Forbes & St. Cyr (2004, hereafter "FISC") have provided evidence that the electricity market can be impacted by space weather. Our analysis indicated that the estimated market impact for PJM was 3.7 % or approximately $500 million dollars over the 19 month sample period. Kappenman has taken exception to this estimate and contends that we have exaggerated the magnitude of the problem that space weather poses to PJM. There are four specific issues: (1) he claims that we have ignored relevant literature; (2) he asserts that Dst is not an appropriate proxy for GICs in PJM; (3) he charges that our findings are inconsistent with the impact of the 17 September 2000 storm; and (4) he alleges that our discussion of October 2003 storms is misleading. In our article, we have explained our methodology, multivariate regression analysis, with a particular focus on how it compares to correlation analysis. We have also explained the limitations of our analysis. We noted that "...While the Dstlprice relationship was found to be robust, the precise estimate should be treated with a relatively high degree of caution given that econometric modeling is not an exact science as well as the fact that the measure of space weather may be a poor proxy for GICs" (paragraph 96). We have also noted that additional research using local magnetometer data are needed (paragraph 97). We did not claim that that our findings for PJM are representative of the impact of space weather on other power grids. On the contrary, we noted that ... "Only analysis of other power grids will tell. " (paragraph 97). Kappenman inaccurately asserts that we have indicated that our findings . . . "imply much higher total costs are likely across the US and elsewhere in the world." He also inaccurately asserts that we have claimed that " . . . Dst is the most suited proxy for GIC in the PJM grid.. ." Moreover, he inaccurately refers to our analysis as a correlation study that uses Dst as quasi-binary indicator

SaintCyr, O. Chris

NASA Technical Reports Server

Source of Acquisition 
NASA Goddard Space FligI~t center 
Forbes & St. Cyr (2004, hereafter "FISC") have provided evidence that the electricity market can be 
impacted by space weather. Our analysis indicated that the estimated market impact for PJM was 3.7 % or 
approximately $500 million dollars over the 19 month sample period. Kappenman has taken exception to 
this estimate and contends that we have exaggerated the magnitude of the problem that space weather poses 
to PJM. There are four specific issues: ( I )  he claims that we have ignored relevant literature; (2) he asserts 
that Dst is not an appropriate proxy for GICs in PJM; (3) he charges that our findings are inconsistent with 
the impact of the 17 September 2000 storm; and (4) he alleges that our discussion of October 2003 storms 
is misleading. 
In our article, we have explained our methodology, multivariate regression analysis, with a particular focus 
on how it compares to correlation analysis. We have also explained the limitations of our analysis. We 
noted that "...While the Dstlprice relationship was found to be robust, the precise estimate should be 
treated with a relatively high degree of caution given that econometric modeling is not an exact science as 
well as the fact that the measure of space weather may be a poor proxy for GICs" (paragraph 96). We have 
also noted that additional research using local magnetometer data are needed (paragraph 97). We did not 
claim that that our findings for PJM are representative of the impact of space weather on other power grids. 
On the contrary, we noted that ... "Only analysis of other power grids will tell. " (paragraph 97). 
Kappenman inaccurately asserts that we have indicated that our findings . . . "imply much higher total costs 
are likely across the US and elsewhere in the world." He also inaccurately asserts that we have claimed 
that " . . . Dst is the most suited proxy for GIC in the PJM grid.. ." Moreover, he inaccurately refers to our 
analysis as a correlation study that uses Dst as quasi-binary indicator. 
1. Relevant Literature and the Magnitude of the Problem. 
IEEE Reports. Kappenman cites an IEEE Working Group Report (Bomki, et. al., 1996). This article is 
concerned with the physical damage that GICs can inflict on the power grid equipment. We contend that 
the IEEE published study authored by Girgis and Ko(1992) is the more relevant study. They calculated the 
overheating effects of GIC currents on the performance of two large transformers. The performance of the 
first transformer was temporarily impacted by even relatively low levels of GICs. For example, five amps 
of GICs were found to reduce its allowable load by more than 25 percent (Girgis and KO, figure 9). The 
second transformer they examined was a step up transformer of a more recent design. Its performance was 
only degraded when the GIC level exceeded 40 amps. Given that the transformers in operation on a grid 
represent a mix of various vintages, it would seem that the impact of space weather on the performance of 
the transformers of any given grid is an empirical issue. 
The DOE and FERC Reports. Kappenman questions the credibility of FISC findings by pointing out that 
neither the DOE or FERC studies mention space weather as a factor that contributes to transmission 
congestion costs. Kappenman goes on to claim that the DOE study concluded that the annual economic cost 
of congestion was between $157 and $444 million for PJM, California, New York, and New England. This 
study explicitly states that the energy model it used to generate the estimates ". . . does not represent 
transmission constraints within regions and does not account for these congestion costs in the 
analysis."(DOE, p. 85) Accordingly, this study says nothing about the magnitude of congestion costs within 
PJM, and we are therefore surprised that Kappenman would cite this study. The earlier FERC Powerpoint 
presentation reports that the cost of congestion during the summer months of 2000 and 2001 at 16 
locations. Only one of these locations lies within the PJM control area. The study's authors do not conclude 
anything about total U.S. (or PJM) transmission congestion costs for the summer of 2000 or 2001. The 
figure of $891 million that Kappenman cites as the national estimate for the summer of 2000 apparently 
refers to the sum of the costs for the 16 constraints (the actual sum is $898.5 million). While the FERC 
study does not mention space weather as a cause of transmission congestion, it does point out that high 
demand is not the only culprit given that congestion also occurs during the fall and spring when demand is 
moderate. This is an interesting finding given the seasonal nature of geomagnetic storms (e.g., Russell and 
McPherron, 1973). The FERC study also includes the category of "system conditions" as a factor 
contributing to congestion costs but does not discuss the underlying determinants of these conditions. 
Based on the results reported by FISC, we suggest that space weather be considered one of these 
determinants. 
The PJM Reports. Kappenman claims that PJM issued only five solar magnetic disturbance (SMD) alerts 
over our 19 month sample period. This does not agree with the number of SMD emergencies declared in 
PJMAnnual Reuort on Ouerations 2001. This report indicates that 35 emergencies were classified as SMD 
-- 
in origin in 2000. In 2001, there were 60 (PJM, 2002a, p. 26). What is especially interesting is that the 
https://ntrs.nasa.gov/search.jsp?R=20070018139 2019-08-30T00:58:17+00:00Z
number of emergencies attributed to solar magnetic disturbances was almost twice the number reported for 
the second most prevalent category (PJM, 2001, p. 26). Kappenman has claimed that this reported 
incidence is a gross overstatement. In reaction to that claim we have contacted PJM directly. An email 
response from a representative of PJM's Performance Compliance Department has indicated that " 
Historical data provided by the eSuite Emergency Messages report for Solar Magnetic Disturbance (SMD) 
events list occurrences of the Conservative Action Emergency Procedure, and do not represent other 
transmission actions that PJM may have taken in response to an SMD event. The count of events posted in 
the 'PJM Annual Report on Operations' is the more complete source." In any event, assuming the market 
price accurately reflects real-time operating conditions, then one should expect GICs to impact the market 
outcome to the extent that the performance of the transformers are adversely impacted regardless of 
whether an official emergency is declared - the laws of supply and demand can be expected to operate even 
when there is no formal announcement that the system is degraded. 
Kappenman also objects to our estimate of the cost of space weather by noting that it exceeds the $132 
million in 2000 and $271 million in 2001 of congestion costs reported in PJM Interconnection State of the 
Market Report 2001. However, these reported costs are based on the differences in the locational marginal 
prices, which means that they do not include the monetary impact of congestion that may occur in the "step 
up" transformers at the generating plants. There is no reason why these particular transformers would be 
immune to GICs. When their performance is degraded, less power is uplifted onto the grid than was 
desired. Based on the analysis of Girgis and KO discussed above, the quantitative impact could be 
significant. This of course would represent a shift to the left of the supply curves in Figure 5 of FISC. This 
hypothesis suggests that the locational marginal prices received by generators are higher during periods of 
geomagnetic activity, all other factors being held constant. This is not idle speculation on our part. We have 
performed a preliminary test of this hypothesis using data for PJM's Western Hub. The price at this Hub is 
used as a reference price by PJM in some of its congestion cost calculations (PJM, 2003, p. 106). The 
preliminary results indicate that this price is positively affected by space weather. One interpretation of this 
result is that it is not meaningful to compare the estimated cost of space weather to reported congestion 
costs. A large portion of reported transmission congestion costs are clearly related to terrestrial supply and 
demand considerations. On the other hand, reported congestion costs do not incorporate the impact that 
geomagnetic activity has on the reference prices used to calculate these costs. 
The Bastille Day Storm. Kappenman asserts that the market impact of the 15 July 2000 storm was 
approximately $900,000. This ignores the econometric analysis presented by F/SC that events in the real- 
time market can impact subsequent prices in the day-ahead market. This estimate is as faulty as measuring 
the cost of a hurricane by only counting the costs incurred by uninsured homeowners. Just as insurance 
premiums rise after an unexpected increase in hurricane activity, day-ahead electricity prices rise following 
periods when real-time electricity prices exceed day-ahead prices. 
2. The Use of Dst as a Proxy for GICs in PJM. Kappenman objects to FISC's use of Dst as a proxy for 
GICs in PJM. This is a legitimate concern that was duly noted by FISC. Kappenman has also indicated that 
he knows of no evidence of measurable GICs at K values less than K4. The research reported by Lundby et 
al. (1985) examined the relationship between Kp, and GIC levels on a 500 kV power line in British 
Columbia. Over the course of their sampling, Kp ranged from KO to K7. The researchers successfully 
observed GICs in every hour of the 636 hour sample period except for 38 hours in which there was a 
malfunction in the equipment. A related paper by Boteler et. al. (1991) using this same data reports that 
when Kp was equal to one, the probability that a GIC would equal or exceed one amp was 0.177. The 
probability was more than 0.44 when K,was greater than one. 
3. The Large Dst Event in September 2000. Kappenman has alleged that the price did not respond as we 
have hypothesized to the storm on 17 September 2000. We do not agree. The real-time price one hour 
prior to the peak of the storm was $12.90 per MWh. As Dst declined over the next hour to -201 nT, price 
increased by 55 percent to $20.01 per MWh. From the regression model, the estimated cost of space 
weather for this hour was $9.81 per MWh. We believe that this represents a significant response given that 
the storm occurred on a Sunday and that there was considerable slack in the market as a result. So much so, 
that the real-time price had been equal to zero for several hours earlier in the day. 
4. The October 2003 Storm. Given the volatile nature of real-time electricity prices and importance of 
terrestrial demand and supply conditions in determining these prices, we are not impressed by 
Kappenman's observations concerning the lack of a visually detectable relationship between space weather 
and the average price over any extended time period. As it turns out, the relationship between space 
weather and the market for electricity is more visually discernable if one looks at transmission congestion 
costs. Based on our earlier analysis, we hypothesize that space weather could give rise to transmission 
congestion between PJM's Western and Eastern Hubs. One easily understood measure of this congestion is 
the absolute value of the differences between the two locational marginal prices. Figure 1 depicts the 
values of Dst along with both the day-ahead and real-time measures of these costs over the period 22 
October - 7 November 2003. We believe that the late October spikes in congestion costs that coincide with 
the large declines in Dst are space weather related. One reason for this belief is that these spikes occurred 
during periods in which PJM had implemented SMD conservative operations. There were also similar 
spikes in marginal transmission congestion costs in both the New York and New England power markets at 
approximately the same time. For example, there were large spikes in marginal transmission congestion 
costs in Long Island, New York that coincided with the late October 2003 storms (Figure 2). 
Conclusion. Close inspection of Kappenman's specific objections reveals that they are without merit. His 
reported incidence of SMD emergencies on PJM is not correct. Our preliminary empirical analysis of the 
real-time price in PJM's Western Hub indicates that it is not meaningful to compare the cost of space 
weather with reported congestion costs. Kappenman's objection to using Dst as a proxy on PJM GICs was 
already acknowledged in F/SC as a "less than ideal measure." His assertion that GICs are not present at low 
K values is not supported by the literature. Contrary to his claim, the real-time price did respond as we have 
hypothesized during the 17 September 2000 storm. Finally, the evidence is clear that the market for 
electricity was impacted by the October 2003 storms. 
Kappenman has requested that we provide a table that would report on the costs of space weather for each 
storm that occurred over our sample period. While space constraints preclude such a table in this reply, we 
would be happy to present storm specific impacts in future analyses. 
Kappenman claims that we have missed the point in that the market impact of space weather is simply the 
result of corrective measures undertaken by grid operators and/or operators of nuclear plants. For the sake 
of argument, suppose that Kappenman is correct and that all the market impacts are the result of corrective 
actions by grid operators. In our view, anyone who believes that the magnitude of these costs is not worth 
knowing has missed the point that prudent investments in space weather research have the potential to 
reduce these costs. 
Acknowledgments 
This research was made possible by a grant from the National Science Foundation (Award- # 0318582). 
The authors would like to thank the World Data Center for Geomagnetism in Kyoto, Japan, the Dst stations 
and the persons who derive the index for providing us with the Dst data series. We also wish to thank 
David Boteler for sharing his insights into the GIC literature, and to the staff of PJM for answering our 
questions regarding the incidence of SMD alerts in PJM. 
References 
Bozoki, B.; Chano, S.R.; Dvorak, L.L.; Feero, W.E.; Fenner, G.; Guro, E.A.; Henville, C.F.; Ingleson, 
J.W.; Mazumdar, S.; McLaren, P.G.; Mustaphi, K.K.; Phillips, F.M.; Rebbapragada, R.V.; Rockefeller, 
G.D., 1992, The Effects of GIC on Protective Relaying, IEEE Transactions on Power Delivery, Vol. 11, 
NO. 2, pp.725-739. 
Boteler, D. H., T. Watanabe. D. B. Butler, R. E. Horita, and G.M. Chen, 1991, Prediction of 
Geomagnetically Induced Currents Levels in B.C. Hydro 500 kV System, Solar-Terrestrial Predictions 
Proceedings, Australia, 2,30-41. 
DOE (US. Department of Energy) 2002. National Transmission Grid Study. 
FERC (Federal Energy Regulatory Commission). 2001. Electric Transmission Constraint Study. 
Forbes, K. F., and 0 .  C. St. Cyr, 2004, Space Weather and the Electricity Market: An Initial Assessment, 
The Space Weather Journal, 2, SW100003,doi: 1029/2003SW000005. 
Girgis, R.S. and C. D. KO, 1992, Calculation techniques and results of effects of GIC currents as applied to 
large power transformers, IEEE Transactions on Power Delivery, Vol. 7, No. 2, pp. 699-705. 
Kappenman, J., 2005, Comments on SWJ Paper 2003SW000005 "Space Weather and the Electricity 
Market: An Initial Assessment", unpublished manuscript. 
Gndby, S., B.E. Chapel, D.B. Boteler, T. Watana, and R.E. Horita, 1985, Occurrence Frequency of 
Geomagnetically Induced Currents: A Case Study on a 500 kV Power Line, Journal of Geomagnetism and 
Geoelectricity ,37,1097- 1 1 14. 
PJM (PJM Interconnection LLC), 2002% PJM Annual Report on Operations 2001. 
PJM (PJM Interconnection LLC), 2002b, PJM Interconnection State of the Market 2001. Report of the 
PJM Market Monitoring Unit, June. 
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Market Monitoring Unit, June. 
Russell, C.T. and R.L. McPherron, 1973, Semiannual variation of geomagnetic activity, Journal of 
Geophysical Research, 78, pp. 92-108. 
Figure 1. Space Weather as Measured by Dst and Transmission Congestion Costs between PJM's 
Western and Eastern Hubs, 22 October - 7 November 2003. 
22- 23- 24- 25- 26- 27- 28- 29- 30- 31- 1- 2- 3- 4- 5- 6- 7- 
Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct Nov Nov Nov Nov Nov Nov Nov 
UT 
-Real-Time Marginal Transmission Congestion Costs 
-Day-Ahead Marginal Transmission Congestion Cost 
-Dst 
Figure 2. Space Weather as Measured by Dst and Marginal Transmission Congestion Costs in Long 
Island, New York, 22 October -7 November 2003. 
22- 23- 24- 26- 26- 27- 28- 29- 30- 31- 1- 2- 3- 4- 5- 6- 7- 
Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct Nov Nov Nov Nov Nov Nov Nov 
Date and Hour (UT) 
-Day-Ahead Marginal Transmission Congestion Costs 
-Real-Time Marginal Transmission Congestion Costs 
- Dst 


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