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The author outlines a procedure for forecasting the
mean and the variance of the average price of
electricity over a specified time interval in a
deregulated market. Such information would be found
useful in financial forecasts, risk management,
derivative pricing, investment and operational
decisions. It is based on a system model in which the
physical and engineering processes and the bidding
strategies are simultaneously considered. A potential
advantage of this approach is that it can consider
changes in system''s structure over time (e.g., entry
of additional generators or a change in load.) The
emphasis in the current work is on the use of
analytical methods to forecast the statistical
distributions of prices. The estimates of variances
in addition to those of the expected values would
allow computation of prediction intervals for the
price as well as individual firm''s profits, and will
be useful for the purposes of risk management, for
example, in the computation of the Value-at-Risk
(VaR). The system based approach in this work is an
important first step in the construction of a
comprehensive model, which may help to design and
manage electricity deregulated markets.
mean and the variance of the average price of
electricity over a specified time interval in a
deregulated market. Such information would be found
useful in financial forecasts, risk management,
derivative pricing, investment and operational
decisions. It is based on a system model in which the
physical and engineering processes and the bidding
strategies are simultaneously considered. A potential
advantage of this approach is that it can consider
changes in system''s structure over time (e.g., entry
of additional generators or a change in load.) The
emphasis in the current work is on the use of
analytical methods to forecast the statistical
distributions of prices. The estimates of variances
in addition to those of the expected values would
allow computation of prediction intervals for the
price as well as individual firm''s profits, and will
be useful for the purposes of risk management, for
example, in the computation of the Value-at-Risk
(VaR). The system based approach in this work is an
important first step in the construction of a
comprehensive model, which may help to design and
manage electricity deregulated markets.