Fed. Energy Regulatory Comm'n v. City Power Mktg., LLC, Civil Action No. 15-1428 (JDB)

CourtUnited States District Courts. United States District Court (Columbia)
Writing for the CourtJOHN D. BATES United States District Judge
PartiesFEDERAL ENERGY REGULATORY COMMISSION, Plaintiff, v. CITY POWER MARKETING, LLC, and K. STEPHEN TSINGAS, Defendants.
Decision Date10 August 2016
Docket NumberCivil Action No. 15-1428 (JDB)

FEDERAL ENERGY REGULATORY COMMISSION, Plaintiff,
v.
CITY POWER MARKETING, LLC, and K. STEPHEN TSINGAS, Defendants.

Civil Action No. 15-1428 (JDB)

UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA

August 10, 2016


MEMORANDUM OPINION

City Power Marketing, LLC, an energy-trading firm founded by K. Stephen Tsingas, engaged in "virtual trading" in wholesale electricity markets. Virtual traders do not actually supply or receive electricity but instead stake out market positions that are effectively bets on how electricity prices will change over time. In other words, they engage in a kind of arbitrage. And their efforts are generally thought to improve the overall efficiency of energy markets.

According to the Federal Energy Regulatory Commission (FERC or Commission), however, in July 2010 City Power engaged in a series of manipulative virtual trades that hurt the market while generating more than $1 million of profit for City Power. In essence, City Power found a way to place trades that had no risk of earning or losing money on the basis of price changes but that nonetheless triggered a financial credit for City Power from the market operator. After a lengthy investigation, FERC concluded that these trades constituted a fraudulent scheme that violated the Commission's Anti-Manipulation Rule, 18 C.F.R. § 1c.2. FERC also concluded that by failing to reveal the existence of certain archived instant messages during the investigation, City Power had violated the Commission's Market Behavior Rule 3, 18 C.F.R. § 35.41(b), which requires truthful communications by parties subject to FERC's authority. FERC ordered City

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Power to disgorge its profits and assessed penalties of $15 million on City Power and Tsingas. Disputing their liability, City Power and Tsingas did not pay. As provided for in the Federal Power Act, FERC therefore filed this action seeking an order affirming its penalty assessment.

City Power and Tsingas—whom the Court will collectively call "City Power," unless context indicates otherwise—have moved to dismiss, arguing that FERC's claims under both the Anti-Manipulation Rule and Market Behavior Rule 3 fail as a matter of law. City Power also argues that this case should be treated like a normal civil action subject to the Federal Rules of Civil Procedure, not a summary review of agency action. The Court largely agrees with City Power on this latter point, and will follow the normal course of district-court adjudication. But the Court disagrees that FERC's claims are unsound. Assuming the truth of FERC's allegations, as the Court must at this stage, FERC has stated plausible claims under both the Anti-Manipulation Rule and Market Behavior Rule 3. City Power's motion to dismiss will therefore be denied.

BACKGROUND

I. PJM'S WHOLESALE ELECTRICITY MARKET

This case concerns allegedly illegal trading in the wholesale electricity market run by PJM Interconnection, LLC (PJM). PJM is the independent, nonprofit Regional Transmission Organization (RTO) that administers the electric grid in a 13-state region that extends from North Carolina to New Jersey to Illinois and includes the District of Columbia. As part of administering the grid, PJM operates a wholesale electricity auction of the sort recently described by the Supreme Court:

These wholesale auctions serve to balance supply and demand on a continuous basis, producing prices for electricity that reflect its value at given locations and times throughout each day. Such a real-time mechanism is needed because, unlike most products, electricity cannot be stored effectively. Suppliers must generate—every day, hour, and minute—the exact amount of power necessary to meet demand from the utilities and

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other "load-serving entities" (LSEs) that buy power at wholesale for resale to users. To ensure that happens, wholesale market operators [such as PJM] obtain (1) orders from LSEs indicating how much electricity they need at various times and (2) bids from generators specifying how much electricity they can produce at those times and how much they will charge for it. Operators accept the generators' bids in order of cost (least expensive first) until they satisfy the LSEs' total demand. The price of the last unit of electricity purchased is then paid to every supplier whose bid was accepted, regardless of its actual offer; and the total cost is split among the LSEs in proportion to how much energy they have ordered. So, for example, suppose that at 9 a.m. on August 15 four plants serving Washington, D.C. can each produce some amount of electricity for, respectively, $10/unit, $20/unit, $30/unit, and $40/unit. And suppose that LSEs' demand at that time and place is met after the operator accepts the three cheapest bids. The first three generators would then all receive $30/unit.

FERC v. Elec. Power Supply Ass'n, 136 S. Ct. 760, 768-69 (2016). The clearing price at a particular location, or "node," on the PJM grid is called the "locational marginal price" (LMP).

PJM operates a so-called "dual settlement market," meaning that it runs two rounds of bidding for each operating day. It first runs a "day-ahead market," which "allows market participants to secure prices for electric energy the day before the operating day and hedge against price fluctuations that can occur in real time. One day ahead of actual dispatch, participants submit supply offers and demand bids for energy. These bids are applied to each hour of the day and for each pricing location [i.e., node] on the system." FERC, Energy Primer: A Handbook of Energy Market Basics 95 (Nov. 2015). PJM takes all of the bids and offers, crunches the numbers, and determines what the clearing price—the "day-ahead LMP"—will be at each node. Generators who offered to supply energy for less than the clearing price are committed to supply that energy and are paid the day-ahead LMP; buyers who bid to purchase energy for more than the clearing price are committed to their purchases and pay the day-ahead LMP. Id.

The next day's actual supply of and demand for electricity, however, might be different from what the day-ahead market presumed. A generation unit might unexpectedly fail, affecting supply, or the weather might be much different than predicted, affecting demand. PJM therefore

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also runs a "real-time market" designed "to meet energy needs within each hour of the current day." Id. (The real-time market is also sometimes called the "spot market" or "balancing market.") As the name suggests, offers and bids in this market are made in real time. "Real-time LMPs are calculated at five-minute intervals based on actual grid operating conditions as calculated in PJM's market systems." Id.

PJM's wholesale market is not restricted to those engaging in "physical transactions," i.e., those who will actually deliver or actually receive electricity. Traders who neither have nor want actual megawatts can engage in "virtual transactions."

A virtual transaction does not require generation to be dispatched or load to be served. Rather, it allows a market participant to arbitrage day-ahead versus real-time prices by either purchasing or selling a position in the day-ahead market, and then doing the opposite in an equal volume at the same location in the real-time market, thereby taking no physical position when the system is dispatched.

City Power Mktg., LLC, 152 FERC ¶ 61,012 at P 17 n.38 (2015) ("Penalty Assessment Order").

Suppose, for example, that a trader believes that the real-time LMP at a particular node will be higher than the day-ahead LMP. (Perhaps the trader has reason to believe that the temperature there will be higher than most forecasts predict, meaning increased air-conditioning use and hence increased power consumption.) The trader makes a virtual bid in the day-ahead market to buy 100MW at $25/MW. If his bid clears, then to offset his purchase, he must also sell 100MW at the same node in the real-time market. If his prediction turns out to have been correct, and the real-time LMP rises to $30/MW, he makes a profit: he "bought" 100MW for $2500 in the day-ahead market and "sold" it for $3000 in the real-time market. Likewise, a trader who correctly predicts that the real-time LMP will be lower can conduct a mirror-image virtual transaction, promising in the day-ahead market to supply 100MW in exchange for $3000, and then buying those 100MW in the real-time market for only $2500. These sorts of arbitrage transactions—the first is called a

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"decrement bid," the second an "increment offer"—are good not only for the traders but also for the market as a whole. Virtual trading encourages price convergence between the day-ahead and real-time markets, and provides price discovery, market liquidity, and increased competition. Penalty Assessment Order at P 20 & n.48; see also PJM Interconnection, Virtual Transactions in the PJM Energy Markets 22-31 (Oct. 12, 2015) (explaining how virtual transactions help mitigate both buyer- and supplier-side market power).

This case centers on another, more complex transaction called an "Up-To Congestion" transaction (UTC). Whereas the virtual transactions described in the preceding paragraph revolve around price changes at a single node, a UTC is concerned with the changing spread of prices between two nodes. It works like this: The trader selects a "source" node and a "sink" node, specifies a number of megawatts, and bids a maximum amount by which the day-ahead LMP at the sink might exceed the day-ahead LMP at the source. (The price difference correlates with the transmission congestion between the nodes, hence the name "Up-To Congestion.") If the actual day-ahead price difference is less than the trader's bid, the UTC transaction clears, and the trader must pay the day-ahead price difference times the number of megawatts specified. The trader will then receive the real-time price difference between the nodes (times the number of megawatts). Thus, if the price...

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