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.
Yes. FEDS now models and evaluates lighting controls, including occupancy sensors. To model existing lighting controls, the user must select the appropriate "yes" response to the "Existing lighting controls?" input and review the existing utilization factors. To infer reasonable utilization factors for the controlled lighting, specify the appropriate space type for the space where the lights exist.
FEDS will also automatically evaluate the savings potential and cost-effectiveness of lighting controls where they do not currently exist. In this scenario, select "no–evaluate occupancy sensor" and identify the most applicable space type. In this case, the "existing" utilization factors identify the portion of time that the lights are currently on, while the "with controls" utilization factors will be used by FEDS to model the impact of the occupancy sensor controls. The "number of sensors required" is used by the cost model to identify how many sensors need to be installed to control the current lighting.
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.
Each lamp and ballast modeled within FEDS has a rated life (specified in hours) associated with it. Actual replacement intervals are calculated within the model based on the light's modeled operating hours (based on utilization factors and occupancy schedules) and rated life of each component. When a lamp or ballast fails, FEDS accounts for the cost to replace the component by figuring both materials and labor requirements. These costs are tallied over the economic study period and reported as the non-annual maintenance cost. FEDS uses the non-annual maintenance cost along with energy and capital costs in determining which fixture can best provide the required level of service at the lowest life-cycle cost.
Exterior lighting, such as security or parking lot lights can be included in FEDS by selecting the exterior fixture location. This will set the heat to space to 0 and alter the calculation of utilization factors appropriate for typical nighttime operation.
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.
Refer to Appendix G of the FEDS User's Guide. Ex: FL 2x4 4F40T12 STD2 = a 2-foot by 4-foot fluorescent fixture, with four 40 watt T12 (1.5 inch diameter) lamps, operated by two standard magnetic ballasts (designed to operate two lamps each).
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.
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.
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.
The utilization factors for lighting represent the portion of time particular lights are on, on average, over the building set. They are expressed as a fraction of the maximum possible load (i.e., 100% of the lights are on 100% of the time) for a given time period. FEDS infers the occupied and unoccupied period utilization factors based on what is typical on average for the lighting technology and use-area type. FEDS typically assumes that some lights are on even during unoccupied times for security, safety, or cleaning staff, or simply because lights were left on. During seasonally unoccupied months and other periods defined as non-operating, utilization factors are set to 0 for all lighting records except for exit lights, which are assumed to operate constantly.
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).
The lighting use-area fixture density is the inferred fixtures per square foot and is based on typical lumen levels for different use-area types. It represents the average fixtures per square foot over the entire use-area (or building for single use-area buildings). Typically, the user will know the total number of fixtures in a use-area and can enter this and allow the software to calculate the fixtures per square foot.
No. At this time FEDS considers only fixture per fixture replacements that provide similar light output. However, the energy impact of correcting an over/under lit condition could be analyzed comparing by two consecutive FEDS baseline runs (by running without optimization).