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At least 469 records · Page 26

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

15 GEOTHERMAL ENERGY↗

Big Data Mining for Assessing Calibration of Building Energy Models

Residential and commercial buildings in China, India, the United States (US), United Kingdom (UK), and Italy consume 39-45% of each nation's primary energy. Building energy models can be used to automatically optimize the return-on-investment for retrofits to improve a building’s energy efficiency. However, with an average of 3,000 building descriptors necessary to accurately simulate a single building, there is a market need to reduce the transaction cost for creating a more robust model for simulating every building in a city and accurately estimate savings prior to capital expenditures.We used two of the world’s fastest supercomputers, assembled unique datasets, and developed innovative algorithms for big data mining to assess different methods to create an accurate building energy model. The team has leveraged a total of eight high performance computing resources and 218 servers to analyze the best methods, metrics, and algorithms for creating an accurate building energy model beyond current industry standards necessary for private-sector financing. The project developed the world’s fastest buildings simulator, has completed over 8 million simulations totaling over 300TB, and mined this data with over 130,000 parallel artificial intelligence algorithms. This was used to quantify accuracy of AI-developed calibration algorithms with results that surpass industry standard guidelines and can identify individual building parameters to between 15% and 32% of their actual value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FECM/NETL CO2 Saline Storage Cost Model CO2_S_COM 2024 (v4)

The U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM), in collaboration with the National Energy Technology Laboratory (NETL), has developed the FECM/NETL CO2 Saline Storage Cost Model (CO2_S_COM). This Excel-based tool provides a comprehensive framework for estimating the costs and breakeven prices associated with storing carbon dioxide (CO2) in deep saline formations. Designed from the perspective of a CO2 storage site owner, the CO2_S_COM incorporates four integrated modules—project management, financial analysis, activity cost estimation, and geological evaluation—to deliver fast, robust and actionable insights for screening project finances.

CO2 storage↗

The BayREN Integrated Commercial Retrofits (BRICR) Project: An Introduction and Preliminary Results

BayREN Integrated Commercial Retrofits (BRICR) is a DOE-funded project which aims to enhance the capacity of energy efficiency programs to recruit participants, develop retrofits, and measure outcomes in small and medium-sized commercial buildings, a sector notoriously hard to reach and expensive to serve, that accounts for 2/3 of US commercial floor space. To address these barriers, BRICR leverages existing incentives, financing, data, and open source software to facilitate two paths for comprehensive improvements: a deep energy retrofit, or serial upgrades integrated into capital improvement and maintenance cycles. BRICR is developing an integrated workflow for iterative energy modeling of commercial buildings for city energy program managers and auditors - starting with mass building-scale simulation based on public records and proceeding through audit, retrofit, and measurement and verification stages. BRICR builds on existing tools including LBNL’s CBES, NREL’s OpenStudio, PNNL’s Audit Template, and DOE’s BuildingSync and SEED PlatformTM. At each stage, BRICR uses available information to inform simulations (starting with public records but iteratively augmented with observations from energy program staff) to improve the quality of the models that inform decision making. This paper presents initial results from energy models of 1699 office and retail buildings in San Francisco. Building stock data from public records were translated to create a BuildingSync file for each building which was stored in SEED. Each BuildingSync file was then translated to multiple OpenStudio Workflow files for EnergyPlus simulation to estimate energy savings of energy conservation measures (ECM). Energy savings predictions for each ECM were written back to an updated BuildingSync file for each building and re-uploaded to SEED. The distribution of baseline energy simulations was calibrated against the publicly disclosed distribution of energy benchmarking data to increase confidence in results.

Piette, M↗

Cyber Friendly Fire

Cyber friendly fire (FF) is a new concept that has been brought to the attention of Department of Defense (DoD) stakeholders through two workshops that were planned and conducted by the Air Force Research Laboratory (AFRL) and research conducted for AFRL by the Pacific Northwest National Laboratory. With this previous work in mind, we offer a definition of cyber FF as intentional offensive or defensive cyber/electronic actions intended to protect cyber systems against enemy forces or to attack enemy cyber systems, which unintentionally harms the mission effectiveness of friendly or neutral forces. Just as with combat friendly fire, a fundamental need in avoiding cyber FF is to maintain situation awareness (SA). We suggest that cyber SA concerns knowledge of a system's topology (connectedness and relationships of the nodes in a system), and critical knowledge elements such as the characteristics and vulnerabilities of the components that comprise the system (and that populate the nodes), the nature of the activities or work performed, and the available defensive (and offensive) countermeasures that may be applied to thwart network attacks. A training implication is to raise awareness and understanding of these critical knowledge units; an approach to decision aids and/or visualizations is to focus on supporting these critical knowledge units. To study cyber FF, we developed an unclassified security test range comprising a combination of virtual and physical devices that present a closed network for testing, simulation, and evaluation. This network offers services found on a production network without the associated costs of a real production network. Containing enough detail to appear realistic, this virtual and physical environment can be customized to represent different configurations. For our purposes, the test range was configured to appear as an Internet-connected Managed Service Provider (MSP) offering specialized web applications to the general public. The network is essentially divided into a production component that hosts the web and network services, and a user component that hosts thirty employee workstations and other end devices. The organization's network is separated from the Internet by a Cisco ASA network security device that both firewalls and detects intrusions. Business sensitive information is stored in various servers. This includes data comprising thousands of internal documents, such as finance and technical designs, email messages for the organization's employees including the CEO, CFO, and CIO, the organization's source code, and Personally Identifiable client data. Release of any of this information to unauthorized parties would have a significant, detrimental impact on the organization's reputation, which would harm earnings. The valuable information stored in these servers pose obvious points of interest for an adversary. We constructed several scenarios around this environment to support studies in cyber SA and cyber FF that may be run in the test range. We describe mitigation strategies to combat cyber FF including both training concepts and suggestions for decision aids and visualization approaches. Finally, we discuss possible future research directions.

99 GENERAL AND MISCELLANEOUS↗

To'Hajiilee Economic Development, Inc. (TEDI) Feasibility Study for Utility-Scale Solar

To Hajiilee Economic Development, Inc. (TEDI) is the economic development entity representing the ToHajiilee Chapter of the Navajo Nation, also known as the Caoncito Band of Navajo (CBN). Using DOE funding, TEDI assembled a team of qualified advisors to conduct a feasibility study for a utility-scale 30 MW Photovoltaic (PV) solar power generation facility on TEDI trust lands. The goal for this project has been to gather information and practical business commitments to successfully complete the feasibility analysis. The TEDI approach was to successively make informed decisions to select an appropriate technology best suited to the site, determine environmental viability of the site, secure options for the sale of generated power, determine practicality of transmission and interconnection of power to the local grid, and secure preliminary commitments on project financing. The feasibility study has been completed and provides TEDI with a practical understanding of its business options in moving forward with developing a solar project on CBN tribal lands. Funding from DOE has allowed TEDI and its team of professional advisors to carefully select technology and business partners and build a business model to develop this utility-scale solar project. As a result of the positive feasibility findings, TEDI is moving forward with finalizing all pre-construction activities for its major renewable energy project.

14 SOLAR ENERGY↗

Arizona Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Arizona homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost-effective over a 30-year life cycle. On average, Arizona homeowners will save $\$$3,245 over 30 years under the 2009 IECC, with savings still higher at $\$$6,550 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for the 2009 and 2 years with the 2012 IECC. Average annual energy savings are $\$$231 for the 2009 IECC and $486 for the 2012 IECC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Delaware Energy and Cost Savings for New Single- and Multifamily Homes: 2012 IECC as Compared to the 2009 IECC

The 2012 International Energy Conservation Code (IECC) yields positive benefits for Delaware homeowners. Moving to the 2012 IECC from the 2009 IECC is cost effective over a 30-year life cycle. On average, Delaware homeowners will save $\$$10,409 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for the 2012 IECC. Average annual energy savings are $\$$616 for the 2012 IECC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Massachusetts Energy and Cost Savings for New Single- and Multifamily Homes: 2012 IECC as Compared to the 2009 IECC

The 2012 International Energy Conservation Code (IECC) yields positive benefits for Massachusetts homeowners. Moving to the 2012 IECC from the 2009 IECC is cost effective over a 30-year life cycle. On average, Massachusetts homeowners will save $\$$10,848 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for the 2012 IECC. Average annual energy savings are $\$$621 for the 2012 IECC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Minnesota Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the Minnesota Residential Energy Code

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Minnesota homeowners. Moving to either the 2009 or 2012 IECC from the current Minnesota Residential Energy Code is cost effective over a 30-year life cycle. On average, Minnesota homeowners will save $\$$1,277 over 30 years under the 2009 IECC, with savings still higher at $\$$9,873 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceed cumulative cash outlays) in 3 years for the 2009 IECC and 1 year for the 2012 IECC. Average annual energy savings are $\$$122 for the 2009 IECC and $669 for the 2012 IECC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rhode Island Energy and Cost Savings for New Single- and Multifamily Homes: 2012 IECC as Compared to the 2009 IECC

The 2012 International Energy Conservation Code (IECC) yields positive benefits for Rhode Island homeowners. Moving to the 2012 IECC from the 2009 IECC is cost effective over a 30-year life cycle. On average, Rhode Island homeowners will save $\$$11,011 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for the 2012 IECC. Average annual energy savings are $\$$629 for the 2012 IECC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Alabama Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Alabama homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Alabama homeowners will save $\$$2,117 over 30 years under the 2009 IECC, with savings still higher at $\$$6,182 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 2 years for both the 2009 and 2012 IECC. Average annual energy savings are $\$$168 for the 2009 IECC and $462 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Arkansas Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Arkansas homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Arkansas homeowners will save $\$$1,948 over 30 years under the 2009 IECC, with savings still higher at $\$$6,679 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 2 years for the 2009 and 1 year for the 2012 IECC. Average annual energy savings are $\$$147 for the 2009 IECC and $\$466 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Iowa Energy and Cost Savings for New Single- and Multifamily Homes: 2012 IECC as Compared to the 2009 IECC

The 2012 International Energy Conservation Code (IECC) yields positive benefits for Iowa homeowners. Moving to the 2012 IECC from the 2009 IECC is cost effective over a 30-year life cycle. On average, Iowa homeowners will save $\$$7,573 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for the 2012 IECC. Average annual energy savings are $\$$454 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Kansas Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Kansas homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Kansas homeowners will save $\$$2,556 over 30 years under the 2009 IECC, with savings still higher at $\$$8,828 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for both the 2009 and 2012 IECC. Average annual energy savings are $\$$155 for the 2009 IECC and $\$$543 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Louisiana Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Louisiana homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Louisiana homeowners will save $\$$1,663 over 30 years under the 2009 IECC, with savings still higher at $\$$4,107 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 2 years for both the 2009 and 2012 IECC. Average annual energy savings are $\$$149 for the 2009 IECC and $\$$358 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mississippi Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Mississippi homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Mississippi homeowners will save $\$$2,022 over 30 years under the 2009 IECC, with savings still higher at $\$$5,400 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 2 years for both the 2009 and 2012 IECC. Average annual energy savings are $\$$164 for the 2009 IECC and $\$$422 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Missouri Energy and Cost Savings for New Single- and Multifamily Homes: 2009 and 2012 IECC as Compared to the 2006 IECC

The 2009 and 2012 International Energy Conservation Codes (IECC) yield positive benefits for Missouri homeowners. Moving to either the 2009 or 2012 IECC from the 2006 IECC is cost effective over a 30-year life cycle. On average, Missouri homeowners will save $\$$2,229 over 30 years under the 2009 IECC, with savings still higher at $\$$7,826 with the 2012 IECC. After accounting for upfront costs and additional costs financed in the mortgage, homeowners should see net positive cash flows (i.e., cumulative savings exceeding cumulative cash outlays) in 1 year for both the 2009 and 2012 IECC. Average annual energy savings are $\$$143 for the 2009 IECC and $\$$507 for the 2012 IECC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗