As the penetration of wind energy continues to increase and become a central piece of the energy mix in the United States, it will become increasingly important to consider ways to more efficiently operate power systems to accommodate significant amounts of such a variable resource. Improvements in wind forecasting methods and techniques will clearly play an important role in efficient operations, however, it is not clear that an unbiased joint forecast of load and wind represents the most economic operating point for the balancing authority (BA). Asymmetries in the wind forecast error, combined with asymmetries in costs of accommodating forecast errors suggest that the BA may most economically position itself slightly long or short with respect to the unbiased forecast. An early paper by Milligan, Miller, and Chapman1 identified the asymmetrical economics associated with wind forecast errors. This asymmetry implies that the economic exposure of over-and under-forecasting are not balanced. If this asymmetrical exposure is not recognized by the system operator, this would likely result in unnecessary costs to the power system, and ultimately, consumers. An approach that would result in cost-minimization would recognize the asymmetry of forecast error costs, and position the system at an economically optimal point where the potential economic consequences of forecast errors are balanced. The implication is that the balancing area should position itself slightly long or short based on expected capacity needs and costs. Another consideration in determining the optimal balancing position is whether the wind energy is used within the balancing area or exported to another area. Energy market scheduling conventions can needlessly increase the wind balancing area's regulation requirements without providing a compensating decrease in the load balancing area's reserves. This economic inefficiency can be eliminated once it is recognized. This paper provides a detailed discussion of these issues, and illustrates with specific examples. Using these examples, we show why neutral wind forecasts may not be the best generation schedules for wind power plants, and how intra-area schedules should be treated to avoid imposing non-productive reserve requirements.
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