The capability of renewables and the importance of decentralization

This entry is based on the study, “Cost-minimized combinations of wind, solar, and electrochemical storage, powering the grid up to 99.9% of the time“.

Description

To summarize, it is a study of reliable renewable energy systems on a regional scale.  Using simple, standard models of renewable electricity generation in different combinations, it seeks to find optimal mixes of generators and storage to meet target reliability rates.  It is modeled after a region called PJM, on a large-scale (72GW) grid, over a long term (4y) period.  It tests 30%, 90%, and 99.9% reliability, representing the proportion of total electrical demand is satisfied by renewables over the whole 4-year period.  It is also cost-minimized, including externalities and excluding subsidies.

Though it includes only three generation technologies (solar, offshore wind, inland wind) and three storage technologies (central hydrogen, central electrochemical batteries, grid-integrated vehicles), their model yields costs equal to today’s, with triple the output capacity.  Concentrated photovoltaics (CPV), concentrated solar thermal power (CSP), and direct-drive wind (DDW) could provide further cost reductions for generation.  Pumped hydroelectric storage (PHES), compressed air storage (CAS), molten salt batteries could provide further cost reductions for storage.  Fossil fuel backup was used on only four occasions on these optimal models.  Solar thermal could provide further benefits to reliability.  Gasifier-burners could replace fossil backup without adding pollution to the air.

The model does not include additional transmission or growth of demand for electricity, but it does include costs in both 2008 and projected into 2030.  The costs being measured are monetary and include financing, building, maintaining, and operating solar, wind, and storage.  Its insolation and wind data is from the U.S. Department of Energy and the National Oceanic and Atmospheric Association.  A known limitation of this study is the fact that PJM is a large region, meaning it receives more benefit from wind power due to its ability to disperse it further.  Dispersion of wind generators reduces their variability, which means higher reliability.

Results

The model created for the study is called the Regional Renewable Electricity Optimization Model (RREEOM).  Each run evaluates about 1.6 billion combinations of generation mixes, storage power, and storage capacity.  The findings are that the optimal mix depends significantly on storage technology and reliability target.  Central batteries seem to be more suited to photovoltaic, offshore wind, and high power output.  Central hydrogen and grid-integrated vehicles, on the other hand, are more suited to inland wind and high storage capacity.

Taking the average of all three storage technologies, the 90% reliable target is met by increasing generator output to 180% of load, while the 99.9% target increases it even further, to 290% of load.  However, only 9-72 hours of storage are needed for this configuration.  The lower target is met almost exclusively using inland wind power, whose output roughly doubles for the higher targets.  Offshore wind quickly grows to make up about half of total output for 90% and 99.9% reliability.  Interestingly, photovoltaic generators are only used for the 99.9% reliable target, and make up a very small proportion of the total.

The 30% target has the lowest cost at today’s prices, while the other two are higher.  However, in 2030 terms, 99.9% reliable renewable electricity costs the same as today’s electricity, and 90% reliable is actually cheaper.  This implies that a smooth but quick transition is not only ecologically effective, but even cost-effective.  Other regions should be tested, but based on these results, fulfilling 30% of electrical demand with wind appears to be a very wise move, and will not have to be curtailed later.

Spilling versus Idling

There was quite a bit of time during the study’s simulations where electrical output was much higher than demand or empty storage capacity, so it was simply “spilled” (not used or stored).  Because there is little insight to the sources of demand for electricity, it may be possible to relax the requirements for demand, thus further reducing our energy scale.  One way to do this, which I have previously mentioned, is to create an “economic idle process” (EIP).  Rather than spilling excess generation, many productive tasks can be made into “idle processes”.  One possible example of this is recycling: During periods where generation exceeds load and storage, the electricity will be spilled into recycling.  The general criteria for an EIP is a task that is continuous and does not have a critical deadline.

One last note regarding the use of models like this on a bootstrapping VIAAC or other NE: This models costs in dollars; a non-monetary (nonmon) model should be tested to spot differences, though I don’t think it will, since dollars are roughly equivalent to embodied energy.  A nonmon model would use kWh or MJ rather than dollars, turning out EROI figures rather than energy per unit cost.  A bootstrapping NE should, however, use this model to meet at least its 30% target; only after the NE is capable of manufacturing its own generators and storage should embodied energy be used as its cost basis.

Source:
C. Budischak, D. Sewell, H. Thomson, L. Mach, D. E. Veron, and W. Kempton, “Cost-minimized combinations of wind power, solar power and electrochemical storage, powering the grid up to 99.9% of the time,” Journal of Power Sources, vol. 225, pp. 60–74, Mar. 2013.

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