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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Performance and Costs of Ductless Heat Pumps in Marine-Climate High-Performance Homes Habitat for Humanity The Woods

The Washington State University (WSU) Energy Program's Building America (BA) team conducted a case study of a high-performance affordable housing community: The Woods (Figure 1). This BA effort is part of a larger-scale study of 30 homes funded from 2013-2016 by Tacoma Public Utilities (TPU) and the Bonneville Power Administration. The Woods is a Habitat for Humanity (HFH) community of homes certified by ENERGY STAR Homes Northwest (ESHNW); the community is in the marine climate of Tacoma/Pierce County, Washington. This research report builds on an earlier preliminary draft 2014 BA report and includes significant billing analysis and cost-effectiveness research from a collaborative and ongoing DHP research effort for TPU and the Bonneville Power Administration. This final BA report focuses on the results of field testing, modeling, and monitoring of ductless mini-split heat pump hybrid heating systems in seven homes built and first occupied at various times between September 2013 and October 2014. The report also provides WSU documentation of high-performance home observations, lessons learned, and stakeholder recommendations for builders of affordable high-performance housing. The research goal of the U.S. Department of Energy's BA research team Building America Partnership for Improved Residential Construction was to compare a ductless heat pump (DHP) hybrid system (DHP in common area/electric resistance [ER] in bedrooms) to an all-electric zonal ER system in high-performance single-family affordable housing. This effort included assessing the costs and benefits of a DHP/ER hybrid system located in the main living area to offset the primary heating demand of zonal ER heaters in the bedroom zones and comparing these findings to data from of new affordable single-family housing in Washington State. This report includes: (1) Measured indoor and outdoor temperatures and relative humidity (RH) in the homes. (2) Field testing results of heating, ventilating, and air-conditioning equipment; ventilation system airflows; building envelope tightness; lighting, appliance, and other input data required for preliminary Building Energy Optimization (BEopt) modeling; and ENERGY STAR field verification (3) BEopt modeling results compared to measured energy use. (4) A comparison of the space heat energy consumption of a DHP/ER hybrid heating system and a traditional zonal ER heating system installed in the same home. This comparison is made by implementing a series of weekly "flip-flop tests" (referred to here as "switchback" tests per TPU) to compare space heating, temperature, and RH in zonal ER heating mode with a DHP/ER mode as discussed in the Building America Test Plan (Lubliner 2010a). (5) Cost data from HFH and other sources related to building efficiency measures focusing on the DHP/ER hybrid heating system. (6) An evaluation of the thermal performance and cost benefit of DHP/ER hybrid heating systems in these high-performance homes employing life cycle cost analysis for energy code policy and monthly cash flow analysis of HFH homeowners. (7) Post-monitoring occupant survey results. The report also provides the following stakeholder findings and recommendations: (1) DHP single-head systems at The Woods are cost-effective to new homebuyers of these high-performance all-electric homes. (2) Stakeholder education is needed on design, inspection, and commissioning; documentation is needed for heat recovery ventilation (HRV) and from ENERGY STAR builders, verifiers, and inspectors to help ensure that the houses meet the goal of "build tight, ventilate right." (3) A code gap in inspection and enforcement was identified that should be addressed by: (3a) Improving the fire marshal's approach to sprinkler attic piping freeze protection; (3b) Improving the maintenance of ceiling insulation continuity; and (3c) Educating the local building inspector on attic insulation inspection concerns that allow for maximizing design improveme...

affordable housing↗
DOE OSTI2023

A Novel Multi-Agent Deep Reinforcement Learning-enabled Distributed Power Allocation Scheme for mmWave Cellular Networks

We consider the power allocation problem over shared spectrum for millimeter-Wave (mmWave) cellular downlink. Existing approaches usually find sub-optimal solutions by solving a non-convex optimization which leads to scalability issues due to centralized control. Therefore, distributed and adaptive approaches are desirable. Recently, model-free Deep Reinforcement Learning (DRL) has achieved success in such wireless resource management tasks. By modeling the radio environment as a Markov Decision Process (MDP) with the base stations (BSs) being the agents, power allocation can be automated at the agent level with comparable throughput performance to conventional centralized schemes. The multi-agent setting presents new challenges as the radio environment is impacted by the joint actions of the agents and is no longer stationary from any individual agent’s perspective. Existing literature bypasses this non-stationarity violation by ignoring it which may cause performance degradation. To tackle this issue, we propose a distributed continuous power allocation scheme based on a modified version of multi-agent Deep Deterministic Policy Gradient (MADDPG) that is tailored for the distributed multiple-agent setting. The proposed scheme employs a centralized-training distributed-execution framework where Q-functions are trained over subsets of BSs while each BS determines its transmit power based only on its own local observation. It admits constant per-BS communication and computation complexity and is thus scalable to large networks. Numerical evaluation shows that the proposed scheme adapts well to a wide range of interference conditions and can achieve comparable or better performance than several state-of-the-art non-learning approaches.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

National Aeronautics and Space Administration (NASA) Agency Report WGISS-51

The Committee on Earth Observation Satellites (CEOS) strives to enhance international coordination and data exchange and to optimize societal benefit. CEOS contributes to NASA’s core mission and is critical to NASA’s Earth Science program and to the future of Earth observations community as a whole because it advances mission planning, interagency coordination and technical implementation. Within NASA, the CEOS Working Group on Information System and Services (WGISS) is a forum for the Earth Sciences Data Systems (ESDS) Program to collaborate with other international and domestic agencies in the development of Earth observation data systems and services. NASA leads the development and demonstration of multiple prototypes supporting CEOS and Group on Earth Observations (GEO) requirements. NASA’s participation in WGISS influences NASA’s Earth Observing System Data and Information System’s (EOSDIS) ability to make high-quality data products available to the broad science community both nationally and internationally. Combined with NASA’s free and open data policy, EOSDIS’s involvement in WGISS is essential to widespread use of research satellite measurements. This presentation focuses on an overview and recent status of NASA’s EOSDIS.

Andrew Mitchell↗
NASA NTRSDate not supplied

NASA Agency Report WGISS 52

The Committee on Earth Observation Satellites (CEOS) strives to enhance international coordination and data exchange and to optimize societal benefit. CEOS contributes to NASA’s core mission and is critical to NASA’s Earth Science program and to the future of Earth observations community as a whole because it advances mission planning, interagency coordination and technical implementation. Within NASA, the CEOS Working Group on Information System and Services (WGISS) is a forum for the Earth Sciences Data Systems (ESDS) Program to collaborate with other international and domestic agencies in the development of Earth observation data systems and services. NASA leads the development and demonstration of multiple prototypes supporting CEOS and Group on Earth Observations (GEO) requirements. NASA’s participation in WGISS influences NASA’s Earth Observing System Data and Information System’s (EOSDIS) ability to make high-quality data products available to the broad science community both nationally and internationally. Combined with NASA’s free and open data policy, EOSDIS’s involvement in WGISS is essential to widespread use of research satellite measurements. This presentation focuses on an overview and recent status of NASA’s EOSDIS.

Andrew Mitchell↗
NASA NTRSDate not supplied

CEOS Enabling Open Science via Science Data Systems

The Committee on Earth Observation Satellites (CEOS) strives to enhance international coordination and data exchange and to optimize societal benefit. CEOS contributes to NASA’s core mission and is critical to NASA’s Earth Science program and to the future of Earth observations community as a whole because it advances mission planning, interagency coordination and technical implementation. Within NASA, the CEOS Working Group on Information System and Services (WGISS) is a forum for the Earth Sciences Data Systems (ESDS) Program to collaborate with other international and domestic agencies in the development of Earth observation data systems and services. NASA leads the development and demonstration of multiple prototypes supporting CEOS and Group on Earth Observations (GEO) requirements. NASA’s participation in WGISS influences NASA’s Earth Observing System Data and Information System’s (EOSDIS) ability to make high-quality data products available to the broad science community both nationally and internationally. Combined with NASA’s free and open data policy, EOSDIS’s involvement in WGISS is essential to widespread use of research satellite measurements. This presentation focuses on an overview and recent status of NASA’s EOSDIS.

Diane Davies↗
DOE OSTI2016

Fleet DNA

Available online at www.nrel.gov/fleetdna, the Fleet DNA clearinghouse of commercial fleet vehicle operating data helps manufacturers and developers optimize vehicle designs and helps fleet managers choose advanced technologies for their fleets. Sponsored by the U.S. Department of Energy, this online tool provides data summaries and visualizations similar to real-world genetics for medium- and heavy-duty commercial fleet vehicles operating in a variety of vocations. If you use Fleet DNA data in a publication, please notify NREL at fleetdna@nrel.gov and include a citation consistent with the following format: “Fleet DNA Project Data.” ([YEAR]). National Renewable Energy Laboratory. Accessed [DATE]: www.nrel.gov/fleetdna.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Complete Evaluation on Advanced Reactor Machine Learning Subversion Attacks (Final)

Navigating through the world of Artificial Intelligence (AI) in nuclear reactors and their Instrumentation and Control (I&C) systems demands a careful, deliberate journey. AI’s capability to manage massive datasets and streamline control systems has indeed carved out a significant role in various sectors, including nuclear energy. However, while AI, and particularly Large Language Models (LLMs), bring a lot to the table in terms of operational efficiency and anomaly detection, they also expose the sector to a new breed of cybersecurity threats, like Inference Attacks, Adversarial Attacks, and Trojan Attacks. This guide is designed to be a straightforward manual, diving deep into the intertwining worlds of AI and cybersecurity within nuclear reactors, and tailoring insights for three crucial audiences: I&C Vendors/Developers, Nuclear Regulators, and Nuclear Reactor Operators and Cyber Defense Teams. (1) Section 2, directed at I&C Vendors/Developers, will provide a clear and focused look at several cybersecurity attacks, offering practical recommendations and detailed scenarios related to AI cybersecurity. This section isn’t just about identifying problems but also about giving solid, usable solutions. (2) Section 3, meant for Nuclear Regulators, gets straight to the point about regulations, policy suggestions, and guidelines that are needed to lay down a robust, secure, and ethical foundation for the application of AI in nuclear operations. The focus is on making sure that everything adheres to international standards and laws while being practicable and clear-cut. (3) Section 4, aimed at Nuclear Reactor Operators and Cyber Defense Teams, offers an exhaustive exploration and technical reports, with clear recommendations and scenario analyses vital to protect operational environments and guarantee the secure application of AI in nuclear reactor operations. The goal is simple: as we step into an era where AI becomes a fundamental element of our technological and energy infrastructures, this guide is here to act as a clear, direct handbook, ensuring that AI is implemented within the nuclear sector in a manner that is secure, responsible, and practical. It’s about striking a balance – optimizing the undeniable benefits offered by AI while securing and shielding against potential cyber threats as we move through this new and complex landscape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Resource Adequacy in Electricity Markets With Renewable Energy

This paper presents a market-based resource adequacy assessment framework to analyze the system generation portfolio that results in a competitive market environment. In particular, we apply the modeling framework to investigate the impact of high penetration levels of variable renewable energy resources and different market designs on achieving resource adequacy. The model captures the strategic capacity investment and retirement decision-making of profit-maximizing generation companies. In contrast to many previous studies, this paper considers markets for capacity, energy, and reserve products in detail; thus, the modeling framework allows improved analysis of generation expansion and revenue sufficiency in a competitive market environment. The modeling framework is based on Stackelberg leader-follower games and is formulated as a bi-level optimization problem, which is then transformed into a mathematical program with equilibrium constraints. Furthermore, we employ a Lagrangian decomposition algorithm to enhance computational performance. In a case study of the electric reliability council of texas (ERCOT) system, we compare the results from the proposed model with those obtained from a traditional centralized least-cost planning model. Finally, the results demonstrate the effectiveness of the proposed modeling framework and highlight the importance of considering strategic behavior in a competitive market framework when assessing resource adequacy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Summary Report on Synthetic Time History Development and Deployment

This report summarizes research work performed at the Colorado School of Mines (CSM) and George Washington University (GWU) in support of the DOE Office of Nuclear Energy Integrated Energy Systems (IES) program. In particular, the work focuses on improving and strengthening two fundamental steps in the mathematical and computational framework that is currently being developed to optimize the economic performance of Integrated Energy Systems. One of the innovative approaches taken by the IES program is that, rather than optimizing the system for a specific year or week or day, the optimization is performed using stochastic synthetic data. Synthetic data is generated by training artificial intelligence (AI) using available but limited data sets. The synthetic data should possess the same patterns as the original set and the same statistical properties, but never repeat the same set of values exactly. The work from CSM focuses on this first step; namely, investigating a methodology to determine the quality of the synthetic data and the right settings for properly training the AI. Once a large set of trustworthy data can be generated the problem of stochastic optimization can be tackled. The optimal IES configuration is highly dependent on the rare high peaks or deep depths of the net demand (grid electricity demand less variable renewable energy [VRE] production). Using an unbiased random sampling of the synthetic data, these extremes are very difficult to generate and therefore the optimization can be unrepresentative and inaccurate. GWU has started an approach to increase the likelihood of generating these rare events with the proper associated probabilistic weight. Both of these projects represent a step forward in achieving the capability to properly size the IESs and to properly capture the value that these systems can provide to the grid by absorbing volatility of net demand without disproportionately increasing the cost of maintaining grid reliability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Scale effects on core design, fuel costs, and spent fuel volume of pressurized water reactors

The desire to improve the economic competitiveness and deployment pace of nuclear energy through modularization, manufacturing, and series production had led to the development of smaller size reactors. As the standard 17x17 fuel technology is mainly maintained in the pressurized water reactors (PWRs) category, this translates into a lower number of fuel assemblies in the core and sometimes a reduced fuel height. To assess the impact of such scale change in core design on fuel cycle cost and spent fuel volume, a scoping analysis tool is developed based on infinite lattice calculations, leakage, fuel management reduced models, and levelized unit cost of electricity (LCOE) estimate. As such, cost dynamics driven by fuel specific power, burnup, core leakage, feed, cycle length, fuel assembly height as well as uranium market data are captured with consistent set of assumptions and analysis methods. A selection of 5 reactor designs representative of leading PWR developers is assessed and compared. Pursuing higher specific powers and optimal burnups are highlighted as the main fuel cost reduction drivers, nevertheless, practical limitations and opportunities must be evaluated to establish the feasibility of such enhanced fuel operation. In consequence, a detailed core design is performed using SIMULATE3 code for 5 PWR variations including natural and forced coolant circulation modes, two reactor scales, power densities of 73, 112, and 123 kW/l and higher discharge burnups. Design and optimization are performed at the lattice level, for the reflector, and at the core loading level. Satisfactory steady-state operation including power distribution, coolant operating limits, and reactivity requirements are analyzed and reported in this paper. The fuel economics of the detailed core designs confirm the scoping analysis findings. Despite the unlocked power uprates in small PWRs, the achievable burnup for a given fuel specific power requires more enrichment and shorter fuel height results in higher fabrication costs per mass of fuel, which makes scaling down core size a more expensive endeavor on the fuel cycle front. Spent fuel volumes are reported for the PWRs designed in this paper. Furthermore, these volumes are driven by the core average discharge burnup regardless of the scale in consideration. Additional cost and core performance aspects related to heavy reflector gains, fuel-reflector substitution, and disposal cost policy in the U.S. are examined.

42 ENGINEERING↗
DOE OSTI2020

Anaerobic Storage and Conversion of Microalgal Biomass to Manage Seasonal Variation in Cultivation

Seasonal variation in microalgal biomass production is a well-known challenge when optimizing economics for algal fuel conversion, especially given the fluctuation in biomass production between winter and summer. Wet storage offers significant potential for cost and energy savings compared to dewatering and dry storage. This study demonstrates the feasibility of preserving harvested Scenedesmus acutus biomass through wet anaerobic storage for use in biochemical conversion. Anaerobic storage effectively preserved biomass with minimal degradation of carbohydrates and preservation of lipids and proteins. Screening experiments identified optimal pretreatment conditions for stored biomass. Scale-up of pretreatment enabled fermentation of the hydrolysate to butyric acid and indicated no observable difference in conversion between unstored and stored biomass. Lipid extraction improved by a relative 12% for stored biomass. These results suggest that wet anaerobic storage can effectively manage seasonal variation in biomass production and is compatible with biochemical approaches for biofuel production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2019

Integrated Commercial Carbon Capture and Storage (CCS) Prefeasibility Study at Rock Springs Uplift, Wyoming (Final Report)

To establish the potential of safe, long-term commercial-scale carbon capture & storage (CCS) in southwestern Wyoming, the University of Wyoming formed a CCS coordination team (CCT) to complete a Phase I CarbonSAFE pre-feasibility study adjacent to the region’s largest coal-fired power plant, the Jim Bridger Plant (JBP). The study’s primary objective was to evaluate the potential of storing 50+ million metric tons of anthropogenic carbon dioxide (CO 2 ) in stacked reservoirs over a period of 25 years. In addition, this integrated study evaluated related aspects of carbon capture utilization & storage (CCUS) at the study site, including: (1) the CO 2 character of post-combustion flue gas from JBP and the technical capacity for retrofitting proven commercial-scale CO 2 capture technology relative to CO 2 source character and technological constraints; (2) utilization of the existing CO 2 pipeline network in the immediate vicinity of JBP for enhanced oil recovery (CO 2 -EOR) and utilizing that network as part of a regional hub for CO 2 storage from other anthropogenic sources; (3) assessment of the challenges and benefits of meeting all of CarbonSAFE programmatic Phase I goals relative to Wyoming’s carbon management regulatory framework; and (4) assessment of the community and environmental factors that may impact CCS at JBP. With respect to storage, we analyzed the potential of stacked Mesozoic reservoirs at the study site, focusing on the Entrada and Nugget sandstones. The reservoir response to injection simulations varied greatly between formations, though they both were capable of CO 2 storage. The Entrada Sandstone is relative thin (~40’) and heterogeneous; storage using one injection and production well was limited to 1.2 Mt over 25 years at the study site. The Nugget Sandstone is much thicker (> 400’) and generally homogeneous; storage using one injection and production well approached 15.0 Mt over 25 years; this scenario suggests that the storage potential in the Nugget Sandstone is close to the estimated P90 calculation of 9.6 Mt/mi 2 as models indicate a storage potential of 8.3 Mt/mi 2 at saturation. Both reservoirs’ storage capacity benefited greatly from coupling an injection well with an offset production well; total storage capacity increased and reservoir pressure stayed below critical thresholds. This indicates that implementing a pressure management strategy at the study site would optimize storage and decrease risk. Seals associated with the targeted reservoirs were shown to be capable of retaining the potential storage volumes, and the site benefits from multiple seal redundancies (i.e. > 7,000’ of seal formations). Furthermore, assessment of different reservoir variables (e.g., fluid composition, pressure, etc.) indicates all reservoirs at the study site are isolated. Storage assessments from Mesozoic reservoirs were coupled with simulations from the site’s Paleozoic reservoirs (the Weber Sandstone and Madison Limestone), which were the focus of previous study. The fully integrated stacked reservoir pre-feasibility studies suggest that the Nugget and Madison formations alone could safely store 50 million metric tons of CO 2 within the study site. Furthermore, both formations are true saline reservoirs near JBP, making them ideal target reservoirs for CO 2 sequestration. Analysis of Wyoming’s laws and regulations confirm that the State has a favorable policy environment for CCS/CCUS. The project’s economic models estimated that the following revenues collectively are sufficient to finance the project over its lifespan if CO 2 utilization is coupled with CCS via the following strategies: (1) sales of CO 2 for EOR (approximately $69 million/year); (2) use of CO 2 tax credits such as amended §45Q and §48A (approximately $484 million total); and (3) sales of low-carbon electricity and marketable carbon offset/credits into carbon-constrained markets (approximately $11-$17 million/year) to West Coast consumers. These revenue estimates are broadly consistent with other studies that concluded arbitrage in JBP retail electricity sales between California and Wyoming could help to support the cost of deploying CCS at JBP. The models also indicate that maintaining a successful business case for long-term CCS -- wherein associated capture, transportation and operational costs are fully addressed at JBP -- is reliant on numerous external factors that complicate predictions. This study suggests that this site meets the CarbonSAFE program’s requirements of being able to feasibly store 50+ million metric tons of CO 2 over 25 years within the site’s stacked reservoirs, especially if coupled with pressure management strategies. This study suggests that the Nugget Sandstone and the Madison Limestone are two of the best reservoirs in the State with respect to overall storage capacity. In addition, the site’s proximity to existing CO 2 transportation networks, CO 2 -EOR opportunities, ability to sell to markets that value low-carbon electricity, Wyoming’s existing carbon regulatory framework, and a public that is well-educated with respect to energy markets and issues collectively increase the potential for implementing commercial-scale CCS adjacent to the JBP. With respect to the available technical and non-technical site data, and the reservoir quality at the study site, we suggest that this site is capable of moving directly into Phase III of the CarbonSAFE program.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Initial Thermal Energy Yield Potential for the Use of Concentrating Solar Power (CSP) for Coal Hybridization in India

The hybridization of concentrating solar power (CSP) with coal-based power generation in India may serve to mitigate fossil fuel use externalities. Assuming parabolic trough systems without storage, this report estimates the upper bound on thermal energy production from India's solar resource to be 633,000 terawatt-thermal (TW th ) annually. Moreover, considering land characteristic constraints, contiguous solar fields (SF) area limitations, and existing coal plant proximity, we produce technical potential estimates. Within 1,000 meters (m) of suitable coal plants, we find the average capacity factor to be 21.1% and the potential for 102,555 gigawatt-hours thermal (GWh th ) aggregated from 25 megawatt thermal (MW th ) CSP SFs. Only about 10% of the land within 1,000 m of each existing coal plant is anticipated to be suitable for hybridization development, and on average this land is expected to support a 43 MW th SF that yields 81 GWh th annually. Chhattisgarh and Tamil Nadu are particularly suited to CSP-coal hybridization and the abundance of suitable land in these states would allow SFs to provide 129 GWh th annually to each coal plant on average. Future research will assess the financial viability of hybridization and explore coal plant optimization strategies that integrate CSP-derived heat (e.g. feedwater heating or potentially coal drying).This study shows significant CSP-coal hybridisation potential for the existing coal plants in India. This preliminary study suggests CSP-coal hybridization may play a supporting role in India's energy system, but it's future is still largely uncertain. This is an area of considerable interest in India, and the methodology could also be adapted for other areas of the world like the United States.

14 SOLAR ENERGY↗
DOE OSTI2026

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Value of Demand Response: Quantities from Production Cost Modeling (Presentation)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗