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At least 847 records · Page 47

Policy, Permit, Perform: Using City Benchmarking Data and Building Construction Permit History to Identify Energy Performance Improvements

The City of Portland (City) and Multnomah County 2015 Climate Action Plan targets a 40 percent reduction in carbon emissions below 1990 levels by 2030. To reach this goal, the plan includes a key objective to reduce the total energy use of existing buildings by 25 percent. Buildings are responsible for one-half of carbon emissions in Portland, Oregon, U.S., and improving their performance is critical to achieving the City’s climate goals. As part of its climate action planning, the City passed an ordinance on April 22, 2015, requiring commercial buildings 20,000 ft2 and larger to benchmark and disclose annual energy performance metrics through ENERGY STAR® Portfolio Manager® (ESPM), including greenhouse gas emissions, building energy use intensity (EUI) and ENERGY STAR scores. Twenty-five cities in the U.S. have adopted similar policies requiring energy benchmarking. These policies are generating a treasure trove of data about the drivers of building performance, but practitioners are only beginning to link benchmarking data to other datasets to produce actionable insight into improving building performance. In 2016, the City received a financial assistance award from the U.S. Department of Energy (DOE) through the Cities Leading through Energy Analysis and Planning project (Award Number DE-0007737). Portland’s project evaluated the application of the DOE Building Energy Asset Score Tool and rating system developed by Pacific Northwest National Laboratory (PNNL) to commercial buildings that report to the City. The City used building construction permit history to develop Asset Scores for a set of office buildings that reported energy performance for 2015 – the first year the City mandated energy benchmarking and reporting for commercial buildings 50,000 ft2 and larger. The primary project objective was to link energy benchmarking data and commercial building permit data to analyze commercial buildings systems that present the best, specific opportunities to improve energy performance. Integrating these datasets from two City departments, the Bureau of Development Services and the Bureau of Planning and Sustainability, could expand Portland’s use of analytics to inform climate policy decisions and strategic targeting of financial incentives for building owners and managers who are best positioned to improve the performance of their buildings. The project began with the commercial benchmarking data received for 340 commercial buildings that submitted calendar year 2015 energy reports. The City retained Research Into Action and Energy 350 (RIA team) to evaluate this self-reported benchmarking data. Based on a survey of 53 building managers, the RIA team found that most respondents used the City’s compliance tools, including a How-to Guide and Help Desk, and found access to utility data to be straightforward. However, almost one-third of the respondents encountered challenges when estimating the gross floor area (GFA), and some experienced confusion regarding the input of property use types and details into ESPM. Based on the RIA team’s recommendations, the City refined its How-to Guide, created online answers to frequently asked questions, and hosted office hour sessions to help building managers accurately characterize their building’s physical characteristics and operations in ESPM. Concurrently with the RIA team’s evaluation, the City worked with PNNL to estimate DOE Asset Score Preview (Preview) scores for 181 of the 340 commercial buildings that submitted ESPM reports to the City. Asset Score Tool is a web-based tool developed by PNNL for DOE to evaluate and rate the as-built energy efficiency of a building. Asset Score Tool’s full analysis capability runs a detailed energy model based on building geometry, age, envelope, lighting and mechanical systems using standard operating assumptions to give the building a score, similar to a miles per gallon rating for a car. Preview, a simplified deployment of the full Asset Score Tool, provides a preliminary score range using only seven data points, six of which are readily available in the ESPM benchmarking data. Analysis of the combined Preview scores and the operational ESPM scores identified buildings with a high potential for energy improvements through either retro-commissioning and retuning of existing operations or capital investments into building systems. The City contracted Whole Building Solutions (WBS) to mine building permit history and develop full Asset Scores for a subset of 26 office buildings that were eligible for both ENERGY STAR scores and Asset Scores. WBS researched permits and building plans to identify mechanical, lighting and envelope systems and other building characteristics necessary to complete Asset Scores. This historical data was recorded using the web-based Asset Score Tool, which evaluates the as designed energy efficiency of existing buildings. Much of this City information was available online after 2010; however, WBS had to search through microfiche files and the City’s database to obtain permit and plan history prior to 2010. Although building geometry, mechanical system type and basic envelope information was consistently identifiable, WBS found permit data gaps that prevented complete and accurate Asset Scores for most of the office buildings. If the City decides to develop Asset Scores based on building permit information in the future, WBS recommended requiring lighting plans, control diagrams and as-built drawings that reflect how the buildings are actually constructed. In addition, WBS recommended uploading plans and permits from microfiche storage into a more comprehensive, searchable database consistent with the City’s current online permit information. To identify the actual lighting types, WBS and City staff conducted site visits of all 26 office buildings. As part of managing the flow of ESPM and Asset Score data for the project, Earth Advantage, a sub-recipient of the Cities-LEAP award, created a DOE Standard Energy Efficiency Data (SEED) (USDOE 2018) instance for the City and used Asset Score’s Application Programming Interface (API) (Asset Score 2018) capabilities to develop two new features in the SEED Platform™: (1) automated Asset Score Preview ranges calculated based on benchmarking data and the City’s estimate of number of building floors; and (2) storage of full Asset Score information. Leveraging the construction permit history and site visit information for the 26 office buildings, The Cadmus Group (Cadmus) analyzed benchmarking data and Asset Score information to identify opportunities and drivers to improve performance. Correlation and regression analysis of the combined dataset was completed to determine whether building operations or specific systems – mechanical, lighting or envelope – present the best opportunities to improve energy performance. The central outcome of this project was Cadmus’ detailed analysis of the richer dataset that was created by combining the City of Portland’s commercial building permit activity and building-specific energy performance information based on metrics from ESPM and Asset Score Tool. Some of their findings collaborate with well-known facts, such as buildings with less efficient lighting systems are good targets for efficiency improvements through lighting upgrades. This analysis also helped identify that individual heating, ventilation, and air conditioning (HVAC) equipment efficiency does not necessarily correlate with building performance. However, overall HVAC system performance, as measured with the Total System Performance Ratio (TSPR) metric, is a better indicator of building performance (Goel et al. 2014). As a metric, TSPR considers whole system performance that includes equipment efficiency and system controls, such as resets for static pressure and chilled water setpoints, which can be more effective and financially feasible options for improving building performance. Given the high cost associated with envelope retrofits, opportunities to upgrade envelope insulation are likely to be limited. However, buildings with single-pane and non-thermal break windows are good candidates for window replacements, such as upgrading to double-pane windows with thermal breaks. This research project determined that developing Asset Scores based on site visits is preferable to mining City building permit data. In addition, the use of benchmarking data to develop Asset Score Preview Scores is recommended as a first step in engaging building managers to develop full Asset Scores. Asset Score Tool outputs can help building managers quickly identify opportunities for improvement and then work with the utility incentive administrator and energy service providers to develop their retrofit plan. Where full Asset Scores are available, analysis using a quadrant matrix with ENERGY STAR scores is recommended to identify buildings that present the best opportunities for operational-behavioral improvements versus ones with opportunities for upgrades to physical building systems. This workflow and the tools will help cities, utility incentive administrators, building portfolio managers and energy service providers develop energy programs and strategies for screening and analysis of buildings with the greatest energy savings potential. This report describes the project approach and research results to inform future coordination of ESPM and Asset Score data, including the use of benchmarking data to generate Preview scores. Given better awareness of energy performance, building managers can make more informed decisions to reduce energy consumption and carbon emissions. With cities, states and jurisdictions adopting benchmarking and auditing ordinances, there are substantial amounts of data submitted to cities that could be used to inform investments in energy efficiency.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Building Blocks for High-Efficiency Organic Photovoltaics: Interplay of Molecular, Crystal, and Electronic Properties in Post-Fullerene ITIC Ensembles

Accurate single-crystal X-ray diffraction data offer a unique opportunity to compare and contrast the atomistic details of bulk heterojunction photovoltaic small-molecule acceptor structure and packing, as well as provide an essential starting point for computational electronic structure and charge transport analysis. Herein, we report diffraction-derived crystal structures and computational analyses on the n-type semiconductors which enable some of the highest efficiency organic solar cells produced to date, 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (ITIC) and seven derivatives (including three new crystal structures: 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(4-propylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (ITIC-C3), 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(3-hexylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (m-ITIC-C6), and 3,9-bis(2-methylene-((3-(1,1-dicyanomethylene)-6,7-difluoro)-indanone))-5,5,11,11-tetrakis(4-butylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (ITIC-C4-4F). IDTT acceptors typically pack in a face-to-face fashion with π–π distances ranging from 3.28–3.95 Å. Additionally, edge-to-face packing is observed with S...π interactions as short as 3.21–3.24 Å. Moreover, ITIC end group identities and side chain substituents influence the nature and strength of noncovalent interactions (e.g. H-bonding, π–π) and thus correlate with the observed packing motif, electronic structure, and charge transport properties of the crystals. Furthermore, density functional theory (DFT) calculations reveal relatively large nearest-neighbor intermolecular π-π electronic couplings (5.85–56.8 meV) and correlate the nature of the band structure with the dispersion interactions in the single crystals and core–end group polarization effects. Overall, this combined experimental and theoretical work reveals key insights into crystal engineering strategies for indacenodithienothiophene (IDTT) acceptors, as well as general design rules for high-efficiency post-fullerene small molecule acceptors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering High Performance Service-Oriented Pipeline Applications with MeDICi

The pipeline software architecture pattern is commonly used in many application domains to structure a software system. A pipeline comprises a sequence of processing steps that progressively transform data to some desired outputs. As pipeline-based systems are required to handle increasingly large volumes of data and provide high throughput services, simple scripting-based technologies that have traditionally been used for constructing pipelines do not scale. In this paper we describe the MeDICI Integration Framework (MIF), which is specifically designed for building flexible, efficient and scalable pipelines that exploit distributed services as elements of the pipeline. We explain the core runtime and development infrastructures that MIF provides, and demonstrate how MIF has been used in two complex applications to improve performance and modifiability.

99 GENERAL AND MISCELLANEOUS↗

Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology

Accurate occupancy prediction can improve facility control and energy efficiency of buildings. In recent years, buildings’ exiting WiFi infrastructures have been widely studied in the research of occupancy and energy conservation. However, using WiFi to assess occupancy is challenging due to that occupancy information is often characterized stochastically and varies with time and easily disturbed by building components. To overcome such limitations, this study utilizes WiFi probe technology to actively scan WiFi connection requests and responses between access points and network devices of building occupants. With captured signals, this study proposed a Markov based feedback recurrent neural network (M-FRNN) algorithm to model and predict the occupancy profiles. One on-site experiment was conducted to collect ground truth data using camera-based video analysis and the results were used to validate the M-FRNN occupancy prediction model over a 9-day measurement period. From the results, the M-FRNN based occupancy model using WiFi probes shows best accuracies can reach 80.9%, 89.6%, and 93.9% with a tolerance of 2, 3, and 4 occupants respectively. In conclusion, this study demonstrated that WiFi data coupled with stochastic machine learning system can provide a viable alternative to determine a building's occupancy profile.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Automated path planning for functionally graded materials considering phase stability and solidification behavior: Application to the Mo-Nb-Ta-Ti system

Functionally graded materials have the potential to improve upon monolithic parts by locally tailoring compositions to surrounding environmental conditions. Difficulties arise when designing composition gradients as incompatible materials can result in detrimental phase formation and failure of the gradient joint. As many alloys are multi-component, designing a composition gradient free of detrimental phases is difficult due to the large composition space available to explore. A framework was developed that improves the path planning algorithm and surrogate models with adaptive sampling schemes specific to their problem definition. A cost function was created to minimize a property (such as cracking susceptibility) along a path. This framework was applied to the Mo-Nb-Ta-Ti system as a case study to showcase the efficiency in building the surrogate models and in iterating different optimal compositionally graded paths.

36 MATERIALS SCIENCE↗

Origin of high optical contrast in zinc-zinc oxide electrodeposits for dynamic windows

The control of solar light and heat emission through windows is an important strategy for increasing the energy efficiency of buildings. Reversible Zn electrodeposition has recently emerged as a promising method for constructing electronically tintable robust dynamic windows. In Zn electrodeposits formed from dimethyl sulfoxide (DMSO) electrolytes during device tinting, we observe extraordinary absorption that is in excess of what is predicted by the Beer-Lambert law for a uniform Zn thin film. Here, the charge required to electroplate these films is abnormally low, significantly less than previously reported dynamic windows based on reversible metal electrodeposition, which facilitates the construction of large-area devices that switch uniformly. Finite-difference time-domain (FDTD) simulations are used to investigate the origin of this enhanced absorption, which arises from plasmonic effects among the Zn nanoparticles and ZnO dendrites in the film. The dielectric ZnO dendrites promote absorption via slit-like Zn-dielectric-Zn structures that from hybrid surface plasmon resonance at metal walls. Through these investigations, we provide design principles to construct low-charge and high-contrast metal and metal oxide-based dynamic windows.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A comparative study of the status of GSHP applications in the United States and China

Ground source heat pump (GSHP) or geothermal heat pump technology was first developed and commercially introduced in the late 1970s, and GSHP units representing approximately 3.9 million tons of cooling had been installed in the United States by 2012. Applications of GSHP technology also have grown rapidly in China since it was introduced into China in the 1990s through collaboration between the Chinese and US governments. It is estimated that by 2013, about 400 million m2 (4.3 billion ft2) of building floor space in China was heated and/or cooled by GSHP systems. Moreover, governments in both China and the United States have programs that in some way support and/or promote the use of GSHP technology. After decades of practice, both countries have accumulated abundant experience in applying GSHP technology, but both also are confronted with various challenges to rapidly deploying this technology. Under the sponsorship of the US–China Clean Energy Research Center for Building Energy Efficiency, researchers reviewed and compared the current status of GSHP applications in the United States and China, including related policies, standards, technologies, equipment, costs, market development, and barriers. Finally, based on this comparative study, future collaborations between the two countries are recommended to improve the application of the GSHP technology and fully realize its energy saving potential.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Durability enhancement of all-solid-state electrochromic devices by adjusting the charge density ratio between electrochromic and counter electrode layers

Here, owing to an increase in global warming, smart-window devices based on charge-balanced electrochromic devices (ECDs), which exhibit high potential to increase the thermal efficiency of buildings, have gained prominence. However, studies on the fabrication and cycling stability of charge-balanced ECDs are scarce. In this study, WO 3 and NiO x films were deposited on indium-tin-oxide (ITO)-coated glass substrates by reactive direct-current magnetron sputtering, and the deposition time was varied to control the thickness and charge density of the thin films. Subsequently, the NiO x /ITO/glass and WO 3 /ITO/glass substrates were laminated with a Li-based polymeric electrolyte to fabricate all-solid-state ECDs comprising electrochromic (EC) and counter-electrode (CE) layers in charge-density ratios of 12.6, 6.4, 2.3, and 1.1. Changes in the electrochromic properties, device-layer microstructure, crystal structure, and elemental composition of the as-constructed ECDs before and after degradation were investigated to understand the influence of the charge-density ratio of the EC and CE layers on the long-term durability of ECDs. Increasing the charge-density ratio decreased the cycling stability of the device owing to changes in the microstructure and crystal structure of the NiO x layer in the microstructural deep-trap sites. Among all the ECDs, those comprising EC and CE layers with similar charge densities showed the most stable optical modulation and highest long-term durability. Finally, based on the aforementioned results, a degradation mechanism for charge-imbalanced all-solid-state ECDs was proposed. This study is expected to open new frontiers in designing optimal-performance electrochemical devices with a wide variety of potential applications.

14 SOLAR ENERGY↗

Dual-Band Electrochromism in Hydrous Tungsten Oxide

The independent modulation of visible and near-infrared light by a single material, termed dualband electrochromism, is highly desirable for smart windows to enhance the energy efficiency of buildings. Tungsten oxides are commercially important electrochromic materials, exhibiting reversible visible and near-infrared absorption when electrochemically reduced in an electrolyte containing small cations or protons. The presence of structural water in tungsten oxides has been associated with faster electrochromic switching speeds. Here, we find that WO 3 ·H 2 O, a crystalline hydrate, exhibits dual-band electrochromism unlike the anhydrous WO 3 providing a heretofore unexplored route to tune the electrochromic response of tungsten oxides. Absorption of near-infrared light is achieved at low Li + /e - injection, followed by the absorption of visible light at higher Li + /e - injection as a result of an electrochemically-induced phase transition. We propose that this dual-band modulation is possible due to the more open structure of WO 3 ·H 2 O as compared to WO 3 . This facilitates a more extended solid solution Li + insertion regime that benefits the modulation of near-infrared radiation via plasmon absorption. Higher degrees of Li + /e - insertion lead to polaronic absorption associated with localized charge storage. Furthermore, these results inform how structural factors influence the electrochemically induced spectral response of transition metal oxides and the important role of structural water beyond optical switching speed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hybrid dynamic windows using reversible metal electrodeposition and ion insertion

Dynamic windows with electronically controlled transmission reduce glare without obstructing views while increasing the energy efficiency of buildings and automobiles via lighting, heating and cooling savings. Electrochromic materials, which change colour with voltage, are widely explored for use in dynamic windows, but they have not been extensively commercialized due to problems associated with colour, cost, switching speed and durability. Here, we develop a class of dynamic windows that combines reversible metal electrodeposition with ion insertion chemistry. These devices function through the reversible electroplating of Bi and Cu at the working electrode and Li+ insertion in a nickel oxide counter electrode. In one minute, 100 cm 2 windows uniformly switch between a clear state with 75% transmission and a colour-neutral black state possessing 10% transmission, which represents a significant improvement over previous metal-based architectures. We demonstrate that these hybrid windows cycle at least 4,000 times without degradation and are compatible with flexible substrates. Finally, we discuss how this approach can be used to design practical large-scale windows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of CdTe/CdS solar cell at low power density for low-illumination applications

In this paper, we numerically investigate CdTe/CdS PV cell properties using a simulation program Solar Cell Capacitance Simulator in 1D (SCAPS-1D). A simple structure of CdTe PV cell has been optimized to study the effect of temperature, absorber thickness and work function at very low incident power. Objective of this research paper is to build an efficient and cost effective solar cell for portable electronic devices such as portable computers and cell phones that work at low incident power because most of such devices work at diffused and reflected sunlight. In this report, we simulated a simple CdTe PV cell at very low incident power, which gives good efficiency.

14 SOLAR ENERGY↗

CONSTRAINTS ON FEEDBACK PROCESSES DURING THE FORMATION OF EARLY-TYPE GALAXIES

Galaxies are found to obey scaling relations between a number of observables. These relations follow different trends at the low- and high-mass ends. The processes driving the curvature of scaling relations remain uncertain. In this Letter, we focus on the specific family of early-type galaxies, deriving the star formation histories of a complete sample of visually classified galaxies from Sloan Digital Sky Survey DR7 over the redshift range 0.01 < z < 0.025, covering a stellar mass interval from 10{sup 9} to 3 Multiplication-Sign 10{sup 11} M{sub Sun }. Our sample features the characteristic 'knee' in the surface brightness versus mass distribution at M{sub *} {approx} 3 Multiplication-Sign 10{sup 10} M{sub Sun} . We find a clear difference between the age and metallicity distributions of the stellar populations above and beyond this knee, which suggests a sudden transition from a constant, highly efficient mode of star formation in high-mass galaxies, gradually decreasing toward the low-mass end of the sample. At fixed mass, our early-type sample is more efficient in building up the stellar content at early times in comparison to the general population of galaxies, with half of the stars already in place by redshift z {approx} 2 for all masses. The metallicity-age trend in low-mass galaxies is not compatible with infall of metal-poor gas, suggesting instead an outflow-driven relation.

79 ASTRONOMY AND ASTROPHYSICS↗

Universal reduced basis for the calibration of covariant energy density functionals

The reduced basis method is used to construct a “universal” basis of Dirac orbitals that may be applicable throughout the nuclear chart to calibrate covariant energy density functionals. Relative to the successful development of a reduced basis emulator for the nonrelativistic Schrödinger equation, the Dirac equation adds an extra layer of complexity due to the existence of negative energy states, which complicates building an efficient reduced basis. However, once this problem is mitigated, the resulting reduced basis is able to accurately and efficiently reproduce the high-fidelity model at a fraction of the computational cost. We are confident that the resulting reduced basis will serve as a foundational element in developing rapid and accurate emulators. In turn, these emulators will play a critical role in the Bayesian optimization of covariant energy density functionals.

Bayesian methods↗

Towards excitations and dynamical quantities in correlated lattices with density matrix embedding theory

Density matrix embedding theory (DMET) provides a framework to describe ground-state expectation values in strongly correlated systems, but its extension to dynamical quantities is still an open problem. We show one route to obtaining excitations and dynamical spectral functions by using the techniques of DMET to approximate the matrix elements that arise in a single-mode inspired excitation ansatz. We demonstrate this approach in the one-dimensional Hubbard model, comparing the neutral excitations, single-particle density of states, charge, and spin dynamical structure factors to benchmarks from the Bethe ansatz and density matrix renormalization group. Finally, our work highlights the potential of these ideas in building computationally efficient approaches for dynamical quantities.

1-dimensional systems↗

CatMass : software for calculating optimal sample masses for X-ray absorption spectroscopy experiments involving complex sample compositions

This paper presents software for calculating the optimal mass of samples with complex compositions ( e.g. supported metal catalysts) for X-ray absorption spectroscopy (XAS) and scattering measurements. The ability to calculate the sample mass and other relevant parameters needed for an XAS measurement allows experimentalists to be better prepared in terms of detector selection, energy range of scan and overall time needed to complete the measurement, thus increasing efficiency. CatMass builds on existing sample mass calculators allowing users to determine the optimum sample preparation, collection geometry, usable energy range for a scan and approximate edge step of the absorption event. Visualization tools present the absorption calculation results in a format familiar to XAS experimentalists, with the added ability to save calculations and plots for future reference or recalculation. CatMass is a program broadly applicable in catalysis and is helpful for users with complex samples due to composition/stoichiometry or multiple competing elements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling

Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to be extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.

Surrogate model, reduced order model, sensitivity ↗

Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid

We consider the field of machine learning and where it is both useful, and not useful, for the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors - such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals - such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop. This paper describes benefits and limits of present machine-learning applications for use on the grid and presents a series of case studies that illustrate the potential benefits of developing advanced local multi-variate analytics machine-learning-based applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗