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.
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.
Weekday, Saturday, and Sunday hot water consumption values are determined using typical usage rates for a given use-area type, along with the number of occupants and occupancy schedule for each day type. Values are also adjusted according to such parameters as the presence or absence of showers and high efficiency fixtures.
FEDS assumes circulating (or loop) hot water systems serve entire buildings. Specifying a loop system for use-area 1 automatically identifies that it also serves use-area 2. Loop systems that only serve use-area 2 cannot be modeled, and the loop selection box is unnecessary and is disabled.
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.
Storage capacity for hot water is calculated using the building type and building's design occupancy. For distributed tank systems, values are rounded up to the next increment of typical tank capacity.
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.
No. If a building (or use-area) has any hot water available users should specify 100% of it is served by hot water. As long as there is hot water available in a space, occupants will utilize it even if it is not immediately accessible. The purpose of having the portion served input is to allow the FEDS user to specify entire buildings (or use-areas) within a building set that do not have any hot water. For example, for a building set consisting of 10 buildings in which two of the buildings have no hot water service, they would enter that two buildings (or 20%) for the portion of buildings in this set that have no water heating.
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.
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 project costing algorithms account for any materials, taxes, and labor costs applicable to a given retrofit measure. Additionally, 15% contractor overhead, 10% design cost, and 6% site level supervisory, inspection and overhead factors are applied, along with any multipliers specified on the regional costs screen under the financial options. Note that many of the cost factors reflect real regional variation, including labor rates, materials cost multipliers, and sales tax rates—with differentiation driven by the specified zip code. Each of these parameters are also able to be modified by the user, if appropriate.
The non-annual maintenance cost is used by FEDS to account for costs recurring on a non-annual basis, such as incremental equipment replacements and replacing failed lamps and ballasts. For example, the present value of the non-annual maintenance cost for lighting represents the present value of the total cost (including materials and labor) to replace the burned-out lamps and ballasts of a particular lighting technology over the course of the study period (generally 25 years).
FEDS employs the same standard life-cycle costing methodology and algorithms as the building life-cycle costing computer program developed by the National Institute of Standards and Technology.
The discount rate is the factor used to adjust (discount) future sums of money into the equivalent current year dollar amount. It can also be thought of as the interest rate or hurdle rate (i.e., the rate of return required by a company for it to undertake a project). FEDS uses the real discount rate, which has the effect of inflation removed. FEDS provides the current Federal real discount rate as the default, but the user may enter any discount rate appropriate for their projects. Energy service companies performing shared energy savings contracts typically require real rates of return in the neighborhood of 10 to 20%.
The global cost multiplier is an overall cost multiplier applied to the total project cost (including all materials, labor, taxes, overhead). It can be used to adjust all of the total project costs used in FEDS economic calculations. This could be used for such purposes as to account for special cost-impacting requirements of working at a facility with stringent security requirements or health and safety risks, or to assess the impact of varying costs on project economics.
On the bottom right of some input screens (windows, lighting, heating, cooling, hot water, and motors) is a check box labeled "replacement required". The purpose of this selection is to tell FEDS that this particular building component or technology must be replaced. Whether it has failed (for example, windows are broken, or the furnace has stopped working), or a replacement or upgrade is planned, checking this box will force a replacement to be evaluated and selected when the FEDS optimization analysis is run. If a replacement option is cost effective, FEDS will work as normal; however, if one is not, FEDS will still provide the recommendation even though it may not be otherwise cost effective. FEDS will still report the most cost-effective option and all of the standard details to help users make informed decisions. This option is also known as replace on failure economics.
For distributed tank systems, FEDS assumes commercial tanks are 80 gallons, while residential units are 50 gallons.
FEDS assumes loop (circulating) systems serve an entire building and, therefore, the number of tanks is inferred to be one for each building, regardless of the number of use areas present.
FEDS project costs are based on industry averages and may not match the exact costs you will be charged. The end-use and technology multipliers are intended to enable the user to adjust for these discrepancies so that the costs used in the FEDS analyses are as close to actual as possible. The recommended approach would be to first enter any known cost data (such as, labor rates, tax rate, discount rate, etc.), and then run FEDS, generate reports, and see what types of projects are coming up. Compare the project costs to actual known costs or bids for similar projects of that type. If any of the technology costs are grossly high or low, adjust them appropriately with a technology multiplier. Rerun FEDS to see if the same technology is being selected, and make sure that the costs more closely represent what the anticipated cost to complete the project. Because of the complex nature of the FEDS cost data, this iterative multiplier approach is the best way for users to modify project costs.