Average at your own risk. The pitfalls and perils of average utility charges

demand charges impact TOU rates energy savings kw engineering energy sustainability consultants

Average at your own risk. The pitfalls and perils of average utility charges

Averages hide things, blending together the highs and the lows arriving at something in the middle. But the end result is a product that doesn’t accurately reflect the diversity of the whole which can be a BIG problem when it comes to estimating savings for an energy efficiency project.

Great examples that avoid problematic averages are the TMY3 and CZ2010 weather data sets. It may seam reasonable to average daily weather data based on historic norms and make that a weather data set, but in practice, doing so would ignore hot streaks and cold snaps – events that test the design limits of HVAC systems. The developers of the TMY3 and CZ2010 datasets realized this and instead avoided averaging to develop standard data sets that reflects the variability of the weather.

People know averages may be a good idea when it comes to figuring out how many bags of Snickers or Twix to stock up on for Halloween, but we certainly know that such averages don’t hold up when the stakes are higher. Like, perhaps, spending $100K on exterior lighting upgrade or dropping $500K on a new chiller.

I’m often surprised by how many audits and energy analyses I review still rely on average utility costs. These projects focus on investment grade projects – significant outlays of capital – and rely on savings calculations that are often too simple.

My Beef with Average Utility Costs

Average utility costs are calculated per unit energy (e.g. kWh, therms, pounds, MMBtu, etc.) by taking the total utility spend and dividing it by the total energy used. This averaging process strips obscures how energy cost components change hourly or seasonally. Unless your tariff lacks seasonal time-of-use components (like for some of my clients on WAPA power) or if the systems runs continuously and will have a uniform continuous energy reduction (e.g. like a server closet uninterruptable power supply) – this will hide the real energy savings and could make some projects look better than they’d otherwise be. A kWh saved on a winter evening has a different cost than a kWh saved in the middle of an August afternoon.

An Exterior Lighting Example

As you might know, I’m kind of a lighting geek – so let’s start there.

Consider a hypothetical client considering a large upgrade of parking lot and pathway lighting. They plan to replace their existing metal halide luminaires with new LED luminaires with bi-level vacancy sensor. All-in-all, it’s a fairly typical energy efficiency measure you’ll find in a lot of our audits. If the customer can achieve a 50% reduction in exterior lighting load and the lighting operates 4,100 hours per year (a typical utility assumption in California), we can calculate the energy savings easily. We could go a step further and layer on the bi-level vacancy sensing by assuming the bi-level lighting will further reduce the lighting load by an additional 50% (now 75% of baseline) for most of the night, when the parking lot is vacant. It’s pretty easy to arrive as some big energy savings this way.

For a typical customer in PG&E territory, the average utility cost, is typically around $0.22/kWh. That cost factors in the energy cost, the demand charges, and usually a sundry of other, much smaller changes. As of this writing, the evenings generally fall in the off-peak and part-peak periods (part-peak from 6:00-9:30 PM and off-peak from 9:30 to 8:30 am the following morning). Those rates are much closer to $0.10/kWh to $0.12/kWh.

Where’d that extra $0.10 go? Part goes to the fact that the peak period energy charges (around $0.15/kWh) weight the average cost slightly. But the big difference is the absence of the demand charge.

What are demand charges?

Demand charges are utility charges for providing power capacity. For most PG&E tariffs today that overnight energy consumption occurs outside of the Peak, Part-Peak, and Maximum Demand charge windows. Changing out or shutting off lighting that doesn’t overlap with the time of the billing period when those demand charges are accrued means that those savings won’t result in a demand dollar savings.

Scheduling oriented projects will echo this exterior lighting project since scheduling opportunities often happen on outside the peak, part-peak, and maximum demand charge events in any given billing cycle.

Trickier Applications of Demand Charges

Other energy efficiency opportunities are weighted seasonally and by time of day. A high-efficiency chiller project (e.g. high kW/ton) will likely have a big impact on the maximum demand charge and both the peak and part-peak charges. At the same time — a chiller retrofit to improve part-load performance – – might only occur at mild loads and may not have significant impact on the demand charges. In either case, these projects don’t lend themselves to specifically thinking about the time of day the system is active, but under which conditions the system might cause or overlap with the demand charge components.

Demand and the binned approach

When we perform small heating, ventilation and air conditioning (HVAC) system calculations, we often use bin-analyses. A bin-analysis groups (or “bins”) similar performance metrics together – in the case of HVAC systems often by outside air temperature. Thus, we might perform a series of calculations for each every 2°F range of outside air temperatures. During the process of binning the data, it’s easy to assign an energy cost to each hour of the year and use our reference weather data set to great a bin that includes not only the number of hours in each temperature bin but also the typical electric cost in a temperature bin. If we expect the system to impact the demand charges a building experiences – we can factor in demand charges into each bin-period.

Demand and the 8760 approach

When an energy calculation relies on an hourly model (whether a custom calculation or an energy model that does the number crunching behind the scenes) – it’s usually a couple of extra columns or a few minutes programming in the details of the energy tariff so start seeing far more accurate time-of-use dollar savings. There is a setup period to get the tariff structure dialed in, in my experience, California’s tariffs haven’t changed structure in the last 10+ years. Updating the hourly tariff structure is usually as easy as entering 10-15 new values that define the tariff and relying on a spreadsheet to propagate those changes to the rest of the year.

When unpredicatable demand charges make savings unpredictable

Even if your energy calculation does everything right and you’ve defined the tariff accurately – a customer may find they still fall short of their dollar savings target. Where this happens, I’ve found that the underlying assumption for the calculations are wrong. If in the peak demand charges are unpredictable, any peak demand savings will be unpredictable.

We had a very forward-minded customer who was continuously adding new energy efficiency and self-generation capabilities to their buildings. One of their improvements included fuel cells. Unfortunately for that customer, their part of the grid was prone to minor voltage sags and somewhat frequent power outages. Based on their utility interconnection agreement, when the building lost utility power, the fuel cells had to shut down. Fuel cells do not like short shut downs. So often a brief outage of a few seconds would result in a three-hour shut down for their on-site generation system. During that three-hour window, their monthly maximum demand charge would be set – and often either their part-peak or peak demand charge, to boot. Because the power outages were difficult to predict, it was similarly difficult to predict whether an energy efficiency measure would help reduce that demand charge reliably.

How to avoid surprises on the bill

To avoid surprises like the one above, it’s a good idea to review a client’s electrical interval data and see if there are inconsistent periods of the peak demand. When a project is likely to have a significant demand impact (generally constituting more than half of the associated utility dollar savings), I will map the utility bill demand charge components (usually only shown on the paper bills) with the interval data to identify when charges were accrued historically and double-check whether those charges will be affected by my proposed improvement.

So, you can see simplifying doesn’t always lead to a preferred savings outcome. Navigating the increasing complex and changing utility charge landscape takes a great deal of energy savvy. When evaluating potential savings impacts of projects remember to account for TOU and operating conditions to get a better picture of your payback before you drop thousands or even millions of dollars in retrofits. If you have any questions about an energy saving project or need help understanding your utility rates, contact us anytime.

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