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With electricity deregulation coming to Virginia and many other states, consumers will soon be able to choose their power companies. While the prospect of a time-consuming decision (all those suppliers and rate plans!) may be dreaded by some consumers, far more formidable decisions are faced by power companies as they prepare to move from a regulated industry to a competitive marketplace.
What would be the costs and revenues, for example, of serving new customers by supplying power to the wholesale energy market? Should generating capacity be expanded, and by how much? How much natural gas should be bought, sold, or stored? What futures contracts should be made, and at what prices? What would be the best fuel for a future power plant, considering return on investment, financial risk, environmental impacts, and regulatory constraints?
For help, power companies are turning to private energy management consultants and university researchers. At Virginia Tech, faculty members are investigating various energy management issues through a research center, the Dominion Center for Energy Modeling and Optimization, established in the Pamplin College of Business in 2000 with funding from Richmond-based Dominion, one of the nation’s largest energy producers.
The center, says Cliff Ragsdale, center director and associate professor of business information technology, is currently working on three projects for Dominion Energy Clearinghouse, the company’s arm for buying and selling wholesale electricity, natural gas, fuel oil, and coal.
“Competitive pressures will intensify throughout the power industry,” says Ragsdale. “Deregulation will require energy companies to optimize the use of their physical and financial assets.”
Decision modeling
Doing so may require making complex decisions speedily. “When decisions have to be made very quickly and many, many options exist — and when these options interact with each other in intricate ways — selecting the best alternative can be pretty overwhelming,” says Ralph Badinelli, associate professor of business information technology. That’s when decision modeling and decision-support systems come to the rescue.
“Such systems can sort through the myriad choices, quantitatively evaluate each one, and recommend the best course of action,” says Badinelli, a decision-modeling expert who is applying decision-support systems in two projects for Dominion.
These interactive computer systems combine mathematical models with information databases and a user interface (the part of the system that communicates with the user). A system’s ability to prescribe the best course of action to the user — not just retrieve and display information and perform calculations — is what distinguishes a decision-support system from a traditional information system.
Decision-support systems are being used, for example, by manufacturers and retailers for inventory management, by brokerage houses for commodities and stock trading, and by doctors and other healthcare professionals to assist in diagnosis and treatment. And they have become essential tools for tackling the difficult decisions confronting energy company managers in a deregulated marketplace.
Gas trading
Take the pressure-cooker, price-volatile environment of minute-by- minute gas trading. (Many utilities now have trading floors for buying and selling energy commodities.) Natural gas is becoming the fuel of choice for new power plants, and its purchase and sale can affect a power company’s costs considerably. Outwitting the competition here typically means being more nimble — or as one Dominion trader told Badinelli, “moving my mouse faster than the other guy.”
Badinelli, who is building a decision- support system to help Dominion optimize its gas storage and trading, says the fast pace of gas trading presents a particular challenge for model building. “It’s the awesome complexity resulting from the need for a policy to guide a sequence of decisions toward long-range strategic performance.”
First of all, at a given point in time, “the trader must take stock of current status; make the most accurate forecast of future demand, supply, and spot and futures prices; and select the offers to make or take in the marketplace — how much to sell from which storage facilities, how much to buy and store, what futures contracts or swaps to make.”
The decisions require assessing the expected profitability of the alternative transactions and the associated risks, he says. Generating the status and forecast inputs to each decision requires a continuous data feed of many market factors.
Moreover, “in gas trading, you can’t make each day’s decision in isolation, but have to look at the chain of decisions over time.” The commitments of a current decision will constrain the alternatives available for future decisions, he says, so the trader must determine the best sequence of interrelated actions over time that form an optimal policy.
Sequential decision process models
If it sounds complicated, it is. Sequential decision process models, Badinelli says, are harder to build than those for stand-alone decisions. But they do make it easier for humans to make the right decisions in situations where time is short and knowledge is limited.
“If you don’t use computers, you have to figure it out in your head.” When humans feel overwhelmed by decision making, he says, they tend to use “heuristics” — simple, experimental, trial-and-error techniques — to make a choice. “And when this doesn’t work, they fall back on even simpler methods, such as flipping a coin.”
When people are stressed out by decision making, Badinelli says, they “are more likely to shoot from the hip and apply a myopic policy that will just get them through the day. But following your nose one day at a time will not lead you down the optimal path. The decision you make today not only gets you through today, but also sets you up for tomorrow and the day after.”
Fresh opportunities
The complexities of deregulation, he says, present fresh opportunities for faculty members to apply their knowledge and skills. “It’s a burgeoning area for research and consulting.”
And Virginia Tech has key expertise to offer utilities and other energy companies, says center director Ragsdale. “Research can help us avoid the problems plaguing California.” Specifically, he adds, being able to accurately forecast prices and demand throughout a power grid, for example, helps to ensure adequate power is available where and when needed. Also, “research into financial instruments for risk management and hedging with long-term contracts can help to ensure stability in prices.”
The industry’s restructuring, Badinelli says, also opens up new employment possibilities for graduates of business information technology, financial risk management, and marketing.
These are lively times for energy consumers and producers, Badinelli says. For decision model builders like himself, it’s particularly exciting. Compared to years past, getting enough data is no longer an impediment. The challenge now goes beyond building a good mathematical model and an efficient database, to keeping the human being involved and in the loop rather than letting the computer run the show.
“We have to build interfaces between the system and the user so that what shows up on the screen and on the printout is clearly understandable and useful, and truly supports decision making. We have to remember that the key word in ‘decision-support system’ is ‘support.’”