FEDS can be run on a machine connected to a network. In some circumstances FEDS can even be run remotely from a network computer or file share. However, because each network is different and interference and connectivity issues are possible, for the best performance (and to lower the risk of problems) it is recommended to run FEDS from a local machine.
Custom EPW files may be created by experienced users and imported using the "Import EPW File" option. There is also an option in FEDS version 8 that allows users to view and alter the weather data (e.g., drybulb temperature, relative humidity, atmospheric pressure, and sky clearness). This is presently intended to allow users to make weather adjustments to be used when calibrating a model to conditions for a specific base year. Contact FEDS support for more information.
Yes. FEDS now provides an option to import additional weather station data. An "Import EPW Weather File" feature enables users to access the growing number of weather station data representing many locations globally, as well as more recent records of typical climate data, and even data covering specific time periods or energy modeling scenarios. All data must be in standard EPW file format. Refer to the FEDS User’s Guide for more information.
Sometimes when the system or software crashes, certain files are locked in the system's memory which can cause strange or unstable behavior upon restarting. If this occurs, try quitting FEDS and restarting again. When closed properly, FEDS will tidy up the system resources and work properly the next time it is run.
No. FEDS infers parameters based on the most likely current condition of a building and its equipment. Inferences for an 1820 vintage building will reflect the typical improvements and upgrades that have occurred over time.
The best way to check the accuracy of a model is to run FEDS without optimization and compare the annual consumption estimated by FEDS to actual metered data. To do this, go to "Exclude Building Sets" from the "Optimization" option on the "Simulation" screen. Make sure the "Pick Building Sets" method is selected then press the "Select All" button on the left side of the screen (under the list of building sets). After saving, go back and run FEDS. This will take from a few seconds to a couple minutes for FEDS to run the baseline load and consumption calculations for the buildings. Alternatively, running with the analysis type set to "Calibration" will accomplish the same thing. Once complete, review the *.txs report for the case and check the following data:
General case and building inputs on the first five pages (for any obvious input errors)
Energy consumption data by fuel type (page 7)
Electric peak demand value and time of occurrence (page 8)
Annual energy consumption by fuel type and end use (page 10)
Do not expect these to be identical to the metered data—this is a model representation of your buildings and even if extremely precise, will vary due to discrepancies related to actual vs. average weather, human behavior, and more. Therefore, achieving consumption values from FEDS that are within 10-15% of actual values suggests a reasonably accurate model. An experienced user who is knowledgeable about building energy systems and their interactions can successfully calibrate to a much tighter tolerance.
If the building is newer than the rated life of the equipment in question, then the remaining life is equal to the difference of rated life and building age. If the building is older than the equipment's rated life, FEDS assumes that on average, equipment will be halfway through their life (but users can override this assumption and specify actual equipment vintage). Rated lives vary by equipment technology. Some examples of rated lives used in FEDS are:
envelope components (windows, insulation, etc.) – 40 years
lights – typically 25 years (Although the cost of replacing lamps and ballasts is figured into the analysis based on specific replacement intervals and hours of operation)
boilers – 40 years
furnaces – 20 years
chillers – 20 years
package AC units – 15 years
heat pumps – Air Source/15 years, Ground-Coupled/20 years
motors – 15 years
hot water heaters – electric, 12 years; gas, 10 years; distributed heat pump, 12 years; central heat pump, 15 years
A useful rule of thumb is that a full FEDS optimization run will take a couple minutes per building set. However, run-time depends on a number of factors, including computing resources, processor speed, size, and complexity of the case. The more buildings, use areas, and technologies being analyzed, the longer the FEDS run will take. Additionally, the presence and number of central energy plants and thermal loops will also impact run-time.
Conversely, a calibration run of the same case and computer takes only a few seconds (with additional time to generate the reports). This is because all building sets are excluded from optimization to help focus on the baseline energy results and aid in focusing on model quality assurance and calibration processes.
Installing FEDS will require approximately 1.7 GB of hard disk space. It is also important to have enough free disk space for case files. We recommend another 10-30 MB for this depending on the number and size of site models.
Choose a weather station that most closely represents the weather at your location. Most times it will be a city in the same state as you, but can be in a neighboring state, or in some instances in another region altogether. When specifying the zip code of the site or building(s), FEDS will recommend a weather station that offers the most similar weather to your location.
FEDS contains a built-in database of building survey data and is able to infer a number of building parameters based on the small set of required inputs provided by the user. For example, FEDS uses information such as building type, location, floor area, and vintage to determine the most likely construction type and geometry. It uses similar information along with heating fuel type and cooling equipment, to determine the most likely heating technology and ventilation system parameters for a building. All inferences enable a user to model buildings without having intimate knowledge of the detailed engineering parameters. The resulting building prototype parameter values are statistically the most likely values based on the limited set of information provided. Of course, all inferred data may be easily overwritten by simply entering (locking) a value in the user interface screens.
inking two distinct building sets together allows greater flexibility in modeling complex building geometries or uses. Linked buildings are designed to model two buildings that share a common wall or are stacked on top of one another. Specifying that the buildings are linked directs FEDS to automatically (based on the geometry information for each building) determine the wall area (or roof/ceiling area) that is shared, and thus not exposed to exterior conditions. It essentially calculates the portion of each buildings shell that is an adiabatic surface (i.e., does not experience conductive heat transfer) and does not receive solar gains. It uses this information in load calculations to appropriately account for the impact of the buildings being connected. There are some rules, however, that must be satisfied in order to link building sets. First, both sets must contain the same number of buildings so that a direct one-to-one linking is achieved. Second, both sets must have the solar normalization turned off (calculate solar gains by facing direction). Also, FEDS currently does not model cantilevered buildings so for top/bottom linking, the N/S and E/W lengths of the top building must not be greater than the corresponding lengths of the bottom building.
FEDS draws upon a number of sources to determine inferable parameter values. Major sources include national building energy consumption surveys such as the Commercial Buildings Energy Consumption, Residential Energy Consumption Survey, large end-use studies such as the End-Use Load and Consumer Assessment Program, ASHRAE handbooks, building and equipment codes and standards, and manufacturers' data and extensive building audit and evaluation experience.
The blue arrows indicate inputs that are required for FEDS to run. If any of these cells do not have a value provided, FEDS will not be able to run and will produce an alert either upon saving a screen or updating inferences. Once a valid input value has been provided and saved, the blue arrow will disappear.
The lock symbol that appears next to many of the input cells indicates the value is inferable by FEDS and does not require an input. An open lock icon means the value is not locked and may be changed by FEDS when inferences are updated. The closed lock symbol represents inputs whose value is locked and protected from being changed when inferences are updated. A user may lock a value by either entering a value into one of these cells, or by clicking on an open lock symbol to lock the value that is currently present in the cell.
Input cells that do not have an icon next to them are for values not absolutely required for FEDS to run but are highly recommended. Values, such as the fuel price data and occupancy hours are extremely important (yet a value may not be required for each fuel or day type). Others, such as the energy consumption inputs and building/technology identifications, are not used by FEDS except for reporting and aiding the user in understanding the output.
A locked value, in terms of FEDS inputs, is one that the user has entered for an inferable parameter. This indicates to the model that this is a user-entered value and should not be updated (inferred). Clicking on the lock symbol can also lock a currently inferred value. When a value is locked, the lock icon will appear as a latched or closed lock. To unlock a value, simply click the icon again, changing it to an open or unlatched lock. This value will now be inferred the next time inferences are run.
In FEDS MBtu signifies Million British Thermal Units. Throughout the program, the 'M' prefix represents million or 106 (MW, MBtu), while 'k' represents thousand or 103 (kWh, kBtu).
Prototype buildings in FEDS are modeled as basic rectangular blocks, with the actual geometry calculated based on the total floor area, number of floors, floor-to-floor height, and aspect ratio. However, additional geometries can be modeled by using the linked building approach or through the advanced geometry inputs, which allow modification to underlying parameters including window/wall/roof/floor areas and conditioned air volumes.
The advanced geometry inputs allow for more flexibility in modeling non-standard building geometries compared to the linked building approach. When accessing the advanced geometry inputs, the user may specify or alter a number of geometric parameters for each zone of the building to customize the resulting model. For example, the exterior wall areas and window areas can be specified for the north, east, south, and west sides of each zone. Additionally, roof, floor, footprint areas, exterior perimeter length, and conditioned air volume can be specified for each zone. These adjustments provide users with the ability to model a number of more complex geometries, such as individual parts of a strip mall complex or varying window fractions for different sides of a building, with greater accuracy than through other means. The option can be accessed via the button on the regular geometry inputs screen.
Solar normalization is used when the orientation of a single building is unknown, does not align with N/S/E/W directions, or when there are multiple buildings of differing orientations in a building set. It can be used to avoid biasing the solar gains calculation by normalizing the exterior wall, window, and roof areas, such that the resultant loads are roughly the average of two buildings: one with an east/west orientation and one with a north/south orientation. FEDS can be set to "ignore facing directions" to use solar normalization.
The aspect ratio is used to define the geometric orientation of the buildings in a building set. It is a ratio of length to width and is calculated by dividing the typical north-facing length by the typical east-facing length.
FEDS now offers 1.116 weather station data locations, primarily from a TMY3 and CWEC sources. From this data it derives such information as heating and cooling design day conditions, hourly temperature, clearness, and humidity profiles for a typical meteorological year. See Appendix D of the FEDS User's Guide for more information.