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.
Prices must be provided for all fuels being used in the buildings being modeled. In addition, prices may also be provided for fuels not currently being used for FEDS to consider those fuels in its economic calculations (e.g., to consider fuel-switching opportunities).
TIP—Watch units required for fuel price parameters! Electric energy prices are requested in ¢/kWh, while demand charges are in $/kW.
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.
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.
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.
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).
Typically, the "Other" fuel type represents liquid propane gas (LPG) or propane fuel. However, if you use another fuel type that is not listed (e.g., wood chips), you may use "Other" to represent this fuel type.
A minimum or contract demand is included in some commercial and industrial electricity tariffs. It specifies the minimum billing demand that will be charged each month. This is important to understand because implementing energy efficiency projects that reduce the site’s monthly peak demand below the contract demand will have limited return, as no additional savings in demand charges will accrue once the actual monthly demand falls below the minimum contract value. If that is possible for your site, it is best to review this with your utility and negotiate a lower contract demand.
A demand ratchet is a billing method commonly imposed by electric utilities on large commercial or industrial customers. It specifies that the billed demand level in kW be the larger of the actual peak demand for the billing period, or a percentage of the highest peak reached during the previous X months. A typical demand ratchet uses 80% of the peak demand occurring during the previous 11 months as the comparison point. Under this scenario, if your facility experiences a peak demand of 1,000 kW for one hour (or 15 minute interval) you will be billed for a minimum of 800 kW during the next 11 months, even if your actual demand is much lower. Demand ratchets are generally used by utilities to reduce the risks of serving certain types of customers who have potentially large swings in demand during the year—making them pay for the assurance of having the high capacity available when needed.
A marginal price is the price paid for the last increment of energy purchased. This should, therefore, exclude all fixed charges (e.g., the monthly customer or meter charge) and focus only on the costs that vary based on the amount of energy used. Some rate structures are more complex and require some analysis. For example, in a block electric rate structure where users pay a certain amount depending on how much electricity used during the month, the value of electricity would be the price corresponding to the amount the building generally consumes in a month (rather than the average cost over all kWh's used). The marginal rate is the value of a unit of energy saved (i.e., the value of a kWh saved by an efficiency measure).
Providing detailed marginal prices for electricity (including any time-of-day or seasonal variations, and the impact of demand charges and ratchets) is important as it can have a huge impact on the types and cost effectiveness of recommended efficiency measures, as compared with applying basic melded average rates.
Distillate oil is light fuel oil that has been further refined than heavier oils. Examples include #2 fuel oil and diesel fuel. Residual oil, as its name suggests, is the oil residue that remains after distilling out the lighter grade components. It is generally designated as #4, #5, or #6 fuel oil, is much more viscous than ordinary oils, and must be heated to allow it to flow and be burned.
Most fuels are valued in FEDS as delivered to the building or end-use. However, the value for district fuels at the building or end-use level are determined somewhat differently. For self-generated fuel types (e.g., central steam, hot water, or chilled water) FEDS calculates the value of the fuel from the inputs in the central plants and thermal loops module. For example, the average value of self-generated steam is calculated based on the energy price of the fuel consumed by the boiler at the central plant along with its conversion efficiency, value of auxiliary energy and chemicals and labor to operate the plant, plus thermal and leakage losses in the thermal loops that distribute the steam to the building. If the central steam plant has multiple distribution loops, the losses may be different and therefore each steam loop can have its own average value for the steam it delivers. For purchased central fuel types (purchased steam, hot water, or chilled water) the value of the fuel delivered to the installation boundary is entered on the "Non-Electric Energy Prices" screen, and then FEDS applies information on the efficiency of each distribution loop to determine the average value of the steam at the building level as delivered by each loop. Marginal values do not consider fixed O&M costs (i.e., those that do not vary with the quantity of central fuel produced/delivered) or distribution losses (which are fixed and do not vary with the amount of energy delivered). Marginal values are used to determine the value of each increment of energy consumed or saved.
No. Given the importance of energy prices on the analysis, as well as the significant variation in rates available within a given region, there are no default or inferred electric or non-electric fuel price data. Users should enter the value of all fuels available.