Establishing the Economic Impacts of

Kevin F. ForbesResearch Supported by the United States National Science Foundation

Did Geomagnetic Activity Challenge Electric Power Reliability During Solar Cycle 23? Evidence from the Balancing Market in England and Wales

Kevin F. ForbesThe Catholic University of AmericaWashington, DC 20064 USAForbes@CUA.edu

O.C. St. CyrDepartment of PhysicsThe Catholic University of Americaand NASA-Goddard Space Flight Center

32nd USAEE/IAEE North American ConferenceAnchorage, Alaska

July 2013

Research Supported by the National Science Foundation

The Basic Structure of the Power Industry

Electricity is produced at relatively low voltages but is generally transported at high voltages so as to reduce transmission losses

Source: U.S.-Canada Power System Outage Task Force

Retail expenditures on electricity were approximately $370 billion in 2011, the most recent year for which data are available.

The economic contribution of this industry is much higher than this because electricity is critical to almost everything we do and thus gives rise to a very large “consumer surplus”

What is the Economic Value of Electricity?

Area “A” Represents consumer expenditures onelectricity

Area “B” represents the consumer surplus that society receives from electricity

B

A Hypothetical Demand for Electricity

Quantity of Electricity

Price

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Q1

A Hypothetical Demand Function for Electricity, Expenditures on Electricity, and the Consumer Surplus from Electricity.

While the wholesale price of electricity may be about $40 per megawatt-hour, the economic literature reports that the “value of lost load” is about $5,000- $10,000 per megawatt-hour

Indicative of the high value of “lost load,” it is not unheard of for the real-time price of electricity in today’s restructured electricity industry to be close to $1,000 per MWh.

Because the consumer surplus from electricity is very large, electricity blackouts are very costly to society

The Day-Ahead and Real-Time Reference Prices of Electricity in the New York Power System, 1 – 31 January 2005

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The power system is almost exclusively an alternating current system

There is a target level of system frequency, i.e. a desired level of voltage and current oscillations each second.

The desired level of system frequency is 50 times per second in most of the world and 60 times per second in North America.

Maintaining the desired levels of frequency requires that electricity supply equal demand at all times, not just on average.

Power systems have very stringent stability conditions

System frequency falls when demand exceeds supply and rises when demand is less than supply. In either case, reliability is compromised.

System operators offset these electricity imbalances by dispatching balancing power. These deployments can be large in magnitude

System Frequency

The Dispatch of Balancing Power in the Power Grid that Serves England and Wales, 1 October – 30 November 2003.

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System Frequency in the UK Power Grid, 12 September 2011.

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Geomagnetic Storms and the Power Grid Geomagenetic storms are disturbances in

the Earth’s magnetic field that are largely caused by explosions in the Sun’s corona that spew out solar particles.

Solar Activity and the Earth’s Magnetic Field

Source: NASA

Geomagnetic Storms and Power Grids Power Grids are vulnerable to

geomagnetic Storms because the power transmission grid acts as an ‘‘antenna’’ of sorts, picking up geomagnetically induced currents (GICs).

These currents have the potential to impair the performance of transformers

Geomagnetically Induced Currents and Transformers

GICs in the UK Power Grid, Oct 30 2003

Source: Alan Thompson of the BGS

The Peer Reviewed Literature GICs have been found to be statisticallyrelated with various measures of real-time

operations in 12 power grids including PJM, NYISO, New England, England and Wales, New Zealand, Australia, Ireland, and the Netherlands.

It may also be relevant to note that the Hydro-Quebec system collapsed in 1989 during a geomagnetic storm.

The relationship is fairly robust:

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The Day-Ahead and Real-Time Reference Price in the New York ISO, January 1-31 2005

The Rate of Change in the Geomagnetic Field and the Real-Time Reference Price in the New York ISO, January 1-31 2005

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Net Imbalance Volume (NIV) – the quantity of electricity that the system operator uses to balance the system.

Positive NIV values for a market period indicate that the system was “short”

Negative NIV values indicate that there was excess supply

The Dependent Variable in this Analysis

A Histogram of the Net Imbalance Volumes in the Power Grid that Serves England and Wales, 11 March 2003 – 31 December 2004

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Net Imbalance Volume (MWh)

NIV tends to benegative becausemarket participants are significantly penalized for being ‘short”

The Imbalance Prices in the Power Grid that Serves England and Wales, 1 October – 30 November 2003

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Ambient Temperature

The GIC proxy

Explanatory variables that reflect expected operating conditions such as forecasted load, the level of scheduled generation relative to forecasted load, and scheduled imports and exports

Binary variables for the hour of the day and the day of the week

The Explanatory Variables

 The model was first estimated using ordinary least squares. A number of the coefficients are highly statistically significant.

 Unfortunately, the OLS residuals are highly autocorrelated which renders the results open to question.

Results:

The Autocorrelations in the OLS Residuals

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The shaded area is the 95% confidence band

The goal of this estimation is to achieve “white noise” in the residuals.

There is no reason to have any confidence in the estimates in the absence of white noise,

Because of the OLS Autocorrelations, an Autoregressive-Moving Average (ARMA) Process was Modeled.

The Autocorrelations in the ARMA Residuals

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Half Hour Lags

The shaded area is the 95% Confidence Band

The GIC/NIV relationship is highly statistically significant.

The relationship is highly contingent on terrestrial based system conditions.

In short, the GIC/NIV relationship is more robust the smaller the level of available generation relative to load.

The ARMA Results

A Histogram of the Net Imbalance Volume Attributed to GICs, 11 March 2003 through 31 December 2004

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Net Imbalance Volume Attributed to GICs (MWh)

The out of sample evaluation period: 1 Jan – 31 March 2005

The control area was expanded to include Scotland on 1 April 2005.

An out of sample forecast was performed

The Net Imbalance Volumes in England and Wales, 1 January 2005 – 31 March 2005

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Predicted and Actual Net Imbalance Volumes in England and Wales, 1 January – 31 March 2005

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The forecast is less accurate if the estimatedeffect of the GICs is removed from the forecast equation

The research reported here strongly supports the view that space weather had electricity market effects during solar cycle 23 even though there is no published evidence of a major space weather induced blackout.

The research also indicates that electricity market imbalances have a degree of predictability. Thus, it may not insurmountable for a system operator to forecast the terrestrial based vulnerability of its power system.

Such forecasts may have the potential to enhance reliability even when the role of space weather is minor.

Conclusions