Conflicting demands for complying with EPA’s MATS rule favor a single control technology to deal with multiple types of power plant emissions.
Forecasting New Gas Users
Each year hundreds of oil or electric customers call Boston Gas to ask about fuel-switching. What do they look for?A gas utility can boost sales only one way-by gaining new customers. And in today's slowly growing economy, conservation trends limit growth opportunities. The average household today uses two-thirds the energy of 15 years ago. Commercial and industrial (C/I) customers also conserve. If a gas utility is to grow, a majority of its new customers will likely come from competing fuels, such as oil or electricity.
But which customers will make the switch? Why, exactly, does a business or individual replace its old oil-fired or electric furnace with a gas-fired unit?
Gas utilities can adopt several different approaches to study the reasons for fuel-switching. Among these approaches, a statistical analysis is probably the most efficient. It doesn't cost as much as a customer survey, which requires the utility to design, print, and mail questionnaires, and then follow up with long telephone conversations, focus groups, and so forth. A successful statistical analysis can also create a mathematical model suitable for forecasting gas demand and evaluating the costs and benefits of advertising and marketing strategies. That's exactly what we've done at Boston Gas. We have developed a forecasting model that estimates the annual inflow of new, fuel-switching C/I customers.How Many Will Ask?
Every year hundreds of managers and owners of C/I establishments contact Boston Gas about converting existing oil-fired or electric equipment to gas. We wanted to know whether we could predict customer behavior-both for intial inquiries and for actual equipment conversions.
To find the answer, we modeled a number of these customer contacts or applications using discrete choice analysis. We developed models based on 1986-1992 historical data, using 1993 as the test year. All potential customers were divided into three classes: "small" would use less than 500 million cubic feet per year (Mcf/yr); "medium," between 500-5000 Mcf/yr; "large," more than 5000 Mcf/yr. We studied each establishment class separately to account for differences in economic behavior between small and large organizations.
Our goal was to understand how fuel prices, the state of the local economy, and the company's marketing activities would affect the inflow of applications for switching to gas. We also tested the effect of environmental regulation on fuel-switching activity by introducing a special categorical variable. This variable reflects major changes in environmental policy from 1986 to 1993. Starting in 1988, customers began to show significant concern about the condition of underground oil tanks. Many businesses and organizations began to consider installation of gas-fired equipment as a way to avoid potential liability from leaky oil tanks. The Clean Air Act (1992) heightened the pressure to replace oil burning equipment with natural gas.
All in all, we found our models statistically reliable. Table 1, covering an eight-year period, shows that the model estimates come very close to the actual numbers of customer contacts. The statistical analysis revealed that small- and medium-sized customers make more inquiries about fuel-switching when the company raises its level of spending for advertising. Among those two classes, environmental concerns