It’s about load. In our long-term reliability assessments, we tend to think of peak demand as a fixed quantity. We adjust it up for new loads such as EV growth, or down for demand response and DER growth, and we adjust it for weather. We consider the variability from wind, solar and hydro during that high demand period, perhaps assigning a capacity value to different weather-related resources. And when we consider adding a gas peaker to the mix to ensure we can meet peak demand, we may use a planning reserve margin (eg 15%) to give us a cushion of safety. Utilities planning for high penetrations of wind and solar may even be conducting loss-of-load expectation analyses using data from multiple weather years to examine what happens to resource adequacy when it’s a low wind/high hydro or low hydro/high solar year. In any case, we take this fixed quantity of peak demand and we plan for it and make investment decisions based on it.
We have treated load as price inelastic. This isn’t necessarily wrong – it reflected consumers’ behaviors. When I turn on the light or the stove, I want that service – now. And for services that could be delayed – well, modest price spreads between peak and off-peak periods may save a modest percentage of my electricity bill, but the absolute savings is so small compared to say, my Starbucks habit, that it does not motivate me.
Big data and artificial intelligence are changing all of that. My Google Nest thermostat knows enough about my comfort needs that Google could use my home as part of a larger aggregation and provide regulating reserves without me even knowing it. Or they could provide peak shaving on a hot summer day and reduce peak demand on the grid. I’ll also point out that I paid them $250 so they could have this capability (instead of buying a $50 thermostat from the local hardware store).
Electrification of the transportation and heating sectors is the second big driver for change. Our EV more than doubled our household electricity consumption. These new loads have significant power demands and they may lead to an increase in system peak demand. But importantly, they also have inherent flexibility. The power industry is aware of and eagerly anticipating the grid integration benefits from controlling EV charging, water heating and space conditioning.
What does all this have to do with renewables? Some utilities are interested in future systems with very high penetrations of wind, solar, hydro and storage. Planners already know there is significant difference between a good and bad hydro year. Add the permutations of good and bad wind and solar years to that, plus the climate change-induced extreme weather events, and there will be a lot of uncertainty of output levels of wind, solar and hydro during system peak for any given year. The industry will need to carefully examine the costs and benefits of a new gas peaker or a new storage facility and determine how much over-building of the system is appropriate and acceptable. But it’s not a stretch to imagine a future where on that hot summer afternoon, system peak will be determined not by peak demand, but by however much wind, solar, hydro, and other generation (storage, thermal, interconnections, etc) happens to be available. And it will be the price elasticity of load that determines which loads are served and which are compensated to provide peak shaving. So instead of thinking of demand as a fixed quantity, with various generators meeting that demand, we would think of total generation as a fixed quantity, based significantly on the weather that day, and various loads being served or not served. Or one could think of loads as negative generators.
This is already being introduced. Portland General Electric recently proposed a $1/kWh peak time rebate. Baltimore Gas & Electric has a $1.25/kWh peak time rebate. This level of savings becomes much more motivating – it gets closer to pricing on toll roads (or my Starbucks habit).
Price elasticity of load turns resource adequacy on its head. The loss-of-load-expectation metric of one day in ten years is no longer meaningful because you never have a loss-of-load event if all load has price elasticity. How the resource adequacy concept will evolve remains to be seen. There will always be some loads (hospitals, military facilities, etc) that are price inelastic and need firm power; on the other hand, those may be the same types of loads that already have backup generators. Behind-the-meter storage may also become a more attractive option for consumers.
Load is going to be a key resource in the future. Our models and analysis techniques will have to evolve to reflect that. And it will help us solve a lot of the problems that many are concerned about, as utilities move to very high levels of renewable energy.
Justin Sharp says
Great piece Debbie. As I’m sure is no surprise to you, I’m largely in agreement. You’ve heard me say many times that one reason wind and solar forecasts are so much harder to produce than load forecasts is that weather modulates loads but it defines wind and solar generation. Translating that statement into management of the system it becomes apparent that as renewable component of the system increases, diurnal load variability becomes less important, and weather impacts on resources serving load (and the weather driven component of it) become critical. Using price elasticity to move LOAD around resources will be a very effective tool to manage this and cannot come too soon. I’m very encouraged by what I’ve read above about PGE and BG&E. It has to be enough to matter to the customer. The $900/MWh prices at mid-C (the land of masses of hydro capacity) this week make it clear that offering $1/kWh peak time rebates is likely win all around.
Gary Nakarado says
It’s about time! Thanks Debbie…
Yael Gichon says
Great article Deb! Thanks for sharing.
Rob Gramlich says
Nice. Perhaps LOLE needs to be “ILOLE” where “I” is “involuntary.” I think ILOLE would still be a positive number in short and long run equilibrium.
Barbara O'Neill says
Good post, Debbie. I was just saying that to stakeholders in Mongolia, and Guyana, and west Africa. Using technology available on a cell phone to shift load should be the leapfrogging I’d like to foresee in developing countries. I am finding that their immediate jump (if away from coal and nukes) is to want to install battery storage. It’s getting the sexier press. But load should thoroughly be explored before they overbuild BESS. That’s my two cents.
Erwin Heuck says
The requirement for overbuild to manage reliability is the key discussion. Should the overbuild be on the distribution end or the transmission end? What level of overbuild is needed to manage reliability expectation?
Hans Hyde says
Agree with your point Barbara O’Neil, but having watched the African space for many years hoping the digital “leapfrogging” phenomenon would happen there before in “The West” – burdened as it with entrenched interests, it has not come, even though it should have.
The simplest explanation, one that we are currently witnessing in northern MISO, the flexibility of available (or accessible) natural gas (& LNG) with combined cycle plants within the BESS has been artificially excluded from the “solution” package. South Africa – which effectively calls all the shots for the Southern Africa Power Pool in the BESS, ESKOM – dominated by coal, and Sasoil’s need to control the liquids & gas supply chain vertical for its Gas to Liquids program, all combined kept the CCGTs off the table. And now, not surprisingly, load shedding has returned.
And this has/is happening in the Northern Great Plains states also.
An entire slew of “digitally” enabling technology came to the African energy space, largely home grown… micro-financing, digital banking, pay-as-you-go meters, even development of regional digital marketplaces to inform producers [of agricultural products] where they could get the best price for their products. But as Debbie Lew rightly points out indirectly about emerging markets, pennies matter in all transactions, and they drive innovation. The same could not be said about the US… the real economics of “Starbucks habits” are not considered on equal basis with the real economics of “energy consumption habits”.
Imagine this…. some guy, let’s call him the “Disruptor”, stands outside a Starbucks, offers the $5 Starbucks product for $4.75 and calls it “Solarbucks”. A customer sees the “savings” and asks for a “Solarbucks”. The Disruptor takes his customer’s money, walks into Starbucks, behind the counter, uses their machines, products, maybe even orders the Starbucks employee to prepare it, etc., then walks out and hands the customer his “Solarbucks”. The customer loves his “Solarbucks” and tells the Disruptor, “this is better than Starbucks! See you tomorrow!” The “Solarbucks Innovator” pockets the $4.75 and walks away.
This is largely the extent of how digital innovation in the electric space has “leapfrogged” the BESS in the US.
Robert Mackay says
52PWh world biosperic annual energy ( Delft Unv rpt 2018)
3PWh presently utilised in large scale hydro worldwide
USA fossil fuel generation presently at 3PWh
Similiar figures for China.
94% of the world hydrospheric energy is non utilised
If a disruptive technology entered this space at say 20-30% to productively harness this system as a Run of River solution then-
P=0.5pAV3*h or 4.8kWs per meter step becomes possible
Einstein said “we cannot solve todays problems with the same thinking that we used when we created them”
You guys are on the right track with base load. Solar and wind are time shift 2nd tier energy provision characterised by a need for either diesel back up or battery storage.
Until now a suitable technology answer has not existed to this base load being met at scale although traditional hydro is generated at 2c/kWh
New hydro using small hydrocyclone technology bypasses these shackles