field scenario. Effective early leakage detection may require additional tools, e.g., borehole CO 2 movement, four-dimensional seismicity, CO 2 soil flux, samples from deeper aquifers, etc., to ensure effective leakage detection and long-term safety of GCS projects.
58 GEOSCIENCES↗
An Open-Source Virtual Testbed for a Real Net-Zero Energy Community
Net zero energy communities (NZECs) are critical to ensure sustainability and resilience of modernized power systems. System modeling helps overcome technical challenges in designing and operating NZECs. In this paper, we present the modeling work based on a real NZEC. Two sets of models are developed: higher-fidelity physics-based models considering the interaction between subsystems of the studied NZEC and capturing fast-dynamics; and lower-fidelity data-driven models requiring less resource to establish and/or run. All models are validated against measurements from this real NZEC. In addition, we create a simulation framework which streamlines the processes for simulation and thus allows using developed models to form a virtual testbed. To demonstrate the usage of the virtual testbed, a case study is conducted where a building-to-grid integration control is evaluated via simulation. The evaluation results suggest that the tested control significantly smooths the power draw of the studied community and doesn’t sacrifice the thermal comfort to a great extent.
Huang, Sen↗
Nonlinear dynamic analysis of solution multiplicity of buoyancy ventilation in a typical underground structure
Buoyancy ventilation is widely used in underground buildings, such as underground hydropower stations. Multiple solutions of buoyancy ventilation may exist in those underground structures. In this study, we developed a transient model comprising an ordinary differential equation system to describe buoyancy ventilation patterns in typical two-zone underground structures. Additionally, the accuracy of the model was validated. Nonlinear dynamical analysis was conducted to study multiple steady-state airflow. According to mathematical derivation, the configuration of one local heat source at the bottom corner introduces two stable solutions. The criterion to determine the stability and existence of solutions for more general scenarios was developed. Using this criterion, we obtained the multiple steady states of any two-zone underground buildings for different stack height ratios and the strength ratios of the heat sources. Furthermore, this criterion can be adopted for the design of buoyancy ventilation or natural smoke ventilation systems. Designers can change the height ratio of the stack or the heat ratio of two zones to induce the desired ventilation patterns. Finally, a case study was conducted with field measurements to demonstrate the use of the nonlinear dynamical analysis method to investigate the multiple steady states of buoyancy ventilation. Through the case study, we validated that the proposed criterion could produce the same result as the nonlinear dynamical analysis.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control
The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.
catalysts↗
NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study
Abstract Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.
60 APPLIED LIFE SCIENCES↗
Dynamically robust coordinated set point tracking of distributed DERs at point of common coupling
Low-inertia operation of small-scale power systems, such as a microgrid or a portion of a long feeder, requires careful coordination of the controller performance of the constituting devices. This challenge is exacerbated in microgrids serving the functionalities of a conventional synchronous-based generation unit while comprised of smaller DERs operating mainly interfaced through power electronics converters. This paper builds on the idea of set point modulation and proposes a two-level control strategy that aims to achieve superior performance at the point of common coupling (PCC) of microgrids by combining a local control level with a distributed and coordinated level. Several case studies on both AC and DC systems, the CIGRE low-voltage benchmark system as the AC system and a test DC microgrid, validate the performance of the proposed approach. The real-world applicability of the approach is established via a high-fidelity power hardware-in-the-loop (PHIL) experimental setup and an application case study on grid frequency regulation. The proposed approach enables a microgrid to participate in ancillary service provisions where speed and quality of regulation are critical.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Insights on Wind Turbine Maintenance From the Usage History of a General Electric Transportation Systems Gearbox
Recently, micropitting that occurred in a wind turbine gearbox has been used as a case study of the International Organization for Standardization technical specification ISO/TS 6336-22. This technical specification contains a proposed calculation of risk of micropitting in gear sets, in terms of a safety factor based on the ratio of the minimum to the permissible specific lubricant film thickness. This report summarizes the operational history of the micropitted gearbox for future case studies.
17 WIND ENERGY↗
Improving the performance of first- and last-mile mobility services through transit coordination, real-time demand prediction, advanced reservations, and trip prioritization
Socio-demographic trends and recent economic development patterns have resulted in travel behavior changes that call for more flexible and accessible public transit options. Because flexible transit services vary in scope, size, and service type, new data-informed methods are useful to optimize services based on the specific needs of local communities and riders. In this study, real-world demand and vehicle trajectory data were used to evaluate and optimize system performance for an existing first-mile–last-mile (FMLM) service in Robinson Township, PA. A general FMLM model for arbitrary demand and service supply was then developed to quantify system performance—both travel time costs and day-to-day reliability—for various operational polices considering spatio-temporal demand variation and transportation network dynamics. Heuristics were used for optimal real-time vehicle routing in sizable real-world networks accommodating various service types and scopes. In this case study, total user costs were reduced by 18.6% when rides were coordinated with mainline fixed-route transit. Predictive routing strategies were shown to marginally improve system performance under sparse and variable spatio-temporal demand. The case study also highlights potentially large travel time and user reliability improvements—reductions of 51% and 53.8%, respectively—when trip requests were made in advance of their desired pickup time. Finally, we show that travel time reliability can be improved for time-inflexible trips with trip prioritization without increasing total user costs. These results were stable to changes in demand density.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Modeling Power Plant Siting Opportunities and Constraints in the Eastern Interconnection
The electrical transmission grid is a critical part of the U.S. national infrastructure, and its modernization is a U.S. Department of Energy (DOE) priority. We describe the Energy Zones Mapping Tool (EZMT), a unique, powerful, and public web-based system with multi-criteria decision analysis (MCDA) models for more than 20 power plant technologies and many other capabilities. Through a case study on natural gas combined cycle (NGCC) power plants in the Eastern Interconnection (EI), we provide an example of incorporating an EZMT MCDA model into a larger planning context, with projections of interconnection-level capacity expansion, thermoelectric power plant retirements, and water availability. Our results provide insights on candidate NGCC site distributions and the criteria influencing them. The case study provides both an efficient methodology for performing similar analyses and hundreds of candidate NGCC power plant sites that can be studied in more detail as potential project sites.
20 FOSSIL-FUELED POWER PLANTS↗
Wavelet-based local mesh refinement for rainfall–runoff simulations
A wavelet-based local mesh refinement (wLMR) strategy is designed to generate multiresolution and unstructured triangular meshes from real digital elevation model (DEM) data for efficient hydrological simulations at the catchment scale. The wLMR strategy is studied considering slope- and curvature-based refinement criteria to analyze DEM inputs: the slope-based criterion uses bed elevation data as input to the wLMR strategy, whereas the curvature-based criterion feeds the bed slope data into it. The performance of the wLMR meshes generated by these two criteria is compared for hydrological simulations; first, using three analytical tests with the systematic variation in topography types and then by reproducing laboratory- and real-scale case studies. The bed elevation on the wLMR meshes and their simulation results are compared relative to those achieved on the finest uniform mesh. Repeated analytical tests show that the slope- and curvature-based criteria are equally effective with the wLMR strategy, and that it is easier to decide which criterion to take in relation to the (regular) shape of the topography. For the realistic case studies: (i) slope analysis provides a better metric to assess the correlation of a wLMR mesh to the fine uniform mesh and (ii) both criteria predict outlet hydrographs with a close predictive accuracy to that on the uniform mesh, but the curvature-based criterion is found to slightly better capture the channeling patterns of real DEM data.
54 ENVIRONMENTAL SCIENCES↗
Energy Savings Results from Small Commercial Building Retrofits in the US
Small commercial buildings, or those comprising less than 50,000 square feet of floor area, represent 94% of U.S commercial buildings by count and consume approximately 8% of the nation’s primary energy; as such, they represent a largely unexploited opportunity for energy savings. Small commercial buildings also represent a large economic market—the National Institute of Building Sciences (NIBS) estimated the small commercial retrofit market at USD 35.6 billion. Despite the prominence of small commercial buildings and the economic opportunity for energy retrofits, many energy efficiency programs focus on large commercial buildings, and create efficiency solutions that do not meet the needs of the small commercial market. This paper presents an analysis of 34 small commercial case study projects that implemented energy efficiency retrofits. This paper contributes to the existing building retrofit body of knowledge in the following ways: (1) it identifies the decision criteria used by small commercial building stakeholders that decided to complete an energy retrofit; (2) it identifies the most commonly implemented efficiency measures in small commercial buildings, and discusses why this is the case; and (3) it provides empirical evidence about the efficacy of installing single energy efficiency measures (EEMs) compared to packages of EEMs in small commercial buildings by reporting verified energy savings. To the authors’ knowledge, this paper is the first to catalog decision criteria and energy savings for the existing small commercial buildings market, and this research illustrates that small commercial building decision-makers seem most motivated to retrofit their spaces by energy cost savings and operational concerns. Furthermore, small commercial building decision-makers opted to implement single-system retrofits in fifteen (15) of the thirty-four cases studied. Finally, this research documents the improved savings, in the small commercial buildings market, associated with a more integrated package of EEMs compared to a single-system approach, achieving approximately 10% energy savings for a single-system approach and more than 20% energy savings for integrated approaches. These savings translate to CO2 savings of 1,324,000 kgCO2/year to 2,647,000 kgCO2/year, respectively, assuming small commercial buildings are retrofit at a rate of 0.95% of the stock annually.
24 POWER TRANSMISSION AND DISTRIBUTION↗