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Optimizing the Energy Usage and Cognitive Value of Extreme Scale Data Analysis Approaches (Final Report)
High performance computers and the people who use them constitute a distributed cognitive system, with part of the work being done in the machine and part in the brains of developer scientists. The UNH portion of this proposal was devoted to the perceptual and cognitive optimization of workflows and visualizations use in High Performance Computing.
Energy Saving Analysis Using Energy Intensity Usage and Specific Energy Consumption Methods
This study presents the energy saving analysis reached through employing the energy intensity usage and specific energy consumption method. The energy analyses conducted in this study are used for implementing a new technology. However, they are additionally used to evaluate the latest concepts, techniques, processes, and uses for technologies, which are aimed at improvement of energy savings. This study shows the correlation between energy consumption, potential energy savings, and the impact of the energy assessment in different industrial sectors. The correlation is found by using two indicators: (1) the energy intensity usage (EIU) and (2) the specific energy consumption (SEC). The data analysis in this study considers the assessments for 67 industries from 2015 to 2019 and classifies those assessments using the Standard Industrial Classification (SIC) code. The results show that energy savings and energy consumption are linearly related. Also, the energy assessment improves energy performance in a more significant way for smaller companies than for larger industries. Furthermore, these results can be extrapolated by identifying the potential benefits of the energy management system (EMS) implementation.
Aerospace Fuels From Nonpetroleum Raw Materials
Recycling human metabolic and plastic wastes minimizes cost and increases efficiency by reducing the need to transport consumables and return trash, respectively, from orbit to support a space station crew. If the much larger costs of transporting consumables to the Moon and beyond are taken into account, developing waste recycling technologies becomes imperative and possibly mission enabling. Reduction of terrestrial waste streams while producing energy and/or valuable raw materials is an opportunity being realized by a new generation of visionary entrepreneurs; several relevant technologies are briefly compared, contrasted and assessed for space applications. A two-step approach to nonpetroleum raw materials utilization is presented; the first step involves production of supply or producer gas. This is akin to synthesis gas containing carbon oxides, hydrogen, and simple hydrocarbons. The second step involves production of fuel via the Sabatier process, a methanation reaction, or another gas-to-liquid technology, typically Fischer-Tropsch processing. Optimization to enhance the fraction of product stream relevant to transportation fuels via catalytic (process) development at NASA Glenn Research Center is described. Energy utilization is a concern for production of fuels whether for operation on the lunar or Martian surface, or beyond. The term green relates to not only mitigating excess carbon release but also to the efficiency of energy usage. For space, energy usage can be an essential concern. Another issue of great concern is minimizing impurities in the product stream(s), especially those that are potential health risks and/or could degrade operations through catalyst poisoning or equipment damage; technologies being developed to remove heteroatom impurities are discussed. Alternative technologies to utilize waste fluids, such as a propulsion option called the resistojet, are discussed. The resistojet is an electric propulsion technology with a powered thruster to vaporize and heat a propellant to high temperature, hot gases are subsequently passed through a converging-diverging nozzle expanding gases to supersonic velocities. A resistojet can accommodate many different fluids, including various reaction chamber (by-)products.
Aerospace Fuels from Nonpetroleum Raw Materials
Recycling human metabolic and plastic wastes minimizes cost and increases efficiency by reducing the need to transport consumables and return trash, respectively, from orbit to support a space station crew. If the much larger costs of transporting consumables to the Moon and beyond are taken into account, developing waste recycling technologies becomes imperative and possibly mission enabling. Reduction of terrestrial waste streams while producing energy and/or valuable raw materials is an opportunity being realized by a new generation of visionary entrepreneurs; several relevant technologies are briefly compared, contrasted and assessed for space applications. A two-step approach to nonpetroleum raw materials utilization is presented; the first step involves production of supply or producer gas. This is akin to synthesis gas containing carbon oxides, hydrogen, and simple hydrocarbons. The second step involves production of fuel via the Sabatier process, a methanation reaction, or another gas-to-liquid technology, typically Fischer- Tropsch processing. Optimization to enhance the fraction of product stream relevant to transportation fuels via catalytic (process) development at NASA GRC is described. Energy utilization is a concern for production of fuels whether for operation on the lunar or Martian surface, or beyond. The term "green" relates to not only mitigating excess carbon release but also to the efficiency of energy usage. For space, energy usage can be an essential concern. Other issues of great concern include minimizing impurities in the product stream(s), especially those that are potential health risks and/or could de-grade operations through catalyst poisoning or equipment damage; technologies being developed to remove heteroatom impurities are discussed. Alternative technologies to utilize waste fluids, such as a propulsion option called the resistojet, are discussed. The resistojet is an electric propulsion technology with a powered thruster to vaporize and heat a propellant to high temperature, hot gases are subsequently passed through a converging-diverging nozzle expanding gases to supersonic velocities. A resistojet can accommodate many different fluids, including various reaction chamber (by-)products.
Real time trajectory optimization for hybrid energy management utilizing connected information technologies
The disclosure is directed to solving a full trajectory optimization problem in real-time for a hybrid electric vehicle (HEV) such that future driving conditions and energy usage may be fully considered in determining optimal engine energy usage and battery energy usage in real-time during a trip. An electronic control unit of the HEV may be configured to: receive route information for a route to be driven by the HEV; and after receiving the route information, iterating the operations of: measuring a current state of charge (SOC) of the battery; using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the co-state value to obtain an updated co-state value; using at least the updated co-state value, computing an updated control value; and applying the updated control value to control a usage of the battery and the internal combustion engine.
Cybersecurity Considerations and Research Pathways for Grid-Interactive Efficient Buildings
Federal facilities serve critical missions and functions that require safe, reliable, and efficient operations. Digitization of several facility operations has increased the cost-effectiveness of energy usage and optimization of energy system performance. As the building controls landscape shifts to become more connected and smarter, building operators now face unique opportunities and challenges to adopt smart enabled devices that can lower energy usage while also optimizing building system performance. The grid-interactive efficient buildings (GEB) initiative aims to make buildings cleaner and more flexible through these smart devices. Smart enabled devices allow greater connectivity and control through remote operations and provide crucial data for analytics and increased efficiency. GEBs enable demand flexibility that has the potential to reduce electrical costs and transform the grid edge where buildings connect to power grids. This operation of interconnected systems, if not designed with cybersecurity practices, causes security gaps and introduces potential attack paths by adversarial and non-adversarial entities leading to disruption of operations.
Assessment of small mechanical wastewater treatment plants: Relative life cycle environmental impacts of construction and operations
Many slow growing and shrinking rural communities struggle with aging or inadequate wastewater treatment plants (WWTPs), and face challenges in constructing and operating such facilities. Although existing literature has provided insight into the environmental sustainability of large facilities, including both the construction and operational phases, these studies have not examined small, rural facilities treating less than 7,000 m 3 /d (1.8 MGD) of wastewater in adequate depth and breadth. In this study, a detailed inventory of the construction and operational data for 16 case studies of small WWTPs was developed to elucidate their environmental life cycle impacts. Conventional LCA framework was followed. The results show that the environmental impacts of both the construction and operational phases are considerable. Operational impacts are highly related to energy usage. Improving energy efficiency of a plant may reduce the environmental impacts related to operations. Construction impacts can vary considerably between facilities. Process-related factors (e.g., concrete and reinforcing steel used in basins) are typically sized using the design flow; thus much of the variability in construction impacts among plants stems from the non-process related infrastructure. Multiple regression analysis was used as an exploratory tool to identify which non-process related plant aspects contribute to the variable environmental impact of small WWTPs. These factors include aluminum, cast iron, and the capacity utilization ratio (defined as the ratio of average flow to design flow). Furthermore, industry practitioners should consider these factors when aiming to reduce the environmental impacts of a small WWTP related to construction. Scenario sensitivity analyses found that the environmental impact of construction became smaller with longer design life, and the end-of-life consideration does not heavily influence the environmental sustainability of a WWTP.
Building Climate Resilience at NASA Ames
NASA Ames Research Center, located at the southern end of the San Francisco Bay (SFB) estuary has identified three primary vulnerabilities to changes in climate. The Ames Climate Adaptation Science Investigator (CASI) workgroup has studied each of these challenges to operations and the potential exposure of infrastructure and employees to an increased frequency of hazards. Sea level rise inundation scenarios for the SFB Area generally refer to projected scenarios in mean sea level rather than changes in extreme tides that could occur during future storm conditions. In the Summer of 2014, high resolution 3-D mapping of the low lying portion of Ames was performed. Those data are integrated with improved sea level inundation scenarios to identify the buildings, basements and drainage systems potentially affected. We will also identify the impacts of sea level and storm surge effects on transportation to and from the Center. This information will help Center Management develop future Master Plans. Climate change will also lead to changes in temperature, storm frequency and intensity. These changes have potential impacts on localized floods and ecosystems, as well as on electricity and water availability. Over the coming decades, these changes are going to be imposed on top of ongoing land use and land cover changes, especially those deriving from continued urbanization and increase in impervious surface areas. These coupled changes have the potential to create a series of cascading impacts on ecosystems, including changes in primary productivity and disturbance of hydrological properties and increased flood risk.The majority of the electricity used at Ames is supplied by hydroelectric dams, which will be influenced by reductions in precipitation or changes in the timing or phase of precipitation which reduces snow pack. Coupled with increased demand for summertime air conditioning and other cooling needs, NASA Ames is at risk for electricity shortfalls. To assess the anticipated energy usage as climate changes, the Ames CASI team is collecting historical energy usage data from Ames facilities, historical weather data, and projected future weather parameters from the CASI Climate subgroup. This data will be incorporated into the RETScreen model to predict how energy usage at Ames will change over the coming century.
Spatiotemporal dynamics of CO 2 emissions from central heating supply in the North China Plain over 2012–2016 due to natural gas usage
Energy consumption from central heating has rapidly increased in the cities of the North China Plain (NCP). The significant use of natural gas in the central heating supply system may have altered the spatial and temporal patterns of CO 2 emissions from central heating, yet the quantitative impacts are poorly understood. In this work, we detect the spatio-temporal dynamics of CO 2 emissions of central heating from 2012 to 2016 at the prefectural-city level in the NCP region, by using the satellite NPP-VIIRS nighttime light data and a panel regression model to estimate CO 2 emissions on a 5 x 5 km 2 grid. We find that despite a slight decrease (2%) in 2014 under the "Natural Gas Utilization Policy", CO 2 emissions continued to grow. Between 2012 and 2016, CO 2 emissions from central heating in the NCP increased from 106 to 121 Tg, although CO 2 emissions declined by 12% in Beijing due to the increasing contribution of natural gas boilers. The gridded CO 2 emissions map shows that over 2012-2016 coal burning is the main driving force of CO 2 emissions in both urban and non-urban regions, despite the increasing fraction of gas-based heating. Our results contribute to city-level policymaking on carbon reduction and climate change mitigation. The high-resolution gridded CO 2 emissions can also be applied in physical models to facilitate carbon cycle studies.
Energy Data from Heat Pumps Installed in Juneau, AK
Heat pumps offer a great low carbon emission method to heat homes. Thermalize Juneau 2021 was a clean energy campaign that helped homeowners in Juneau, Alaska install heat pumps into their homes. Juneau is located near the climactic limit of many heat pumps, and we were interested in how well the heat pumps can function in cold climates. This was done by using Sense meters to remotely monitor the energy usage of 10 homes with heat pumps. The Sense meters are small devices that connect to the electrical panel and monitor the energy use of multiple appliances through machine learning. First, we recorded the energy usage of a heat pump in the lab using both the Sense meter and the existing lab datalogger. Both recorded very similar energy usage data which confirmed that the Sense meter can accurately measure the fluctuations in the heat pump energy use. Next, we looked at the energy data from the Sense meters in the homes with heat pumps and paired it with local weather data to see how well the heat pumps functioned in the cold weather.
Systems and methods for data analytics for virtual energy audits and value capture assessment of buildings
A system may provide virtual energy audits of one or more target buildings. The system may retrieve weather data and energy usage data specific to a given target building from a weather server and a utility server, respectively. The system may store predefined building characteristics corresponding to the given target building in local memory. Based on the weather data, energy usage data, and/or predefined building characteristics, the system may generate one or more building markers that characterize the energy usage and efficiency of the given target building. Building efficiency diagnostics and energy conservation prognostics may be generated based on the building markers and may be sent by the system to be displayed via a user interface of a client device. The energy conservation prognostics may include one or more energy conservation measure recommendations and corresponding predicted cost/energy savings.
New U.S. Data Tools are Playing a Crucial Role in Decarbonizing Buildings at Speed, Scale, and Low Cost
Preparing buildings for retrofits traditionally requires expensive on-site audits or timeintensive simulation models. As a result, the majority of buildings fail to pursue cost-saving retrofits. To address these barriers, the U.S. Department of Energy (DOE) has introduced the Building Efficiency Targeting Tool for Energy Retrofits (BETTER)-a new, free, on-line tool that utilizes a data-driven analytical engine and user-friendly web interface to automatically analyze a building's monthly energy usage in response to weather conditions. The tool benchmarks a building's electric and fossil energy usage against peers; estimates energy, cost, and emissions reductions at the building and portfolio levels; recommends energy efficiency measures; and prioritizes buildings for net-zero energy retrofits. Thanks to interoperability with the DOE's Standard Energy Efficiency Data (SEED) platform, BETTER is supporting U.S. jurisdictions to prepare buildings for retrofit at speed, scale, and low cost to comply with energy policies. This paper discusses the use of BETTER and SEED by one of the branches of the California state government to streamline a retrofit program across 455 public non-residential buildings to align with state goals to reduce greenhouse gas emissions. It describes the organization's challenge to reduce energy consumption across a geographically diverse, aging portfolio; explores how BETTER and SEED improved workflow efficiency; presents preliminary results, including avoiding audit costs of $3.28 million and developing the groundwork for retrofit projects estimated to prevent emission of 2,271 t CO2e annually; and provides guidance for other jurisdictions seeking similar results.
New U.S. Data Tools are Playing a Crucial Role in Decarbonizing Buildings at Speed, Scale, and Low Cost
Preparing buildings for retrofits traditionally requires expensive on-site audits or time- intensive simulation models. As a result, the majority of buildings fail to pursue cost-saving retrofits. To address these barriers, the U.S. Department of Energy (DOE) has introduced the Building Efficiency Targeting Tool for Energy Retrofits (BETTER)—a new, free, on-line tool that utilizes a data-driven analytical engine and user-friendly web interface to automatically analyze a building’s monthly energy usage in response to weather conditions. The tool benchmarks a building’s electric and fossil energy usage against peers; estimates energy, cost, and emissions reductions at the building and portfolio levels; recommends energy efficiency measures; and prioritizes buildings for net-zero energy retrofits. Thanks to interoperability with the DOE’s Standard Energy Efficiency Data (SEED) platform, BETTER is supporting U.S. jurisdictions to prepare buildings for retrofit at speed, scale, and low cost to comply with energy policies. This paper discusses the use of BETTER and SEED by one of the branches of the California state government to streamline a retrofit program across 455 public non-residential buildings to align with state goals to reduce greenhouse gas emissions. It describes the organization’s challenge to reduce energy consumption across a geographically diverse, aging portfolio; explores how BETTER and SEED improved workflow efficiency; presents preliminary results, including avoiding audit costs of $3.28 million and developing the groundwork for retrofit projects estimated to prevent emission of 2,271 t CO2e annually; and provides guidance for other jurisdictions seeking similar results.
Numerical Study of Liquid Piston Compression Using Large-Eddy Simulation and Volume-of-Fluid Approach
Efforts to increase the efficiency of residential and commercial air conditioners and heat pumps have demonstrated that the compressor accounts for most of the system’s electrical energy usage. Therefore, the efficiency of this component should be improved to reduce its energy usage. The US Department of Energy’s Oak Ridge National Laboratory developed a near-isothermal liquid piston compressor (LPC) that uses propylene glycol (PG) to compress CO2. This report presents numerical studies of the LPC in which the compression chamber fills with injected PG from the bottom inlet. Numerical simulations were performed using the large-eddy simulation (LES) with the wall-adapting local eddy-viscosity (WALE) subgrid-scale model coupled with the multiphase volume-of-fluid (VOF) model to simulate the transient interface between gas and liquid and to capture the heat and mass transfer within the compression chamber. In this effort, effects of boundary conditions applied to the LES-VOF calculations (e.g., no wall, an adiabatic wall, and a wall with a heat flux subscribed) to the overall pressure and temperature of CO2 gas as well as the transient evolution of flow and heat transfer evolution within the compression chamber are investigated and discussed. It was found that the LES calculation with no wall have shown no dynamical flow patterns and the volume-averaged temperature of CO2 increased from 305 to 392.7 K, while LES calculations with a constant wall temperature or a wall heat flux had similar increases of CO2 temperatures. Results of LES simulation using a wall heat flux showed different stages in the compression process and revealed dynamical formation and interaction of CO2 gas layers and circulation flow patterns within the chamber that contribute to the overall heat transfer between the solid wall, gas, and liquid surface in the compressor.
Makah Tribe Strategic Energy Plan
The U.S. Department of Energy’s (DOE) Energy Transitions Initiative Partnership Project (ETIPP) connects remote and island communities, regional partners, and the DOE national laboratories to support communities as they seek to build resilience in their energy systems. The Makah Tribe faces several energy challenges, including frequent power outages and the potential for an extended outage due to an earthquake or tsunami. The Tribe joined ETIPP in 2022 to address those challenges, seeking to build energy resilience and sovereignty in the community. The Makah Tribe, Spark Northwest, the Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL) collaborated to develop a strategic energy plan as part of the second cohort of ETIPP communities. The long-term energy vision of the Makah Tribe includes increasing energy efficiency in the community, improving energy management capacity, and developing the renewable energy generation and storage sufficient to independently power the Reservation for one year. Additionally, the ETIPP team worked with Makah leadership, staff, and community members to identify a set of community priorities, values, and goals to guide energy development as the Tribe takes the incremental steps toward their vision for energy sovereignty. Those energy values include ecosystem-based management, energy sovereignty and project ownership, workforce development and capacity, economic opportunity, community wellbeing and priorities, and emergency disaster resilience. To understand what would be needed for a year for energy independence, the PNNL team conducted an assessment to determine the current energy usage of the Tribe and also modeled several scenarios for future energy use. Using the energy usage values, the team estimated how two types of renewable energy technology, specifically locally deployed solar and small-scale wind, could contribute towards the energy independence goal. The energy baseline and resource assessment produced the following key findings:
Intelligent industrial demand response to increase grid flexibility and reliability: A review
The rapid transition toward renewable energy has introduced challenges in grid stability due to the intermittency of non-dispatchable sources like solar and wind. Industrial Demand Response (IDR) offers a promising, cost-effective solution that adjusts energy consumption patterns to align with supply, increases renewable utilization, and reduces costs. This review provides an updated analysis of IDR, sorting technologies into five categories: energy storage, scheduled energy usage, operational flexibility, on-site generation, and intelligent operations. Energy storage solutions, while requiring little flexibility, often have the longest payback periods. While slightly better, on-site generation also has longer payback periods, ranging from 5 to 20 years or more. Scheduled energy usage, operational flexibility, and intelligent operations allow significant peak reduction at lower capital costs but require greater flexibility. While 15–20 % peak reduction is within the range of all five categories, scheduled energy use and on-site energy generation are shown to have reductions of up to 70–80 % in select scenarios. Combining multiple IDR strategies from these five categories maximizes both financial and operational benefits. Synergistic approaches are shown to enhance grid stability while reducing costs. As the grid evolves, IDR will enable a more flexible, renewable-powered future that will benefit industrial facilities and the broader energy system.
Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking
The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.