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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Brick Schema Standardized Plug Load Control Strategies for Load Reduction: Preprint

Plug loads comprise a significant percentage of commercial building energy consumption. Applying intelligent controls to turn off plug loads when unused can provide dynamic load reduction and flexibility, which are key traits of grid-interactive efficient buildings. This capability is important for equitable decarbonization as it can enable disadvantaged communities to electrify buildings without costly upgrades to electrical infrastructure. In this work, we present the effectiveness of various control strategies along with the operational lessons that informed their design. During a three-year period, we operated over 600 smart outlets in 12 university office buildings. The attached plug loads consisted primarily of printers, TVs, water dispensers, and copiers. After recording baseline power measurements for one year, we designed plug load control (PLC) strategies for each plug load type, use, and for different risk tolerance levels because PLC can potentially be disruptive to daily work. We used the Brick Schema to facilitate the management of plug load locations and other metadata. For advanced controls, we integrated the smart plugs with heating, ventilation, and air conditioning (HVAC) systems through the campus building automation system. We found static schedules to be the least disruptive and most predictable for occupants, resulting in 38% and 66% energy savings in two studies. For printers, print server-triggered PLC produced 86% savings, the highest of all strategies with minimal occupant impact. Scheduling of water dispensers and digital signage TVs produced 49% and 70% savings respectively with opportunities to improve performance with the use of HVAC occupancy data.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2013

High-Performance Computing for Real-Time Grid Analysis and Operation

Power grids worldwide are undergoing an unprecedented transition as a result of grid evolution meeting information revolution. The grid evolution is largely driven by the desire for green energy. Emerging grid technologies such as renewable generation, smart loads, plug-in hybrid vehicles, and distributed generation provide opportunities to generate energy from green sources and to manage energy use for better system efficiency. With utility companies actively deploying these technologies, a high level of penetration of these new technologies is expected in the next 5-10 years, bringing in a level of intermittency, uncertainties, and complexity that the grid did not see nor design for. On the other hand, the information infrastructure in the power grid is being revolutionized with large-scale deployment of sensors and meters in both the transmission and distribution networks. The future grid will have two-way flows of both electrons and information. The challenge is how to take advantage of the information revolution: pull the large amount of data in, process it in real time, and put information out to manage grid evolution. Without addressing this challenge, the opportunities in grid evolution will remain unfulfilled. This transition poses grand challenges in grid modeling, simulation, and information presentation. The computational complexity of underlying power grid modeling and simulation will significantly increase in the next decade due to an increased model size and a decreased time window allowed to compute model solutions. High-performance computing is essential to enable this transition. The essential technical barrier is to vastly increase the computational speed so operation response time can be reduced from minutes to seconds and sub-seconds. The speed at which key functions such as state estimation and contingency analysis are conducted (typically every 3-5 minutes) needs to be dramatically increased so that the analysis of contingencies is both comprehensive and real time. An even bigger challenge is how to incorporate dynamic information into real-time grid operation. Today’s online grid operation is based on a static grid model and can only provide a static snapshot of current system operation status, while dynamic analysis is conducted offline because of low computational efficiency. The offline analysis uses a worst-case scenario to determine transmission limits, resulting in under-utilization of grid assets. This conservative approach does not necessarily lead to reliability. Many times, actual power grid scenarios are not studied, and they will push the grid over the edge and resulting in outages and blackouts. This chapter addresses the HPC needs in power grid analysis and operations. Example applications such as state estimation and contingency analysis are given to demonstrate the value of HPC in power grid applications. Future research directions are suggested for high performance computing applications in power grids to improve the transparency, efficiency, and reliability of power grids.

Contingency Analysis↗
DOE OSTI2019

Coordinated PEV Charging for Distribution System Management

Plug-in electric vehicles (PEVs) can help to reduce worldwide dependence on petroleum and carbon emissions. In the past a few years, PEVs have received considerable attention as an eco-friendly and cost-effective alternative to conventional gasoline vehicles. PEVs consume higher power from the grid during charging compared to conventional residential loads. Therefore, the emerging fleet of PEVs will introduce a considerable amount of additional load on power system. On the other hand, majority of PEVs are parked for more than 90% of the time, making them ideal for providing various services through Electric Vehicle Supply Equipment (EVSE), a.k.a. charging stations which are PEVs’ connection points to the power system. In this project, coordinated PEV charging are developed to provide distribution system services, considering PEV characteristics, realistic travel pattern, charging behaviors, and EVSE power rating and availability. The main efforts and contributions are summarized as follows. • Mobility models and EVSE charging capability/availability are indispensable for evaluating PEV charging coordination strategies and developing PEV charging control. Many existing studies utilize simplified mobility models assuming that the entire vehicle fleet returns home in the evening and is parked at home until the next morning. Some other PEV models better represent diversified home arrival and departure time, but cannot capture varying charging flexibility and capability at different locations, and therefore are not appropriate to study the impacts of public EVSE on PEV load and utilization. In this work, a mobility and charging flexibility model is proposed to better represent the temporal availability and varying charging capability from PEV onboard charger and EVSE. • Based on the mobility model, a generalized optimization method is proposed to evaluate different PEV charging coordination strategies. In existing literature, different algorithms and methods need to be designed to evaluate each charging strategy from both vehicle owners’ and system’s perspective. With the optimization method proposed in this work, different charging control strategies can be studied and compared by only updating objective functions. Moreover, optimization tricks are provided to convert the optimization problems to equivalent linear programming problems, which can be efficiently solved with existing solvers. • An innovative scheduling and control framework is proposed to enable smart PEV charging for grid services while meeting PEV owners’ travel needs. In the proposed framework, each set of EVSE is equipped with a controller that estimates charging power and energy flexibility based on vehicle characteristics, EVSE power rating, battery energy state, and upcoming trip information. With the simplified charging flexibility model received from each EVSE controller, the central coordinator determines the optimal power allocation for a look-ahead time window for the given grid services. The proposed charging control can help reduce the computational complexity and communication requirement compared with existing methods. It is also scalable to the expanding PEV fleet and robust to uncertainties in upcoming vehicle trips and future system condition. • The proposed charging strategy evaluation and smart charging control methods are applied to one of the prototypical feeders developed by the Pacific Northwest National Laboratory (PNNL) for case studies. Detailed trip information extracted from the National Household Travel Survey (NHTS) is used to represent travel and parking patterns. Different scenarios are simulated to evaluate the performance of the proposed methods and understand how PEV mobility and public EVSE availability affect PEV load and potential grid services.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Healthcare Energy End-Use Monitoring

NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers, and engineers in the healthcare sector will be able to use these results to more effectively prioritize and refine the scope of investments in new metering and energy audits.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Energy savings and usability of zero-client computing in office settings

This study provides a detailed comparison of the power consumption, usability, and applicability of virtual machines (VMs) - accessed through zero-client devices - and traditional laptop computers in office settings. The study analyzed high-level plug loads across two office spaces, one using traditional laptops, the other using zero clients. In addition, the individual power consumption of four workstations was monitored and compared. Each workstation user switched between using a laptop or zero client for one week and then using the alternate system the second week. Results of the high-level and workstation analysis show that average workstation plug loads are lower for occupants using zero clients. However, this does not include power consumed by the data center managing VMs. This study calculates the affiliated data center power draw of VMs and shows that server-related loads push total zero-client computing energy higher than that of traditional laptops. Finally, a questionnaire was administered to building occupants to determine the appropriateness of zero-client computing for various user groups, with the results indicating that VMs are most appropriate for more basic software functions. The findings of this study suggest that advances in server technology can help improve both the overall efficiency and the usability of zero-client computing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Irvine Smart Grid Demonstration, a Regional Smart Grid Demonstration Project

ISGD was a comprehensive demonstration that spanned the electricity delivery system and extended into customer homes. The project used phasor measurement technology to enable substation-level situational awareness, and demonstrated SCE’s next-generation substation automation system. It extended beyond the substation to evaluate the latest generation of distribution automation technologies, including looped 12-kV distribution circuit topology using URCIs. The project team used DVVC capabilities to demonstrate CVR. In customer homes, the project evaluated HAN devices such as smart appliances, programmable communicating thermostats, and home energy management components. The homes were also equipped with energy storage, solar PV systems, and a number of energy efficiency measures (EEMs). The team used one block of homes to evaluate strategies and technologies for achieving ZNE. A home achieves ZNE when it produces at least as much renewable energy as the amount of energy it consumes annually. The project also assessed the impact of device-specific demand response (DR), as well as load management capabilities involving energy storage devices and plug-in electric vehicle charging equipment. In addition, the ISGD project sought to better understand the impact of ZNE homes on the electric grid. ISGD’s SENet enabled end-to-end interoperability between multiple vendors’ systems and devices, while also providing a level of cybersecurity that is essential to smart grid development and adoption across the nation. The ISGD project includes a series of sub-projects grouped into four logical technology domains: Smart Energy Customer Solutions, Next-Generation Distribution System, Interoperability and Cybersecurity, and Workforce of the Future. Section 2.3 provides a more detailed overview of these domains.

25 ENERGY STORAGE↗
DOE OSTI2012

A Novel Integrated Magnetic Structure Based DC/DC Converter for Hybrid Battery/Ultracapacitor Energy Storage Systems

This manuscript focuses on a novel actively controlled hybrid magnetic battery/ultracapacitor based energy storage system (ESS) for vehicular propulsion systems. A stand-alone battery system might not be sufficient to satisfy peak power demand and transient load variations in hybrid and plug-in hybrid electric vehicles (HEV, PHEV). Active battery/ultracapacitor hybrid ESS provides a better solution in terms of efficient power management and control flexibility. Moreover, the voltage of the battery pack can be selected to be different than that of the ultracapacitor, which will result in flexibility of design as well as cost and size reduction of the battery pack. In addition, the ultracapacitor bank can supply or recapture a large burst of power and it can be used with high C-rates. Hence, the battery is not subjected to supply peak and sharp power variations, and the stress on the battery will be reduced and the battery lifetime would be increased. Utilizing ultracapacitor results in effective capturing of the braking energy, especially in sudden braking conditions.

25 ENERGY STORAGE↗
DOE OSTI2014

Field Trial of a Low-Cost, Distributed Plug Load Monitoring System

Researchers have struggled to inventory and characterize the energy use profiles of the ever-growing category of so-called miscellaneous electric loads (MELs) because plug-load monitoring is cost-prohibitive to the researcher and intrusive to the homeowner. However, these data represent a crucial missing link to understanding how homes use energy. Detailed energy use profiles would enable the nascent automated home energy management (AHEM) industry to develop effective control algorithms that target consumer electronics and other plug loads. If utility and other efficiency programs are to incent AHEM devices, they need large-scale datasets that provide statistically meaningful justification of their investments by quantifying the aggregate energy savings achievable. To address this need, NREL researchers investigated a variety of plug-load measuring devices available commercially and tested them in the laboratory to identify the most promising candidates for field applications. This report centers around the lessons learned from a field validation of one proof-of-concept system, called Smartenit (formerly SimpleHomeNet). The system was evaluated based on the rate of successful data queries, reliability over a period of days to weeks, and accuracy. This system offers good overall performance when deployed with up to 10 end nodes in a residential environment, although deployment with more nodes and in a commercial environment is much less robust. NREL concludes that the current system is useful in selected field research projects, with the recommendation that system behavior is observed over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Long Island Smart Energy Corridor

The Long Island Power Authority (LIPA) has teamed with Stony Brook University (Stony Brook or SBU) and Farmingdale State College (Farmingdale or FSC), two branches of the State University of New York (SUNY), to create a “Smart Energy Corridor.” The project, located along the Route 110 business corridor on Long Island, New York, demonstrated the integration of a suite of Smart Grid technologies from substations to end-use loads. The Smart Energy Corridor Project included the following key features: -TECHNOLOGY: Demonstrated a full range of smart energy technologies, including substations and distribution feeder automation, fiber and radio communications backbone, advanced metering infrastructure (AM”), meter data management (MDM) system (which LIPA implemented outside of this project), field tools automation, customer-level energy management including automated energy management systems, and integration with distributed generation and plug-in hybrid electric vehicles. -MARKETING: A rigorous market test that identified customer response to an alternative time-of-use pricing plan and varying levels of information and analytical support. -CYBER SECURITY: Tested cyber security vulnerabilities in Smart Grid hardware, network, and application layers. Developed recommendations for policies, procedures, and technical controls to prevent or foil cyber-attacks and to harden the Smart Grid infrastructure. -RELIABILITY: Leveraged new Smart Grid-enabled data to increase system efficiency and reliability. Developed enhanced load forecasting, phase balancing, and voltage control techniques designed to work hand-in-hand with the Smart Grid technologies. -OUTREACH: Implemented public outreach and educational initiatives that were linked directly to the demonstration of Smart Grid technologies, tools, techniques, and system configurations. This included creation of full-scale operating models demonstrating application of Smart Grid technologies in business and residential settings. Farmingdale State College held three international conferences on energy and sustainability and Smart Grid related technologies and policies. These conferences, in addition to public seminars increased understanding and acceptance of Smart Grid transformation by the general public, business, industry, and municipalities in the Long Island and greater New York region. - JOB CREATION: Provided training for the Smart Grid and clean energy jobs of the future at both Farmingdale and Stony Brook. Stony Brook focused its “Cradle to Fortune 500” suite of economic development resources on the opportunities emerging from the project, helping to create new technologies, new businesses, and new jobs. To achieve these features, LIPA and its sub-recipients, FSC and SBU, each have separate but complementary objectives. At LIPA, the Smart Energy Corridor (1) meant validating Smart Grid technologies; (2) quantifying Smart Grid costs and benefits; and (3) providing insights into how Smart Grid applications can be better implemented, readily adapted, and replicated in individual homes and businesses. LIPA installed 2,550 AMI meters (exceeding the 500 AMI meters in the original plan), created three “smart” substations serving the Corridor, and installed additional distribution automation elements including two-way communications and digital controls over various feeders and capacitor banks. It gathered and analyzed customer behavior information on how they responded to a new “smart” TOU rate and to various levels of information and analytical tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Field Trial of a Low-Cost, Distributed Plug Load Monitoring System

Researchers have struggled to inventory and characterize the energy use profiles of the ever-growing category of so-called miscellaneous electric loads (MELs) because plug-load monitoring is cost-prohibitive to the researcher and intrusive to the homeowner. However, these data represent a crucial missing link to our understanding of how homes use energy, and we cannot control what we do not understand. Detailed energy use profiles would enable the nascent automated home energy management (AHEM) industry to develop effective control algorithms that target consumer electronics and other plug loads. If utility and other efficiency programs are to incent AHEM devices, they need large-scale datasets that provide statistically meaningful justification of their investments by quantifying the aggregate energy savings achievable. To address this need, we have investigated a variety of plug-load measuring devices available commercially and tested them in the laboratory to identify the most promising candidates for field applications. The scope of this report centers around the lessons learned from a field validation of one proof-of-concept system, called Smartenit (formerly SimpleHomeNet). The system was evaluated based on the rate of successful data queries, reliability over a period of days to weeks, and accuracy. This system offers good overall performance when deployed with up to ten end nodes in a residential environment, although deployment with more nodes and in a commercial environment is much less robust. We conclude that the current system is useful in selected field research projects, with the recommendation that system behavior is observed over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Laboratory Resources and Techniques to Evaluate Smart Home Technology: Preprint

Smart home technologies promise to make residential buildings more comfortable, less costly to operate, more energy efficient, and more integrated with the grid, but these systems are difficult to evaluate in traditional laboratory spaces. To aid in the development and evaluation of new home energy management systems (HEMS), NREL built the Systems Performance Laboratory (SPL) within the Energy Systems Integration Facility. SPL has electrical infrastructure for three residential buildings, complete with smart meters, breaker panels and a full complement of major and minor appliances in each 'home.' Cord and plug power connections mean that appliances can easily be swapped for different models. Distributed energy resources (DER), such as residential photovoltaic (PV) inverters and home batteries, are also available for integration. Sensors monitor the power consumption of all loads and controllers can simulate occupancy to drive the appliances in realistic ways. A novel hardware-in-the-loop application was developed to ensure air conditioner cycling by combining a building simulation with a physical air conditioner and a thermostat, which allows us to simulate performance in any climate with any building construction. Another application of the hardware-in-the-loop technique uses a grid simulation to model the grid impact for different control strategies related to smart home technologies. This laboratory is a powerful, flexible tool that can be employed to evaluate the effect that home energy management and other smart home technologies will have at the appliance, whole-home, and distribution feeder levels - all of which are important perspectives for different stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1983

Photovoltaic stand-alone modular systems, phase 2

The final hardware and system qualification phase of a two part stand-alone photovoltaic (PV) system development is covered. The final design incorporated modular, power blocks capable of expanding incrementally from 320 watts to twenty kilowatts (PK). The basic power unit (PU) was nominally rated 1.28 kWp. The controls units, power collection buses and main lugs, electrical protection subsystems, power switching, and load management circuits are housed in a common control enclosure. Photo-voltaic modules are electrically connected in a horizontal daisy-chain method via Amp Solarlok plugs mating with compatible connectors installed on the back side of each photovoltaic module. A pair of channel rails accommodate the mounting of the modules into a frameless panel support structure. Foundations are of a unique planter (tub-like) configuration to allow for world-wide deployment without restriction as to types of soil. One battery string capable of supplying approximately 240 ampere hours nominal of carryover power is specified for each basic power unit. Load prioritization and shedding circuits are included to protect critical loads and selectively shed and defer lower priority or noncritical power demands. The baseline system, operating at approximately 2 1/2 PUs (3.2 kW pk.) was installed and deployed. Qualification was successfully complete in March 1983; since that time, the demonstration system has logged approximately 3000 hours of continuous operation under load without major incident.

Naff, G. J.↗
NASA NTRS2018

RESTful CFDP: Managing GDS Complexity with Microservices

NASA's Advanced Multi-Mission Operations System (AMMOS) is currently adding capability to support the CCSDS File Delivery Protocol (CFDP). This feature is being added as part of the AMMOS Mission Data Processing and Control System (AMPCS). In order to address the system’s increasing complexity, AMPCS has recently been re-architected to break down its monolithic applications into smaller, individually deployable microservices. The CFDP capability is the first new AMPCS feature to leverage this new architecture. The CFDP microservice provides a web-based Representational State Transfer (REST) application programming interface (API) for complete monitor and control of its operations, and this enables it to be decoupled from other AMPCS microservices. This also results in better scalability for redundancy and load balancing. AMPCS's CFDP microservice is designed to support generic CFDP operations, agnostic to AMPCS's legacy concept of Downlink Products. An optional runtime plug-in allows the CFDP microservice to simulate CFDP artifacts as Downlink Products. Applying the microservices software architecture pattern both in the latest release of AMPCS and in providing the new CFDP capability has resulted in a more flexible system with improved extensibility and maintainability. System complexity has also become more manageable.

Choi, Joshua S.↗
DOE OSTI2019

A Hierarchical Charging Control of Plug-in Electric Vehicles with Simple Flexibility Model

The demand for plug-in electric vehicles (PEVs) is increasing exponentially, which could have significant effects on the power grid, because charging one PEV is nearly equivalent to adding three houses to the power system. Even though PEVs increase demand on the electric grid, their capability to actively interact with the grid presents excellent opportunities for load management, demand response, and various other grid services. This paper proposes an innovative scheduling and control framework to enable smart PEV charging for grid services while meeting PEV owners’ travel needs. In the proposed framework, each set of electric vehicle supply equipment (EVSE) is equipped with a controller that estimates charging power and energy flexibility based on vehicle characteristics, EVSE power rating, battery energy state, and upcoming trip information. With the charging flexibility model received from each EVSE controller, the central coordinator determines the optimal power allocation for a look-ahead time window for the given grid services. The proposed charging coordination strategy can help reduce the computational complexity and communication requirement compared with existing methods. It is also scalable to the expanding PEV fleet and robust to uncertainties in upcoming vehicle trips and future system condition. The proposed method is studied using a prototypical feeder developed at Pacific Northwest National Laboratory and detailed trip information extracted from the National Household Travel Survey.

Wu, Di↗
DOE OSTI2015

What is the Controllable Electrical Demand from Non-Residential Electric Vehicle Supply Equipment in the San Diego Region?

The EVSE deployed by The EV Project included both residential and non-residential units. Approximately 4,000 non-residential AC Level 2 (ACL2) EVSE were installed in workplace environments, fleet applications and publicly accessible locations near retail centers, parking lots, and similar locations. The power required to recharge a plug-in electric vehicle (PEV) can be a significant additional electrical load to electric grid but may also provide a controllable resource for mitigating grid overload issues. Electric utilities seek ways to reduce their generating costs by controlling the maximum (peak) load on their system, their generating resources, and frequency and voltage control on the system. This management may be achieved indirectly, through rates that incentivize their customers (including PEV owners) to manage the charging of their vehicles, or may take the form of direct utility control of non-residential EVSE. What insight can The EV Project data provide related to the magnitude of this impact and the potential controllable demand? The paper What is the Controllable Electrical Demand from Residential EVSE in the San Diego Region?1 addressed this question for residential EVSE. This paper quantifies the total controllable electrical load imposed on the electric grid by non-residential PEV charging in the San Diego region of The EV Project.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2012

Plug-Load Control and Behavioral Change Research in GSA Office Buildings

The U.S. General Services Administration (GSA) owns and leases over 354 million square feet (ft2) of space in over 9,600 buildings [1]. GSA is a leader among federal agencies in aggressively pursuing energy efficiency (EE) opportunities for its facilities and installing renewable energy (RE) systems to provide heating, cooling, and power to these facilities. According to several energy assessments of GSA's buildings conducted by the National Renewable Energy Laboratory (NREL), plug-loads account for approximately 21% of the total electricity consumed within a standard GSA Region 3 office building. This study aims to provide insight on how to effectively manage plug-load energy consumption and attain higher energy and cost savings for plug-loads. As GSA improves the efficiency of its building stock, plug-loads will become an even greater portion of its energy footprint.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1981

Technology development of the Space Transportation System mission and terrestrial applications of satellite technology

The Space Transportation System (STS) is discussed, including the launch processing system, the thermal protection subsystem, meteorological research, sound supression water system, rotating service structure, improved hypergol or removal systems, fiber optics research, precision positioning, remote controlled solid rocket booster nozzle plugs, ground operations for Centaur orbital transfer vehicle, parachute drying, STS hazardous waste disposal and recycle, toxic waste technology and control concepts, fast analytical densitometry study, shuttle inventory management system, operational intercommunications system improvement, and protective garment ensemble. Terrestrial applications are also covered, including LANDSAT applications to water resources, satellite freeze forecast system, application of ground penetrating radar to soil survey, turtle tracking, evaluating computer drawn ground cover maps, sparkless load pulsar, and coupling a microcomputer and computing integrator with a gas chromatograph.

Source record↗
DOE OSTI2020

Ibis Networks/WattIQ (IN2 Final Report)

Ibis Networks is a full-stack cleantech company that provides plug-level energy monitoring and control to solve energy and asset management problems for the enterprise. During DATES – DATES, an NREL research team worked with the Ibis team to validate their product, the InteliSocket. The Ibis InteliSocket is a pass-through plug-load energy monitor and controller that is designed to reduce energy wasted by common 120 V plug-in devices in commercial office buildings, such as computer peripherals, conference room AV equipment, and break-room appliances. The system can shut off supply power to these end uses via remote control, manual switches, pre-set schedules, or automated control algorithms. The scope of this IN2 project was the development and refinement of “smart” learning behavior algorithms (LBAs), which could help installation processes and dramatically expand the sockets’ capabilities and energy-saving potential by suggesting suitable control schedules that are based on monitored use patterns. While Ibis has the analytical and software expertise for algorithm development, the lack of test data, both in a controlled laboratory setting and in real-life deployment scenarios, represented a key barrier toward commercialization of the product. Assistance through the IN2 program provided an opportunity to conduct the needed “trial and error” algorithm development. The project included baseline field-data collection, laboratory testing, and field validation components, all of which were conducted at the NREL campus between April 2017 and July 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗