Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Commercial Building”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms

The “Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms” project focuses on exploring alternative power converter and system-level plant configurations to achieve the lowest cost and highest energy output for a given solar plus storage (e.g., PV + battery) plant, including the use of medium voltage (MV) collection while taking into account detailed models of all elements. To realize this objective, four approaches were utilized (i) employ a novel Medium Voltage String Inverter (MVSI) topology (soft switching solid state transformer – S4T) to convert 1000 Vdc to 4.16 kVac; (ii) plant collection using standard, low-cost overhead MV distribution network; (iii) enable energy storage integration without additional converter cost to achieve dispatchability of the PV resource; and (iv) provide advanced functionality (autonomous operation, track ISO signals for dynamic balancing and ancillary services, and PV farm operation as a virtual grid resource). Subsequently and in alignment with the previously mentioned approaches, the project was structured in five efforts (i) S4T MVSI simulation and design; (ii) system analysis and storage optimization; (iii) financial analysis; (iv) power converter prototype build and test; and (v) regulatory and commercial impact study. The outcomes provided by each effort can be summarized as follows (i) Project explored the use of MV AC distribution architecture for hybrid PV+storage utility-scale PV farms; (ii) Detailed loss and LCOE analysis for AC and DC side BESS architecture, including multiple converter topologies, as well as for proposed MVSI/MDCT systems; (iii) MVSI was built and holds promise but needs lower-cost high-voltage Si-C devices, which does not seem possible in the near term; (iv) MDCT provides a simpler modular building block – validated through HIL and farm level modeling, simulation and experimental validation; (v) 300 kVA MDCT prototype built and tested, technology is being commercialized; and (vi) Regulatory model of utility building PV plants, where PV panels are treated as DC generation (IPP), seems viable and can allow improved grid integration.

14 SOLAR ENERGY↗
DOE OSTI2023

Building an EPA Class VI Permit Application

Summary To accelerate the commercialization of carbon capture and storage (CCS), the US Department of Energy (US DOE) is building on decades of characterization efforts and pilot-scale projects through their CarbonSAFE program. Administered through their National Energy Technology Laboratory, this program seeks to bring fully integrated projects to the sector that can store more than 50 million tonnes of CO2 over a 30-year period. The program, which was enacted before the enhancement of Internal Revenue Code Section 45Q, is in the capture assessment, characterization, and permitting phase. The objectives of this paper are to discuss (a) the injection permitting requirements of the CarbonSAFE projects; (b) information gathering in support of the permit; (c) the timelines of field development and permit-related activities; (d) the major technical components of the field development plan; and (e) early feedback from the regulators toward acceptance of the permit. In Mississippi, more than 30,000 acres have been characterized by six deep characterization wells, a deep groundwater well, and 92 line miles of 2D seismic as part of the CarbonSAFE Project ECO2S. During the acquisition of seismic data, all receiver lines were live, which resulted in the generation of a pseudo-3D seismic design. The incorporation of a 3D seismic survey was not included as part of this project due to logistical difficulties presented by the undulating, wooded surface terrain. A suite of openhole geophysical logs was taken from each well, allowing for a detailed interpretation of prospective storage reservoirs and confining intervals to complement the analysis carried out on the 290 ft of a whole core that was cut through the prospective confining zone and storage reservoir. The detailed geologic and reservoir data were assembled and entered into a 3D model to assess the injection capacity and the area of review (AoR). This information fed into the detailed corrective action, monitoring, testing, and postinjection site care (PISC) modeling. The results have been exceptional. The geologic assessment has revealed three primary storage targets, ranging in depth from 3,500 ft to 6,000 ft. These storage reservoirs net 1,300 ft of sandstone, with mean porosity and permeability of 29% and 3.6 darcies, respectively. Together, these reservoirs have storage capacities that may exceed 20 million tonnes per square mile, making this a gigatonne prospect. Forward modeling of the project resulted in an AoR of 16 sq miles, injecting about 8000 t/d, for 30 years, via two deep injection wells. The excellent confining characteristics of the caprock, relatively simple geologic structure, and lack of historical well drilling activity in this area provide excellent containment of the injected CO2. Based on this work, the project has proposed 20 years of PISC. To date, only two US CO2 injection permits have been granted. These projects relied on a singular capture point feeding a singular sequestration point (source to sink), and considerations have not been made to garner CO2 emissions from other industrial sources. The Kemper County Storage Complex is a first-of-its-kind storage hub concept that looks to develop an area capable of storing significant quantities of CO2 from the region. Also, this work will show how characterization efforts, geological and numerical modeling efforts, and plan development were constructed in support of permit and incentives acceptance.

Energy & Fuels↗
DOE OSTI2023

Clean Energy Employment Impacts and Occupational Analyses: Building Envelope & Electrification Upgrades

Under the Communities LEAP (Local Energy Action Program) Pilot, the U.S. Department of Energy (DOE) is working with a group of LEAP communities to bolster workforce development initiatives and support the growth of local employment in the clean energy economy. Through this resource, DOE seeks to provide participating communities with an overview of the types of occupations that could be affected by investments in building envelope and building electrification upgrades in existing building stock - differentiating between the residential and commercial sectors. This occupational analysis is intended to be used by communities to inform workforce initiatives (e.g., local training and education programs) as they implement building energy efficiency and electrification projects at scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Commercial Vehicle Electrification Evaluation Toolkit (CVEET)

The CVEET can identify and characterize charging and battery capacity challenges for class 3-8 commercial vehicle electrification, including battery electric and plug in hybrid vehicles for various trucks, vans and buses, over a wide range of vehicle operation. The tool can help build the understanding of the impact of commercial vehicle electrification on energy consumption, payload penalty, and GHG (i.e., CO2) emissions. The tool employs a quantitative approach to estimate electric vehicle energy consumption, characterize component performance and determine appropriate charging assumptions to conduct a comprehensive priority analysis of MD/HD vehicle electrification using public domain data.

Gao, Zhiming↗
DOE OSTI2025

NRIC Annual Report FY 2025

The National Reactor Innovation Center (NRIC), established in August 2019, is a national United States (U.S.) Department of Energy (DOE) program. NRIC’s mission is to partner with industry and national laboratories to bridge the gap between concept, demonstration, and commercialization of advanced nuclear technology. NRIC accomplishes this through building or enhancing existing DOE infrastructure to support testing of components and systems that are key to successfully deploying advanced nuclear technology. NRIC’s vision is that by 2028, NRIC will be partnered with industry and accelerating the demonstration and deployment of advanced nuclear technology using DOE national laboratory infrastructure and expertise. NRIC will establish four new experimental facilities and two large reactor test beds for integrated technology demonstrations and experimentation by 2028 and complete two advanced nuclear technology tests by 2030. Achieving this vision will enable urgently needed abundant and affordable clean energy both domestically and internationally. NRIC’s success will inspire our nation and the global community to embrace the promising contribution of innovative nuclear reactor technologies to the clean energy economy and re-establish the U.S. as the global leader in advanced nuclear energy. NRIC is tasked with expediting the development of advanced nuclear energy technologies by bringing together private-sector technology developers and the world-class capabilities of the DOE national laboratory system. Through this program, the U.S. private sector is given access to the physical infrastructure available at DOE national laboratories to test and demonstrate their reactor concepts. NRIC works closely with the DOE-Nuclear Energy (NE) program that grants access to technical, regulatory, and financial support for commercializing nuclear energy. NRIC builds upon these new reactor concepts and technology successes to effectively strengthen U.S. nuclear leadership.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Coaxial color channel focus evaluation to estimate standoff height in directed energy deposition additive manufacturing

Directed energy deposition (DED) is an additive manufacturing process that is being rapidly adopted by industry and is well suited for the fabrication of complex components in a variety of metal alloys. In laser cladding systems such as DED, powder is blown in a stream to a metal substrate coincident with a laser necessary to deposit molten metal with 3D spatial control. The focus of both the laser and the powder stream are crucial, and best deposition occurs at a predetermined standoff height between the build surface and the print head. Generally, no monitoring of this distance is implemented in commercial DED systems. Due to potential over or under building, the standoff height often changes over time but tends to self-correct. However, inexpensive and minimally intrusive methods to identify optimal standoff are required to provide real-time control to maintain the optimal distance. The present work explores the quantification of the focus of the three-color channels of a coaxial camera to determine the standoff height. An experiment was performed in which a 254 mm wall is built and the standoff height, initially 5.0 mm below the optimal position, was then intentionally increased every 25.4 mm of wall length by an amount of 1.0 mm to a final position 7.0 mm above optimal. Computer vision is demonstrated to monitor the amount of focus in each color band and estimate standoff distance. Finally, a response can be calculated in under 40 ms using simple hardware and can work in most laser-based DED systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cost-Benefit Analysis of the 2021 Washington State Energy Code – Commercial Provisions

The state of Washington recently updated their current state commercial energy code, which is the 2018 Washington State Energy Code (2018 WSEC-C) to an updated version named the 2021 WSEC-C. This report assesses the life cycle costs and savings and greenhouse gas emissions impacts of the 2021 WSEC-C compared to the 2018 WSEC-C, as requested by the Washington State Building Code Council (SBCC).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Overview of Building Electrification Technologies and Market Opportunities

This report provides an overview of building electrification drivers and select building electrification technologies and their markets and performance. Covered topics: Building Electrification Drivers and Context; Heat Pumps for Space Conditioning; Heat Pump Market Opportunities; Life Cycle GHG Emissions Impacts of Heat Pump Space Conditioning Technologies; Heat Pump Water Heaters; Electrification of Gas Loads: Commercial and Residential; Residential Panel Capacity; Electric Vehicle Impacts and Connections to Buildings; and Building Envelope Improvements and Thermal Energy Storage (TES) Opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Panel Session 108: Technology Transfer and Commercialization: Innovative Solutions for Global Opportunities

This panel focus was to build the connection between innovative solutions and the various industries looking for more efficient methods, products, and processes in Tech Transfer and Commercialization. This panel had interest across the entire conference base, whether they are encountering a challenge, introducing an innovative solution, or are the host that is trying to get from a pure research / Research, Development, Demonstration, Testing, and Evaluation solution to one that is commercially viable and robust enough for long term and/or high risk deployment scenarios and which will support greater chance of success and positive outcomes. Panelists with presentations: Practical, Successful Technology Transfer (Laurie Judd); Technology Needs for Clean-up of Mercury Contamination on the Oak Ridge Reservation (Renee Echols); US DOE Office of Technology Transitions (Kyle Wiley); Technology Transfer in Support of Delivering Clean-up Missions (Kristan Schruder); Mission to Market (J. Chris Ford)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Test of a Novel, Commercial-Scale Wave Energy Direct-Drive Rotary Power Take-Off at the NREL National Wind Technology Center (CRADA CRD-14-571 Final Report)

The National Renewable Energy Laboratory (NREL) will work with Columbia Power Technologies [C-Power] to support work under US DOE DE-EE-0006399, “Build and Test of a Novel, Commercial-Scale Wave Energy Direct-Drive Rotary Power Take-Off Under Realistic Open-Ocean Conditions.” Work will include a review of their design for a novel wave energy direct drive generator. After review, the system will be prototyped and tested in the NREL National Wind Technology Center (NWTC) 5MW dynamometer and data will be recorded and analyzed. Conclusions from data analysis will be used to improve the design prior to completing a version of the system for ocean deployment. Additionally, NREL will work with Columbia Power Technologies [C-Power] to quantify the system levelized cost of energy (LCOE) and analyze the system in agreement with US DOE System Performance Advancement (SPA) goals 1 and 2.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Low Carbon Technology Strategies: Large Office

This document includes steps that building owners and operators can implement to achieve smart, healthy, and low-carbon large office buildings within their existing building portfolios. Large offices are typically over 50,000 square feet and often include complex heating and cooling systems.

analytics↗
DOE OSTI2023

Lighting and visual comfort performance of commercially available tubular daylight devices

Tubular daylight devices (TDDs) require a much smaller roof opening than conventional skylights and, because of their highly reflective tube, they can deliver daylight farther away from the building envelope. This can provide lighting energy savings, increasing resilience in new and existing buildings. Different types and configurations are available amongst commercially available TDDs, including domes/diffusers with varying optical properties and the diameter of the TDD. This paper presents a comprehensive experimental evaluation of the lighting and visual comfort performance of multiple configurations of commercially available TDDs, varying dome type (prismatic and clear), diffuser type (Fresnel and prismatic), and diameter (53 and 35 cm), under a range of environmental conditions (different times of day/year, sky cover). Based on illuminance measurements, estimated lighting energy use is also presented. Results indicate that, for clear sky, light levels increase and energy use decreases with solar altitude (e.g., 16 Wh/m 2 daily energy use intensity on a high maximum daily solar altitude (MDSA) day and 34 Wh/m 2 on a low MDSA day) and TDD diameter (e.g., 34 Wh/m 2 and 69 Wh/m 2 for 53 cm and 35 cm TDDs, respectively, for low MDSA). The daily illuminance profile is more rounded for prismatic domes and has higher peaks for clear domes; this translates into a somewhat higher average daily useful daylight illuminance (DUDI) for prismatic domes (86 %) when compared to clear domes (80 %). No clear impact of diffuser type was apparent. In conclusion, measurements indicated no discomfort glare for any of the conditions tested.

14 SOLAR ENERGY↗
DOE OSTI2026

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗
DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Managing Subsurface Pressure Buildup and Interference in Commercial-Scale CO 2 Storage Project with Proximal Injection Wells

Large-scale decarbonization using carbon capture and storage (CCS) is likely to involve many commercial-scale CO 2 storage projects located in close proximity to each other. This close proximity raises concerns over pressure interference among the storage projects. Pressure interference between injection and storage efforts can reduce the practicable CO 2 storage resource and force wells to inject CO 2 at a lower rate to avoid the fracture pressure thresholds per United States Environmental Protection Agency (EPA) Class VI well regulations to preserve injection and confining zone integrity and potentially mitigate against inducing seismic activity. These analyses employ numerical full-physics reservoir modeling to evaluate how pressure buildup fronts and CO 2 plumes evolve under commercial-scale injection volumes of CO 2 in which multiple storage sites located in close proximity occur in tandem. The simulation models mimic injection at pseudo basin-scale and assume homogeneous saline formation(s) as storage targets with a pair of upper and lower homogeneous seal layer/s. These analyses specifically investigate the efficacy of two basin-wide reservoir pressure management strategies in addressing the technical challenges associated with pressure buildup and CO 2 plume commingling. The strategies explored include: 1) enlarging the area of injection well spacing (WS) and 2) storing CO 2 in a stacked sequence (SSS) of saline formations compared to a single formation. The storage and confining zones properties assumed were held common across the scenarios, unless specified otherwise. Analyses results show that after injecting 4 million tons per year for 30 years using 4 separate wells (each injecting 1 million metric tons per year), the radius of CO 2 plume extends to a mere 3 km or less from injection wells. Meanwhile, the radius of pressure buildup ranges on the order of tens to a few hundreds of kilometers, depending on the magnitude of pressure buildup threshold that one would use to define the front. CO 2 plume commingling from different injection wells appears to occur 50 years post-injection, especially under scenarios with narrowly spaced (i.e., < 5 km apart) injection well locations. Findings from sensitivity cases on the well spacing suggest that storage formations modeled would require different well spacing to avoid fracture pressure thresholds. For instance, modeled storage formations with high fracture gradients (i.e., 0.8 psi/ft) would need less than 5–km well spacing, whereas those with lower fracture gradients (i.e., 0.7 psi/ft) would need approximately 20–km well spacing, based on assumed modeling parameters. Under stacked injection, the pressure challenges (described above) still exist but are more alleviated due to distributing the same injection volume across more available reservoir volume. These analyses demonstrate that stacked-sequence storage can effectively address the challenges, while still providing the same target CO 2 storage volumes and allowing a large number of storage projects to be deployed in the same basin by better utilizing the available storage resource across different reservoir depths. Among cases modeled, the resulting pressure buildup front is most suppressed when each storage project distributes injection volumes over several wells, each of which injects a portion of the total CO 2 across the stacked sequence. This strategy results in the smallest CO 2 aerial footprint amongst scenarios evaluated but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 42 percent compared to the commercial-scale single-formation storage), the result of which is crucial to maintain caprock integrity. The findings presented by this research draw attention to the importance of greater coordination among storage operators and regulatory stakeholders to foster the upscaling and deployment of CCS. These analyses provide insights into required decision-making when considering multi-project deployment in a shared basin. Because these analyses evaluate a very specific geologic situation, they bear further investigations across other geologic situations.

42 ENGINEERING↗
DOE OSTI2024

ANSI/ASHRAE/IES Standard 90.1-2022 Performance Rating Method Reference Manual

This document is intended to be a reference manual for the Appendix G Performance Rating Method (PRM) of ANSI/ASHRAE/IES Standard 90.1-2022 (Standard 90.1-2022). The PRM can be used to demonstrate compliance with the standard and to rate the energy efficiency of commercial and high-rise residential buildings with designs that exceed the requirements of Standard 90.1. Use of the PRM for demonstrating compliance with Standard 90.1 was a new feature of ANSI/ASHRAE/IES Standard 90.1-2016 (Standard 90.1-2016). The procedures and processes described in the PRM reference manual (PRM-RM) are designed to provide consistency and accuracy by filling in gaps and providing additional details needed by users of the PRM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

ANSI/ASHRAE/IES Standard 90.1-2019 Performance Rating Method Reference Manual

This document is intended to be a reference manual for the Appendix G Performance Rating Method (PRM) of ANSI/ASHRAE/IES Standard 90.1-2019 (Standard 90.1-2019). The PRM can be used to demonstrate compliance with the standard and to rate the energy efficiency of commercial and high-rise residential buildings with designs that exceed the requirements of Standard 90.1. Use of the PRM for demonstrating compliance with Standard 90.1 was a new feature of ANSI/ASHRAE/IES Standard 90.1-2016 (Standard 90.1-2016). The procedures and processes described in the PRM reference manual (PRM-RM) are designed to provide consistency and accuracy by filling in gaps and providing additional details needed by users of the PRM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗