The business decision to go green has never been more difficult. Between a variety of cash and tax incentives, third-party ownership agreements, and the quest for a capital-free project, the business case can become prohibitively complex. As a result, justifications get over-simplified, projects aren’t all they appear to be, and we end up with nicely packaged projects yet only a vague understanding of the true economics behind them.
As a result, billions of dollars in jobs have been developed whose projected returns will never be realized. Conversely, millions of dollars of savings will never be realized because projects never get off the ground in the first place. With the energy industry promising to be the driver of a new economy, it’s our responsibility as electrical professionals to understand the economic truths behind the business case. This can only be accomplished, however, if you truly know how electric utilities bill for electricity (see SIDEBAR: Understanding Your Electric Utility Bill below), how to decode that billing structure in terms of project economics, and how to select and modify projects to yield the best results.
It all comes down to the most misunderstood of the energy contract complexities — the positive cash flow, or more specifically, the avoided cost. All energy projects share this economic basis. Whether the project is based on demand response, on-site generation, or an energy efficiency retrofit, its feasibility depends on the same thing: projected energy savings. These savings are based on a simple calculation and depend on the amount of energy offset and avoided cost of energy (ACOE).
Positive cash flow = (energy offset) x (avoided cost of energy)
Because the energy offset is a known or contracted amount, the only unknown is the ACOE, which is defined as the rate (per kWh) that a project relieves a customer from paying to the electric utility. If a customer installs a solar panel that offsets 100kWh annually — and his annual electric utility cost is reduced by $15 as a result — then the avoided cost of energy for that solar panel is $0.15 per kilowatt-hour (kWh). The ACOE is the absolute basis for any energy project, as it defines the entire financial return. However, it typically achieves no more attention than a blind average of past electric utility bills or a quick glance at an electric utility rate tariff. Due to the dynamic nature of energy usage and rate tariffs, the ACOE cannot be empirically measured. Therefore, customers are left with little other choice than to make these inaccurate approximations. The project’s real-world financial performance is equally immeasurable, leaving so many companies with an inaccurate assessment of their project’s value. In any other investment vehicle, this kind of ambiguity would be unacceptable.
As we begin to explore how to properly calculate avoided cost, understand that these methods are meant for commercial and industrial electric utility customers — and do not represent an overall improvement or degradation of energy project economics. These factors can swing either way, and the results are particular to a specific technology, facility, and rate tariff combination.
In order to understand this concept, let’s walk through a few of the basic parameters involved in arriving at this calculation.
The tariff — For any ACOE calculation, you must know the current rate tariff of the facility under consideration. For the following examples, we will use a common commercial rate tariff in California, Pacific Gas & Electric (PG&E) Company’s E-19 Secondary. Time of Use (TOU) rate tariffs like this one bill customers across multiple billing categories, each with an associated metric/rate and differentiated by time of day and season. The primary charge types are energy charges (which bill customers on a per-kWh basis for energy consumed) and demand charges (which bill customers on a per-kW basis for their maximum rate of consumption in any given period). Neglecting a great deal of less-significant rate categories for a moment (i.e., fixed costs, facility charges, rate components, etc.), the PG&E 19S tariff can be summarized as shown inTable 1 (click here to see Table 1).
The data — In order to properly calculate the avoided cost of a facility, you need to know the energy profile of the facility. Luckily, some electric utilities offer historical TOU data, often as an Excel file, which details the facility’s consumption in 15-min. intervals. The interval of choice is typically a year or 35,040 data points. This historical data set is used to model the first year of a project’s life — so the more recent the data, the better the approximation. The ACOE calculation also requires the energy profile of the proposed energy project, also as 15-min. interval data. This is another commonly overlooked detail of the calculation and impacts the ACOE by as much as 30% in the following example (click here to see Table 2).
Let’s says a lighting retrofit reduces the consumption of luminaires by a known amount. In a warehouse that operates 24/7, the impact of the luminaires would be spread across on-peak, partial-peak, and off-peak periods. In contrast, an air-conditioning retrofit on the same warehouse would have a much higher avoided cost, because it’s most active during hot afternoons — and its energy profile coincides nicely with the higher on-peak and partial-peak rates. Because the energy profiles — and likewise the associated ACOE — varies considerably between various generation, efficiency, and demand response technologies, it is imperative that the project’s energy profile data be accurate.
As illustrated in Fig. 1 (click here to see Fig. 1), the project’s energy profile can then be subtracted from the facility load profile (on an interval by interval basis) in order to create a new effective energy profile for the facility. This new effective energy profile is an approximation of what the facility profile would look like after the project has been executed. You now have two distinct facility load profiles — a before and an after — and you can run them through a bill generator in order to convert the offset kWh and kW into dollars. The difference between these two bill cases provides you with the actual dollar amount offset by the project, which includes the avoidance of both energy costs and demand costs, when applicable.
For simplified overall economic analysis, this dollar amount is then divided by the annual energy offset by the project to produce the ACOE in dollars per kilowatt-hour ($ / kWh). For the following examples, we will use the interval data of a 55,000-sq-ft medical office building, a summary of which is shown in Fig. 1.
There are three primary ways to impact avoided cost: the timing of the energy offset; demand coincidence; and reliability. The higher the percentage of the energy offset that occurs in on-peak or partial-peak periods, the higher the avoided cost. One of the best technologies at exploiting this trend is solar power, because it only operates during daylight hours, and 80% of its impact is between the hours of 10 a.m. and 3 p.m. Solar systems primarily offset on-peak and partial-peak periods (i.e., those with the highest rates). One of the worst technologies at exploiting this trend would be a night lighting retrofit, as it would mostly offset energy during off-peak times (i.e., off-peak rates).
Demand coincidence, however, is a much more sensitive issue. In order for a project’s energy profile to coincide with a facility’s demand profile, it must (a) be offsetting energy at the same time that the facility is experiencing maximum consumption, and (b) persist for the entirety of the TOU period — or until the facility’s consumption declines. The technologies that best exploit this are base-load or 24/7 technologies, such as fuel cells, co-gen systems, or efficiency retrofits for high-demand equipment.
However, even if a project’s energy profile perfectly coincides with a facility’s demand profile, it must be reliable. If a project offsets 100% of the demand, for 99% of a billing period, it does not avoid any demand cost. It only takes one poorly timed 15-min. interval of high facility demand and low energy offset to result in a project achieving $0 of demand savings for that billing period. Without even considering the temporary failure of equipment, this is an enormous issue for technologies like solar, which have an energy profile that can swing wildly based on weather conditions. Once equipment failure or maintenance is considered, the only way to take this unfortunate reality into account is to either (a) insert such outages strategically into the performance profile of your technology, or (b) provide contractual means with the equipment provider to make the customer whole for such outages. Both strategies are effective and common, but in reality, many projects only avoid some demand cost. The variability inherent in the interval model demonstrates this as long as the projects performance data accurately reflects the expected performance of the equipment. Examples of a demand coincidence and reliability situations are shown in Figs. 2 and 3. (click here to see Fig. 2) and (click here to see Fig. 3).
For the medical office building, under the PG&E E-19S rate tariff, Table 2 shows the results of this type of analysis. In some cases, the post-project energy profile may even lend itself to an entirely different electric utility tariff. The ACOE is also shown in Table 2 for a PG&E A-6 tariff, which is heavily weighted toward energy costs and almost entirely removes demand costs. In some cases, the opportunity can be extremely lucrative, but electric utility policies and restrictions must be studied thoroughly before including this assumption in a business case.
Armed with this method of analysis, the ACOE can be merged with the rest of the economic business case. Because the ACOE calculated here determines the present day avoided cost, that value must be escalated up to the expected year of project commissioning as well as annually throughout the life of the project. The per-year escalation is another complex and commonly misunderstood topic — well outside the scope of this article — but should include not only the expected increases in energy costs over time, but also upcoming political/industrial assumptions and the general trend toward dynamic pricing, which is destined to significantly increase the value of demand avoidance.
As the business case develops, at least one member of the team should understand the details of avoided cost, including the relevant rate tariff rules, regulations, and restrictions. Aside from a requisite understanding to develop the economic case, a thorough understanding will ultimately lead to significant advantages in bidding work, insights into the value of the various contracting means (including opportunities for advanced performance contracting), and in legally protecting the financial performance of the project through contractual performance obligations.
Swaaley is a licensed professional engineer and renewable energy consultant at Mazzetti Nash Lipsey Burch, San Francisco. He can be reached at scott.j.swaaley@gmail.com.
To truly comprehend avoided cost, you must first understand how electric utilities bill for electricity, specifically time of use (TOU) pricing. TOU rate tariffs bill customers across multiple billing categories, each with an associated metric and rate, and differentiated by time of day and season. These time-based periods are referred to as TOU periods and typically include: winter on-peak, winter partial-peak, winter off-peak, summer on-peak, summer partial-peak, and summer off-peak — as shown in the Table (click here to seeTable). The on-peak designation illustrates that the time period is associated with a region’s highest electrical demands and, subsequently, the highest unit cost.
In addition to the TOU periods, there are two primary charge types: energy charges and demand charges. The differentiation between these two charge types is significant.
Energy charges bill customers on a per-kilowatt-hour (kWh) basis. A kWh is a measure of the energy consumed by a facility in a given period of time. For example, based on the Table, a component of a customer’s July electric utility bill would be summer on-peak energy. This quantity would be the sum of all the energy consumed by the customer in July between the hours of 12:00 p.m. and 5:00 p.m. (neglecting weekends and holidays).
Demand charges bill customers on a per-kilowatt (kW) basis. A kW is a measure of power, an instantaneous measurement of energy consumption. From another perspective, power is to energy (kW to kWh) as speed is to distance (mile-per-hour to mile). Power and speed are instantaneous measurements whereas energy and distance are the latter applied over time.
Demand charges, however, add one additional step. They bill based on the maximum demand in a given TOU period. So while energy measurements accumulate based on actual consumption, much like your odometer would accumulate miles, demand charges are based on the maximum power reached within a particular period (i.e., the maximum point reached by your speedometer). If you’re facility averages a 200kW load in a given period, but some anomaly causes a temporary spike in demand up to 400kW, you are charged for the 400kW demand — even if the anomaly only lasted for a short time.
Considering that demand charges account for as much as 40% of a typical customer’s bill, these charges may seem outrageous, but electric utilities have just cause. While the commodity (energy) is the thing actually consumed, electric utilities are required to have the infrastructure in place to serve your instantaneous needs when they spike temporarily. In 2008, the California Independent System Operator (CALISO) reported that 5% of its required infrastructure was in operation only 0.2% of the time, and that 10% of their required infrastructure was in operation only 0.6% of the time. So, in essence, demand charges fund that inefficiency.
The avoidance of demand charges is an art of sorts, and is becoming the basis for an entire industry of technology. It also represents a significant opportunity for advanced commissioning services. If a particular project can be aligned in such a way that it reliably reduces a facility’s demand, then the financial return can be significant. However, if that avoidance is not realized in the field, it can spell disaster for a project’s economics.