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.
Normal/typical plug loads are accounted for (inferred) automatically within FEDS. These values can be viewed and/or changed from the miscellaneous equipment inputs in maximum detail display. The data is based on major end-use load surveys for typical plug load levels and accounts for the typical levels of equipment loads in a given use-area type. For example, for an office building this will account for typical levels of things, such as computers, printers, copiers, clocks, vending machines, coffee makers, and kitchenette equipment.
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.
Generally, it is best to specify the original purpose of the building as the building type, and then modify the use-area type to reflect its current use. Select building type = "Education", use-area type = "Office." The building's construction characteristics are inferred based on building type, while usage parameters (including occupancy, lighting and equipment use, and hot water demand) are based on the use-area type.
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.
There is effectively no limit to the number of building sets allowed in a single case if there is enough hard drive space. Currently, each building set occupies approximately 4.3 megabytes of space across all file types. Given adequate storage space, FEDS can be—and has been—used to model an entire community, city, or utility service area.
There is no real limit to the number of buildings that can be modeled in a building set. However, building sets are designed to model buildings that share similar characteristics. The more similar buildings are within a given building set, the more accurate the results will be.
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.
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.
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.
Use the building type or use-area designation that best fits regardless of which list it is on. The building set classes were grouped this way to aid in the selection of common types, but either list may be selected.
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).
FEDS allows a negative value for percentage of heat to the conditioned space. For example, if the equipment has a COP of 2.0 and operates with an exterior condenser, then -200 should be entered for this value and the capacity should be half the actual rated capacity. (This will result in heating an amount equivalent to 200% of the unit's consumption as being rejected outside.)
The typical FEDS user will not have detailed information available regarding plug load levels in order to adequately model them and will need to rely on the inferred values. However, miscellaneous equipment records may be modified or added if a load is unusual or atypical of the use-area type, or has an extremely large load (or one that sees extensive use) that is above and beyond what would be considered typical. Similarly, a user may want to reduce the capacity density for some areas deemed to have a lower load density than typical for that type of space, or even delete entire records when there is no equipment in use of a given type.