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.
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).
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.
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.
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.
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.
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).