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96 Historically, overestimates were eventually corrected by growth in demand, with the assumption that excess capacity could be sustained by the rate base and would be absorbed by naturally occurring increases. In the current market climate, an underestimate is likely to lead to under capacity, resulting in diminished quality of service including localized brownouts, blackouts, and distortion in capacity investment needs. Overestimates could lead to the authorization of excess capacity, which might not be sustainable in the rate base. Given the interest in deregulation, with associated unbundling of electricity supply services, tariff reforms, and increasing reliance on privatesector providers such as energy service providers (ESPs), accurate demand forecasting is of evergreater importance. Chapter 9 EnergySector Fundamentals: Economic Analysis, Projections, and Supply Curves 9.5 Forecast Demand and Supply Calculations rapidly rising energy prices, emergence of alternative fuels and technologies, demographics, and industrial technologies, more sophisticated demand models have been employed by utilities and government agencies. Penalties for underestimation have been overcome in the past, typically by resorting to rapid construction of plants such as simple or combinedcycle gas turbines12 to meet emerging shortterm demand. This technique was successful in large measure because of the relatively low price and easy access to fuels such as natural gas. Power plant construction periods, including needs assessments, financing, approvals, and physical construction, may vary from four to 12 years for thermal and fossil plants. Shorter construction periods occur for gasfired generation, which may be needed for peak demand and load following. In the case of geothermal plants, the time to build and install the power plant can be less than two years, once the well field has been developed. As a result, utilities typically forecast demand and load profiles for 20 years into the future, adjusting annually. For the industrial and manufacturing sectors, including public utilities, many factors such as available technologies, market share, and location will drive their longterm forecast. Forecasts, in turn, will further influence investment plans for industry and associated industries as well as demand management plans for regulators and utilities. The system load shape is important for organizing future construction planning and tariff design. For instance, demand forecasting models can provide an assessment of the impact of new technology on overall energy consumption, a fact that may allow technologies such as geothermal power to seek rent in the form of attribute values, which could trade on a separate market13 and increase returns on the base investment. For instance, demand forecasts are often done for each consumer category and voltage level. Charging the commercial, industrial, and large consumers a higher charge, which is then used to subsidize social reform programs, optimizes revenues while keeping social objectives in mind. The forecast may also indicate a relative category of higher willingness or ability to pay vs. those needing subsidy. In electricity markets, electricity demand forecasts are of interest to suppliers (responsible for meeting demand), grid operators (responsible for dispatch and system security), and generators. Generators use forecasts to estimate delivered power prices and to calculate imbalance charges, which are particularly important for volatile fuel costs and some renewable technologies. Energy and peak demand growth rates generally hover around 2% a year.PDF Image | Energy Sector Fundamentals
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