Large scale energy has proven almost as elusive a Yeti, and perhaps almost as all world saving juicy as the silver bullet for the werewolf or the Holy Grail itself (and not the Monty Python kind).
Energy storage for nearly 15 years has been the energy tech and cleantech version of the ultimate “but-if”. I.E., but if we had that, life would be grand. And untold billions have been expended globally on searching for it, here in the US in the distributed generation and fuel cell boom created in large part by Enron and , and through today’s ARPA-E. Let alone in corporate and national research centers and universities around the globe, and venture capital backed startups galore. Flywheels, superconducting energy storage, solid oxide fuel cells with internal batteries, hydrogen in metal hydrides, high pressure tanks, and activated carbon, super capacitors, regenerative PEM fuel cells, and those running on methanol and ethanol, new battery chemistries with lithium, zinc, sodium, etc, new battery topologies – bipolar this and left twisted plate that, varying chemistries and systems for flow batteries which look like fuel cells and act like batteries, new materials for old electrodes with nanomaterials, graphite, silicon, carbon nanotubes, and let’s not forget better power electronics to mimic the results, as well as compressed air, plain old ice and massive thermal sinks. New and reworked energy storage ideas have proved a dime a dozen. Making them work, let alone scaling them up, costing them down and changing the world? Well, that’s still Yeti-land.
So far we can’t beat the simple cost and expediency of building more power plants, more lines, and burning more natural gas. Let alone beat simply dialing back the usage. Gravity and liquids and energy efficiency are still the ultimate crown jewel of energy storage.
The Problem basically boils down to this. Yes, a myriad of technologies work. Some work well. Some look cheap on the surface. Some even scale up. BUT they don’t get widely deployed. Why?
Probably because at the spear point – at the application that each is best suited for, the costs are higher, the scale up is trickier, the directly applicable market is smaller, and the substitutes relatively better or cheaper or easier than we thought they were.
I’ve taken an only partially tongue in cheek attempt to describe the problem here, in the hope that a firm description of the problem will find us NOT waxing eloquent about the issue 15 years hence, but find it solved by sharp minds. Assuming of course that this is a problem that a better mousetrap can solve. Better mousetrap of course, defined as better and cheaper than the alternatives, and better and cheaper than the value provided, by enough margin to make us get off the dime.
Energy Storage Adoption Problem
Direct Technology Cost x (1.5 to 2 yielding acceptable manufacturing and distribution margins)
Installed Cost x (1 + Service Margin)
= Total Installed Cost
Then where Cost is F(Depr of TIC, O&M Cost, Fuel Cost)
Then TIC / Number of Hours Used Per Unit of Time (Max of Rated Life (Max of Rate Life per Unit of Time)
+ (O&M Cost / Unit of Time) / Number of Hours Used Per Unit of Time
= O&M Cost Per Hour Used
+ Fuel Cost Where Applicable (F of cost of “storing the energy”, e.g. the device literally needs to “buy” and “sell” its energy stored for the time used.
And where Cost /Per Energy Hour Must Be:
Greater than Value of an Energy Hour Used in that Application
Less than the Cost /Per Energy Hour of the Substitutes
On both an LCOE and NPV basis, with adequately large differentials to justify the switching costs
Where DTC is a F(Technology type, Scale of systems, Unit Vol Sold/Unit Time)
Where UVS/Unit Time if F(time and construction and regulatory annoyance for Installed Cost, TC, Rated Life, Actual Field Performance, Availability/performance/cost of substitutes)
And where IC is a F(Scale of systems, Unit Vol Sold/Unit Time) – but a viciously different F than DTC
And where Substitutes can Comprise (Direct energy storage alternatives for that application, Indirect energy storage alternatives at system level that alter the need at that application, downstream energy efficiency projects, downstream demand response projects, downstream production alternatives, infrastructure or capacity expansion and adjustment both at that application and system wide that alters the need at that application, expenditure delays or adjustments in acceptable reliability or reserve margin requirements, and additional energy production both marginal in short term and base load in long term).
And that no subsidies or quotas are factored in.
And if we’ve provided got an articulation and a theoretical formula describing the problem – then it’s time for some to crack it. Peer review requested, fire away. Provided that, no commentary will be read by the author if it does not either contain reference to one of my acronyms, or introduce a new one.