Abstract
It is in some ways a strange curiosity that the “microprofession” of measurement and verification has generally ignored the financial side of the question of demonstrating the performance of an energy retrofit project. That is, a component which is conspicuously absent from the International Performance Measurement and Verification Protocol (IPMVP) is any treatment of the conversion of units of energy into dollars saved or costs avoided. It is an unfortunate omission, as conspicuous as the “missing man” in a formation flyover at a memorial service.
This article attempts to fill that hole in the IPMVP by addressing at least five different treatments of establishing a realistic dollar value for the units of energy saved in a performance contract and which are potentially being documented in a measurement and verification process.
INTRODUCTION
The International Performance Measurement and Verification Protocol (IPMVP) is notable in its lack of addressing the valuation of energy savings. This situation may very well be the result of the fact that the vast majority of professionals involved in measurement and verification come from an engineering and/or academic point of view and perhaps have a predilection for dealing with engineering units only. This should probably be considered a significant weakness in IPMVP, as it has been our experience that building owners, in fact care very less about saving energy, but care very much about saving money.
An addition to the IPMVP has been proposed to the technical committee but, for the apparent reasons stated above, was not implemented in the 1997 IPMVP’s successor, “IPMVP 2000.” This article essentially presents that proposed addition “Valuing Energy Savings,” and discusses many different ways of establishing the value of a kilowatt hour saved. In doing so, it will address the following concepts and methodologies:”avoided cost” average unit cost weighted average unit cost calibrated simulation real time costing rate application
Readers should realize that just as all methods of measurement and verification are imperfect, yet useful, the various methods of valuing energy savings presented herein are similarly flawed, but also useful.
AVOIDED COST
Facility managers can get into trouble if they do not address the mindset of the “audience” they are working for—generally upper management. As a general observation, upper managers tend not to understand, nor do they particularly care about, the intricacies of energy management and the “wonders” of the engineering world of Btus or kilowatt hours. Rather, they more characteristically tend to think and deal in economic units, i.e., dollars. As a result, trouble can occur due to this difference in mind sets.
As a simple but illustrative example, suppose that the facility manager has managed to decrease energy use by 10% from the prior year. Unfortunately, however, the energy supplier has simultaneously raised his rates by 10%—with the result that the total cost of energy for the facility has remained the same. Now, suppose further that upper management, based on what they thought were the promises made by the facility manager for his energy conservation program, decreased the budget for energy by 10%, and has now discovered that they are 10% over budget. Upper management cannot help but conclude that the facility manager has failed to produce the promised “savings” (after all, they paid a million last year and the bill this year is still a million—meaning that there are no savings). The potential consequences for the facility manager are fairly obvious and ominous in this scenario and would be avoided by any facility manager with any sense at all.
Then the astute facility manager, will have educated upper management in such a way that they understand that total energy cost is a product of two components: consumption and rates, and that cost may stay the same or even increase at the same time that “savings,” better known as “cost avoidance,” is being achieved.
This “cost avoidance,” then, is the difference between what the actual cost of energy is vs what the cost of energy would have been had no conservation actions been taken. In our illustration, while total cost remained the same, it would have increased by 10% had no energy management program been implemented. This concept is particularly poignant in facilities such as acute care hospitals, where a phenomenon known as “energy creep” is fairly common. In many acute care hospitals (and other types of complex facilities as well, of course), over time, more and more diagnostic and other types of electric and electronic equipment is brought into the facility. When this is combined with the natural “wearing down” of the facility’s infrastructure systems (lighting, heating, ventilating and cooling (HVAC), etc.), it is not uncommon for a facility’s energy use to gradually increase over time. In one specific case documented in the references, a 10-year pattern of growing energy use was observed, approximately 3% for electric and 5% for natural gas, during a period when no active changes to the energy management program were undertaken.
AVERAGE UNIT COST
This is the simplest method of valuing units of energy, and it may be applied to any of the four measurement and verification options (A-D).
This method simply takes the total cost of energy (from the utility bill) and divides it by the total number of units consumed, thereby producing an average unit cost for the units consumed. To set a value for energy units saved, this average unit cost for the current period (typically a month) is simply multiplied by the units of energy the measurement and verification procedures identified as having been saved.
This method is obviously very simple and (perhaps obviously) ignores the fact that energy use often has a time-related value, as embodied, e.g., in time-of-use (TOU) electric rates. Just as some believe that Option A in its simplest form (where few or no actual measurements are made) is a “bogus” measurement and verification (M&V) methodology, the use of average units costs may similarly be disparaged. However, if the energy
management program being employed is a broad program that affects energy use in a generally uniform manner over all time periods, then it may well be a perfectly suitable and acceptable methodology to the parties of a performance contract.
WEIGHTED AVERAGE UNIT COST
This is a fairly simple method, which is also applicable to all methods of measurement and verification. It is, however, perhaps best suited to Option A.
This approach makes a number of thoughtful assumptions about the time-occurrence of energy use (or energy savings) and performs calculations which apply the appropriate rate schedules to the assumptions to determine a weighted average unit cost for the energy units.
While it is based on assumptions, it may be updated or “calibrated” to actual experience if a time-related energy use pattern data are available (say, in a 15-min demand profile).
Tables 1-3 show three examples of a spreadsheet which performs the calculation of weighted average unit cost. Note that the examples show three different patterns of energy use, and produce distinctly different results based on those patterns. Keeping in mind that the analysis assumes that the load being evaluated is a nominal 1 kW load, then the calculation of annual kilowatt hour, e.g., also equals the equivalent full load operating hours (EFLH—please see the American Society of Heating Refrigeration and Air Conditioning Engineers (ASHRAE) handbook for a discussion of this term if it is one with which the reader is unfamiliar). While a complete explanation of the details of the spreadsheet has not been provided, the majority, if not all, of the calculations can be understood by observation. The author will assist those in need of explanation as required.
REAL TIME COSTING
This method is a bit more rigorous than those discussed above, and is generally oriented towards Option B.
This approach consists of building the rate schedule into the monitoring system and applying the rate schedule “on the fly” as energy savings are (or were) actually occurring.
For example, if a variable frequency drive was applied to a motor which previously operated fully loaded all the time, then the instrumentation, data gathering, and data reduction measurement and verification “package” applied to this retrofit would, during each operating time window (perhaps an hour), measure the then-current energy use of the motor, when compared with the original or baseline energy use, calculate the energy units saved, and apply the rate schedule applicable during that window of time.
Table 1 Average electrical cost analysis (based on time-of-use (TOU)/savings)
| Time of use (TOU) group: 1 Description: 24 h a day oper | ation | Date: 10/31/02 INIT: HK | ||||||||||||||
| Period (TOU) | Time | Available hours per day | Occ. hours per day | Percentage in use (%) | Hours of
use per daya |
Days per week | Weeks
per season |
Days per seasonb | Hours of use | Kilowatt hour unit cost ($) | Total energy cost ($) | Peak demand cost ($)c | Part demand cost ($)c | Max demand cost ($)c | ||
| Season: summer | ||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 8.5 | X 100 | = | 8.5 | 5 | 26.2 | 128 | 1088 | 0.05059 | 55.04 | 0 | 0.00 | 2.55 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 3.5 | X 100 | = | 3.5 | 5 | 26.2 | — | 448 | 0.05810 | 26.03 | 0 | 3.70 | 0.00 |
| Peak M/F | 12:00 | 18:00 | 6.0 | 6.0 | X 100 | = | 6.0 | 5 | 26.2 | — | 768 | 0.08773 | 67.38 | 13.35 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 3.5 | X 100 | = | 3.5 | 5 | 26.2 | — | 448 | 0.05810 | 26.03 | 0 | 0.00 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 2.5 | X 100 | = | 2.5 | 5 | 26.2 | — | 320 | 0.05059 | 16.19 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 24.0 | X 100 | = | 24.0 | 2 | 26.0 | 52 | 1248 | 0.05059 | 63.14 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 24.0 | X 100 | = | 24.0 | NA | NA | 3 | 72 | 0.05059 | 3.64 | 0 | 0.00 | 0.00 |
| Summer season totals | 183 | 4392 | 257.44 | 80.10 | 22.20 | 15.30 | ||||||||||
| Season: winter | ||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 8.5 | X 100 | = | 8.5 | 5 | 26.0 | 125 | 1062.5 | 0.05038 | 53.53 | 0 | 0.00 | 2.55 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 3.5 | X 100 | = | 3.5 | 5 | 26.0 | — | 437.5 | 0.06392 | 27.97 | 0 | 3.65 | 0.00 |
| Part-peak M/F | 12:00 | 18:00 | 6.0 | 6.0 | X 100 | = | 6.0 | 5 | 26.0 | — | 760.0 | 0.06392 | 47.94 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 3.5 | X 100 | = | 3.5 | 5 | 26.0 | — | 437.5 | 0.06392 | 27.97 | 0 | 0.00 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 2.5 | X 100 | = | 2.5 | 5 | 26.0 | — | 312.5 | 0.05038 | 15.74 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 24.0 | X 100 | = | 24.0 | 2 | 26.0 | 52 | 1248.0 | 0.05038 | 62.87 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 24.0 | X 100 | = | 24.0 | NA | NA | 5 | 120.0 | 0.05038 | 6.05 | 0 | 0.00 | 0.00 |
| Winter season totals | 182 | 4368 | 242.06 | 0.00 | 21.90 | 15.30 | ||||||||||
| Annual totals | 365 | 8760 | 499.51 | 80.10 | 44.10 | 30.60 | ||||||||||
Table 1 Average electrical cost analysis (based on time-of-use (TOU)/savings) (Continued)
| Actual rate schedule | |||
| Rate: PG&E E19S | Effective: 1/1/98 | ||
| Summer ($) | Winter ($) | ||
| Demand charges ($/kW) | |||
| Max peak | 13.35 | 0.00 | |
| Max part-peak | 3.70 | 3.65 | |
| Max demand
Energy charges ($/kWh) Peak |
2.55 0.08773 | 2.55 0.00 | |
| Partial-peak | 0.05810 | 0.06392 | |
| Off-peak | 0.05059 | 0.05038 | |
| Results of analysis | |||
| Total demand (kW) cost | $155 | ||
| Total energy (kWh) cost | $500 | ||
| Total cost | $654 | ||
| Total cost/kWh | $0.075 | ||
| Average cost/kWh w/o demand | $0.057 | ||
All calculations assume a 1 kW load. All demand costs are “percentage in use” times rate in effect for period. Cost calculated herein may be used for valuing consumption or savings. aHours of use per day = occ. hours per dayX percentage in use. bWeekdays “days per season” are less holidays. cDemand cost season sub-totals are for 6 months.
Table 2 Average electrical cost analysis (based on time-of-use (TOU)/savings)
| Time of use (TOU) group: 3 Description: night lighting from 8 | p.m. to 1 a. | . | Date: 10/31/02 INIT: HK | ||||||||||||||
| Period (TOU) | Time | Available hours per day | Occ. hours per day | Percentage in
use (%) |
Hours of use per day” | Days per week | Weeks per season | Days per seasonb | Hours of
use |
Kilowatt hour unit
cost ($) |
Total energy cost ($) | Peak demand cost ($)c | Part demand cost ($)c | Max demand cost ($)c | |||
| Season: summer | |||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 1.0 | X | 100 | = | 1 | 5 | 26.2 | 128 | 128 | 0.05059 | 6.48 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 0.0 | X | 0 | = | 0 | 5 | 26.2 | — | 0 | 0.5810 | 0.0 | 0 | 0.00 | 0.00 |
| Peak M/F | 12:00 | 18:00 | 6.0 | 0.0 | X | 0 | = | 0 | 5 | 26.2 | — | 0 | 0.08773 | 0.0 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 1.5 | X | 100 | = | 1.5 | 5 | 26.2 | — | 192 | 0.05810 | 11.16 | 0 | 3.70 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 2.5 | X | 100 | = | 2.5 | 5 | 26.2 | — | 320 | 0.05059 | 16.19 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 0.0 | X | 0 | = | 0 | 2 | 26.0 | 52 | 0 | 0.05059 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 0.0 | X | 0 | = | 0 | NA | NA | 3 | 0 | 0.05059 | 0.00 | 0 | 0.00 | 0.00 |
| Summer season totals | 183 | 640 | 33.82 | 0 | 22.20 | 0.00 | |||||||||||
| Season: winter | |||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 1.0 | X | 100 | = | 1 | 5 | 26.0 | 125 | 125 | 0.05038 | 6.30 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 0.0 | X | 0 | = | 0 | 5 | 26.0 | — | 0 | 0.06392 | 0.00 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 12:00 | 18:00 | 6.0 | 0.0 | X | 0 | = | 0 | 5 | 26.0 | — | 0 | 0.06392 | 0.00 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 1.5 | X | 100 | = | 1.5 | 5 | 26.0 | — | 187.5 | 0.06392 | 11.99 | 0 | 3.65 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 2.5 | X | 100 | = | 2.5 | 5 | 26.0 | — | 312.5 | 0.05038 | 15.74 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 0.0 | X | 0 | = | 0 | 2 | 26.0 | 52 | 0 | 0.05038 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 0.0 | X | 0 | = | 0 | NA | NA | 5 | 0 | 0.05038 | 0.00 | 0 | 0.00 | 0.00 |
| Winter season totals | 182 | 625 | 34.03 | 0 | 21.90 | 0.00 | |||||||||||
| Annual totals | 365 | 1265 | 67.85 | 0 | 44.10 | 0.00 | |||||||||||
| Demand charges ($/kW) | ||
| Max peak | 13.35 | 0.00 |
| Max part-peak | 3.70 | 3.65 |
| Max demand | 2.55 | 2.55 |
| Energy charges ($/kWh) | ||
| Peak | 0.08773 | 0.00 |
| Partial-peak | 0.05810 | 0.06392 |
| Off-peak | 0.05059 | 0.05038 |
| Results of analysis | ||
| Total demand (kW) cost | $44 | |
| Total energy (kWh) cost | $68 | |
| Total cost | $112 | |
| Total cost/kWh | $0.088 | |
| Average cost/kWh w/o demand | $0.054 | |
All calculations assume a 1 kW load. All demand costs are “percentage in use” times rate in effect for period. Cost calculated herein may be used for valuing consumption or savings. aHours of use per day = occ. hours per day X percentage in use. bWeekdays “days per season” are less holidays. cDemand cost season sub-totals are for 6 months.
| Actual rate schedule | |||
| Rate: PG&E E19S | Effective: 1/1/98 | ||
| Summer ($) | Winter ($) | ||
Table 3 Average electrical cost analysis (based on time-of-use (TOU)/savings)
| Time of use (TOU) group: 2 | Date: 10/31/02 | ||||||||||||||||
| Description: typical office usage from 7 a.m. to 7 p.m. | INIT: HK | ||||||||||||||||
| Period (TOU) | Time | Available hours per day | Occ. hours per day | Percentage in
use (%) |
Hours of use per day” | Days per week | Weeks per season | Days per seasonb | Hours of
use |
Kilowatt hour unit
cost ($) |
Total energy cost ($) | Peak demand cost ($)c | Part demand cost ($)c | Max demand cost ($)c | |||
| Season: summer | |||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 1.5 | X | 100 | = | 1.5 | 5 | 26.2 | 128 | 192 | 0.05059 | 9.71 | 0 | 0.00 | 2.55 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 3.5 | X | 100 | = | 3.5 | 5 | 26.2 | — | 448 | 0.05810 | 26.03 | 0 | 3.70 | 0.00 |
| Peak M/F | 12:00 | 18:00 | 6.0 | 6.0 | X | 100 | = | 6 | 5 | 26.2 | — | 768 | 0.08773 | 67.38 | 13.35 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 1.0 | X | 100 | = | 1 | 5 | 26.2 | — | 128 | 0.05810 | 7.44 | 0 | 0.00 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 0.0 | X | 100 | = | 0 | 5 | 26.2 | — | 0 | 0.05059 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 0.0 | X | 100 | = | 0 | 2 | 26.0 | 52 | 0 | 0.05059 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 0.0 | X | 100 | = | 0 | NA | NA | 3 | 0 | 0.05059 | 0.00 | 0 | 0.00 | 0.00 |
| Summer season totals | 183 | 1536 | 110.56 | 80.10 | 22.20 | 15.30 | |||||||||||
| Season: winter | |||||||||||||||||
| Off-peak M/F | 24:00 | 8:30 | 8.5 | 1.5 | X | 100 | = | 1.5 | 5 | 26.0 | 125 | 187.5 | 0.05038 | 9.45 | 0 | 0.00 | 2.55 |
| Part-peak M/F | 8:30 | 12:00 | 3.5 | 3.5 | X | 100 | = | 3.5 | 5 | 26.0 | — | 437.5 | 0.06392 | 27.97 | 0 | 3.65 | 0.00 |
| Part-peak M/F | 12:00 | 18:00 | 6.0 | 6.0 | X | 100 | = | 6 | 5 | 26.0 | — | 750 | 0.06392 | 47.94 | 0 | 0.00 | 0.00 |
| Part-peak M/F | 18:00 | 21:30 | 3.5 | 1.0 | X | 100 | = | 1 | 5 | 26.0 | — | 125 | 0.06392 | 7.99 | 0 | 0.00 | 0.00 |
| Off-peak M/F | 21:30 | 24:00 | 2.5 | 0.0 | X | 100 | = | 0 | 5 | 26.0 | — | 0 | 0.05038 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak S/S | 00:00 | 24:00 | 24.0 | 0.0 | X | 100 | = | 0 | 2 | 26.0 | 52 | 0 | 0.05038 | 0.00 | 0 | 0.00 | 0.00 |
| Off-peak H | 00:00 | 24:00 | 24.0 | 0.0 | X | 100 | = | 0 | NA | NA | 5 | 0 | 0.05038 | 0.00 | 0 | 0.00 | 0.00 |
| Winter season totals | 182 | 1500 | 93.34 | 0.00 | 21.90 | 15.30 | |||||||||||
| Annual totals | 365 | 3036 | 203.90 | 80.10 | 44.10 | 30.60 | |||||||||||
| Actual rate schedule Rate: PG&E E19S
Demand charges ($/kW) |
Effective:
Summer ($) |
1/1/98
Winter ($) |
| Max peak | 13.35 | 0.00 |
| Max part-peak | 3.70 | 3.65 |
| Max demand | 2.55 | 2.55 |
| Energy charges ($/kWh) | ||
| Peak | 0.08773 | 0.00 |
| Partial-peak | 0.05810 | 0.06392 |
| Off-peak | 0.05059 | 0.05038 |
| Results of analysis | ||
| Total demand (kW) cost | $155 | |
| Total energy (kWh) cost | $204 | |
| Total cost | $359 | |
| Total cost/kWh | $0.118 | |
| Average cost/kWh w/o demand | $0.067 | |
All calculations assume a 1 kW load. All demand c osts are “percentage in use” times rate in effect for period. Cost calculated herein may be used for valuing consumption or savings. aHours of use per day = occ. hours per dayX percentage in use. bWeekdays “days per season” are less holidays. cDemand cost season sub-totals are for 6 months.
Table 4 Variable air volume cost avoidance
| Day type Hour | Weekday cost | Rate sch | Date: 06/09/98 | ||||
| Existing | Retrofit | Delta | |||||
| kW/kWh | $/kWh | kW/kWh | $/kWh | kWh | $/kWh | ||
| 1 | 200 | 10.12 | 52 | 2.62 | 148 | 7.50 | |
| 2 | 200 | 10.12 | 50 | 2.51 | 150 | 7.61 | |
| 3 | 200 | 10.12 | 44 | 2.25 | 156 | 7.87 | |
| 4 | 200 | 10.12 | 41 | 2.09 | 159 | 8.03 | |
| 5 | 200 | 10.12 | 38 | 1.94 | 162 | 8.18 | |
| 6 | 200 | 10.12 | 40 | 2.05 | 160 | 8.07 | |
| 7 | 200 | 10.12 | 54 | 2.72 | 146 | 7.40 | |
| 6 | 200 | 11.62 | 69 | 3.99 | 131 | 7.63 | |
| 9 | 200 | 11.62 | 86 | 5.09 | 112 | 6.53 | |
| 10 | 200 | 11.62 | 103 | 5.96 | 97 | 5.66 | |
| 11 | 200 | 11.62 | 113 | 6.55 | 87 | 5.07 | |
| 12 | 200 | 11.62 | 127 | 7.39 | 73 | 4.23 | |
| 13 | 200 | 17.55 | 148 | 13.01 | 52 | 4.53 | |
| 14 | 200 | 17.55 | 161 | 14.11 | 39 | 3.44 | |
| 15 | 200 | 17.55 | 170 | 14.95 | 30 | 2.60 | |
| 16 | 200 | 17.55 | 173 | 15.20 | 27 | 2.34 | |
| 17 | 200 | 17.55 | 170 | 14.95 | 30 | 2.60 | |
| 18 | 200 | 17.55 | 161 | 14.16 | 39 | 3.39 | |
| 19 | 200 | 11.62 | 141 | 8.19 | 59 | 3.43 | |
| 20 | 200 | 11.62 | 119 | 6.89 | 81 | 4.73 | |
| 21 | 200 | 11.62 | 100 | 5.82 | 100 | 6.60 | |
| 22 | 200 | 10.12 | 85 | 4.28 | 115 | 5.84 | |
| 23 | 200 | 10.12 | 74 | 3.73 | 126 | 6.39 | |
| 24 | 200 | 10.12 | 65 | 3.27 | 135 | 6.84 | |
| Total/avg. | 4800 | 299.42 | 2386 | 163.71 | 2414 | 135.71 | |
| Rate schedule: PG&E E19S | Effective date: 01/01/98 | |
| Summer ($) | Winter ($) | |
| Demand charges ($/kW) | ||
| Max peak | 513.35 | 0.00 |
| Max part peak | 170.0 | 3.65 |
| Max demand | 2.55 | 2.65 |
| Energy charges ($/kW) Peak: | 0.08773 | 0.00 |
| Partial-peak | 0.05810 | 0.06392 |
| Off-peak | 0.05059 | 0.05038 |
Table 4 Variable air volume cost avoidance (Continued)
If a real-time system of data gathering and analysis is employed, then this valuing of energy units saved would also be in real time. However, the approach is just as effective in valuing the energy units saved even if it is applied after the fact to energy data gathered in real time, but analyzed at a later time.
Table 4 shows a sample spreadsheet for an Option B measurement and verification of a variable volume fan conversion. In this example, the baseline conditions have been established by short-term monitoring of the fan motor and a load profile developed as well through short-term monitoring and extrapolation to a year-long load profile by means of linear regression of the short-term load monitoring data and applying the linear regression equation (Y = mX+ b).
RATE APPLICATION
This method has Option C in mind and assumes that either the utility meter is being employed to measure and record both baseline and postretrofit energy use, or that a meter of similar character has been applied to the facility, and that the baseline energy use has been recorded in such a way that the present rate schedule can be applied to it. That is, the peak demand and energy use in each TOU period is available.
In this instance, the current rate schedule is applied to the recorded energy use and the total cost calculated for
both the baseline and postretrofit situations. The cost avoided is simply the difference between the two.
A wealth of proprietary software is already commercially available to implement this methodology, such as Faser, Metrix, and Utility Manager, to name three.
CALIBRATED SIMULATION
This method is not for the faint of heart, and is oriented towards Option D. This method, perhaps due to the extremely wide variation in simulation skill and acumen among its practitioners, has a reputation for being completely hypothetical, extremely effective, or anywhere in between.
Simply put, calibrated simulation requires significant rigor and clear demonstration of its faithful emulation of reality if it is to possess veracity. To achieve this goal, this approach would encompass, e.g., the creation of a computer simulation model of a building or sub-system (say a chiller plant) in its baseline state, and the calibration (and demonstration thereof) of the model to reality. In addition, the retrofitted facility would also be modeled and calibrated as well. In the case of a chiller plant, the reality to which the models are calibrated might be a dedicated utility-style electric meter through which all power consumed by the plant is measured, and other specific measurements, perhaps instantaneous pump and cooling tower electrical demand, total cooling provided by the plant (ton hours output), etc.
Because both the baseline and retrofit conditions are simulated and calibrated, there can be considerable faith, then, in the veracity of the units of energy and the time-related patterns of energy use in the model.
Assuming that the simulation tool used for the modeling has the ability to incorporate and apply the rate schedules in use, both models may be run with whatever current rate schedule is in effect, and very accurately calculate the operation cost of the baseline and the retrofit facilities. Avoided cost, then, is simply the difference between the two.
CONCLUSION
The bottom line of all these efforts, again, is to translate the “technical” determination of units of energy saved into a financial result which management may make use of. Without doing so, energy engineers run the risk of being dismissed as being irrelevant by upper management, so this step in the M&V process is, perhaps amazingly, the one that may be the most important of all!
