Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “demand”

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 649 records · Page 36

Vertical meteorological patterns and their impact on the energy demand of tall buildings

In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Finally, guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An energy storage dispatch optimization for demand-side management in industrial facilities

An energy storage (ES) dispatch optimization was implemented to test lithium-ion battery ES, supercapacitor ES, and compressed air ES on two different industrial facilities – one intermittent process facility and one continuous process facility. The model first shows the capability of optimizing the size of a single technology on a single industrial facility to maximize the return on investment. Then, for the same profile, the model identifies significant differences in the optimal size for different technologies based on their performance parameters. Third, the model identifies differences in the optimal size for each technology based on the facilities profile. Here the results show compressed air ES yields the highest return on investment for both facilities and provides insight for future development of ES systems.

25 ENERGY STORAGE↗

H2@Scale Hydrogen Economic Potential Supply and Demand Locations

This data release provides estimates of hydrogens economic potential for possible hydrogen applications and production technologies by geographic location for various scenarios, as described in "The Technical and Economic Potential of the H2@Scale Concept within the United States". We define the economic potential as the quantity of hydrogen at an equilibrium price at which suppliers are willing to sell and consumers are willing to buy the same quantity of hydrogen.

alternative energy↗

dGen (Distributed Generation Market Demand) Model Data: Alpha Release

Open sourced data needed to run the basic alpha release version of the dGen model. Includes a pre-generated agent file of 100,000 agents in pickle file format along with the base schema and table data in parquet format that are needed to create a postgreSQL database for the model to interact with.

14 SOLAR ENERGY↗

Integrated Demand Management Findings from March 2018 Simulation: Demonstrating Benefits of Submitting Multiple Trajectory Options

This presentation provides a summary of August 2017 Newark airport simulation, with focus on impact of varying Trajectory Options Set (TOS) "participation levels" (i.e., the percentage of flights that submit TOSs), as well as the results from March 2018 LaGuardia simulation with Flow Evaluation Team, which focused on benefits to individual carriers of participation. During the study, we demonstrated that both the participating and non-participating airlines benefited when TOSs but that the participating airlines benefited most and the improvement seen by participants was greatest when overall participation was lower.

New York↗

Demand-Capacity Balancing Algorithms for Urban Air Mobility Operations

This paper proposes new Demand/Capacity Balancing (DCB) algorithms that resolve imbalances at enroute waypoints, such as crossing, merging, and UAM corridor entry or exit waypoints, in addition to vertiports; we refer to this algorithm as DCB-Waypoint, still using pre-departure delay as the sole resolution mechanism. Like DCB-Vertiport, DCB-Waypoint takes one flight at a time and resolves imbalances one waypoint at a time, starting from the origin vertiport followed by the sequence of constrained waypoints and, finally, the destination vertiport. The next advancement assigns airborne delays, in addition to pre-departure delays at vertiports. This algorithm, called DCB-Airborne-Delays, uses information on flight speeds to ensure that the assigned delays are feasible, meaning that variations in flight speeds are within feasible aircraft speed ranges. The proposed algorithms are being implemented in a new fast-time simulation tool developed especially for simulating UAM operations. The full paper will provide additional details of the new DCB algorithms that have been developed, as well as the results from simulations using these algorithms. Finally, the DCB algorithms will be compared against one another to obtain insights and recommendations for the future development of more advanced DCB algorithms.

urban air mobility, demand-capacity balancing↗