Robin Hood vs Renewable Portfolio Standards

Do Renewable Portfolio Standards Reverse the Robin Hood Concept
 by Taking from the Poor and Giving to the Rich?


English literature has the legend of Robin Hood, who “stole from the rich and gave to the poor.”  Some people liken the graduated income tax as a government Robin Hood program to achieve some of this wealth transfer from the rich to the poor, a form of income redistribution.  In contrast, renewable portfolio standards seem to have the opposite effect of concentrating money in the hands of the few at the expense of the entire community, including the poor.

Most government programs serve a Robin Hood function, taking money from the rich and middle class and providing services to the poor or to the general public.  The Solyndra nightmare is different in that the money is going to the rich, not to the poor or the general public.  The Solyndra nightmare will serve to concentrate the wealth in the country, giving money to a relatively few people.  Given that the money is coming from the general taxes raised by the government, the Solyndra nightmare will concentrate the wealth to a few rich people at the expense of other rich people and the middle class.  The large number of people who don’t earn enough to pay income taxes avoid the wealth concentration aspects of the Solyndra nightmare.

Renewable Portfolio Standards are different.  Everyone pays for electricity, either directly to the utility or indirectly in the form of rent.  The money associated with Renewable Portfolio Standards is paid to a few individuals, often people with ties to the legislators who voted to enact the Renewable Portfolio Standards.  Thus, money is coming out of the pockets of everyone, including the poor who were supported by Robin Hood, and goes into the pockets of the rich, the people who own the projects mandated by Renewable Portfolio Standards, the people whom Robin Hood supposedly robbed.

So, should Renewable Portfolio Standards be considered to be a reverse of the Robin Hood concept?  Do Renewable Portfolio Standards take from the poor and give to the rich?

Ramping–Wind Data from Kodiak, Alaska

A growing concern about renewable resources, such as wind and solar, is that they can ramp down and then back up in a few seconds.  The requirement that electric utilities balance their sources and uses of electricity on a real time basis means that the utility must incur a cost by contra-cyclically ramping up and then down other sources of electricity, whether the other source is generation, load control, or a storage unit.

Determining the cost of the countervailing generation is an accounting nightmare.  An alternative approach is to set a dynamic transfer price, where the dynamic pricing mechanism reflects the degree of imbalance on the network.  A large shortage should result in a high price.  A large surplus should result in a low price.  I first wrote publicly about a dynamic pricing mechanism in “Tie Riding Freeloaders–The True Impediment to Transmission Access,” Public Utilities Fortnightly, 1989 December 21, and recently wrote again about the mechanism in regard to “Pricing Unscheduled Ramping,” released 2011 September 15.  The latter is available on my web site,

Chugach Electric Association (CEA) is planning a 17.2 MW wind farm just outside Anchorage, Alaska.  CEA is interconnected with Anchorage Municipal Light & Power (MLP).  MLP is concerned about the ramping of the wind farm, since the ramping will jerk around the MLP system.  MLP obtained second by second wind generation data from Kodiak Electric Association (KEA) for the 4.5 MW wind farm on the KEA system for October 2010.  KEA operates asynchronously to CEA and MLP but it is one system in Alaska with a wind farm and thus with data about wind farm operations.

During the 2,678,400 seconds that month, the KEA wind farm averaged 1,544 KW of generation.  The wind generators had auxiliary power needs, such that during 535,798 seconds (20.00% of the time), the power flow was negative, that is, the auxiliaries were using more power than the generators were producing, averaging 34 KW of net flow from KEA.  During another 6,852 seconds (0.26% of the time), the generation was zero.  For the 2,135,750 seconds when there was net power flow from the generators, the average net generation was 1,944 KW.  The median value is 988.3 KW, with half of the values being greater than or equal to 988.3 KW and half of the values being less than or equal to 988.3.

I used Excel to count the number of seconds during which the wind farm was within specified blocks.  The blocks were 100 KW wide.  The block containing the most seconds was for the range when the flow was negative, between -100 KW and 0 KW.  The next highest count was for the interval between 4,500 KW and 4,600 KW, roughly the capacity of the wind farm.

In “Pricing Unscheduled Ramping” I present graph of the Excel counts, including a presentation of the mean and median values.  The distribution has its maximum value for the 100 KW of negative value and for the interval between 4,500 KW and 4,600 KW.  This second highest count is roughly the capacity of the wind farm.  In “Pricing Unscheduled Ramping” I also present a cumulative distribution of the number of seconds during the month by the net generation during those seconds, including a presentation of the mean and median values.

Since I was concerned about the amount of ramping that the wind farm was imposing on the system, I then calculated the second to second change in power levels.  The maximum one‑second drop in power generation was 646.1 KW.  The maximum one second jump in power generation was 303.6 KW.  During 1,361,692 one second intervals (50.84% of the intervals), there was no change in the power level of the wind farm.  So, despite some large one second ramps that KEA experienced with its wind generation, most of the time (50.84% of the intervals) the wind farm was absolutely stable with no ramping at all.

Another measure of ramping is the summation of the ups and the downs.  Looking at just the instances when the wind farm ramped up, the amount of ramping was 8,351,700.90 KW.  Assuming a capacity of 4,500 KW, the wind farm during the month of October ramped the equivalent of its full load 1,856 times, or 2.5 times each hour.  Thus, on average, every 24 minutes the wind farms ramped the equivalent of going from zero to full load and back to zero.  Few fossil fired generators would be able to last very long if they had to react to a duty cycle of 2.5 times full load each hour.  Flywheels and batteries are likely to be the only devices that can react to the need for such a duty cycle.

In “Pricing Unscheduled Ramping” I present a cumulative distribution of the number of one second intervals during the month by the net generation ramp during those seconds.  As is apparent from the above discussion, the cumulative distribution had a large jump at a change of 0 KW.

FERC seems to be enamored with the way that Bonneville Power Authority (BPA) charges penalties for imbalances.  Under the BPA approach, the penalty price depends on the amount that the generator is out of balance, the greater the imbalance, the greater the unit charge for the penalty.  The pricing plan in “Pricing Unscheduled Ramping,” out of necessity, presents such a punitive pricing plan for ramping. 

I presented a non-punitive plan for pricing imbalances in “Reply Comments Of Mark B. Lively In Regard To Using Prices Instead Of Penalties For (1) Regulation And Frequency Response, (2) Energy Imbalance, (3) Generator Imbalance, And (4) Inadvertent Energy,” Preventing Undue Discrimination and Preference in Transmission Services, FERC Docket No. RM05-25-000 and RM05-17-000, 2006 September 20.

A non-punitive plan for pricing generation ramping (and generation imbalances) rewards those imbalances that are in synch with the ramping needs of the grid as a whole.  Thus, when the wind generators ramp up while the grid is ramping up, the wind generators would be rewarded for that ramp.   Conversely, when the wind generator is ramping down while the system is trying to ramp up to meet a ramp up in load, then the wind generator should be penalized.

For a more complete discussion of the non-punitive pricing for unscheduled flows of electricity see “Tie Riding Freeloaders”, “Pricing Unscheduled Ramping”, or my reply comments in FERC Docket RM05-17-000.