Are existing ancillary service markets adequate with high penetrations of variable generation?

The inherent variability of wind generation may 1) increase the operating costs of the conventional generators used to follow the net load not supplied by wind capacity (i.e. due to additional ramping costs), and 2) increase the amount of reserve conventional generating capacity needed to maintain Operating Reliability. For customers, the higher operating costs for conventional generators caused by additional ramping are largely offset by lower wholesale prices, due to reductions in the total annual generation from fossil fuels. However, the lower wholesale prices ($/MWh) imply lower annual earnings for conventional generators that lead to higher amounts of missing money ($/MW) needed to maintain the Financial Adequacy of installed generating units. In addition, the operating costs for the generating units that provide ramping will be higher, and these costs are not covered in the standard markets that supply regulation. The objective of this paper is to determine how wind variability affects the optimal hour-to-hour dispatch of generating units and the corresponding operating costs and wholesale prices. The results show that incorporating the cost of ramping can have substantial effects on these costs and on the optimum amount of wind capacity dispatched and the amount of reserve generating capacity needed for reliability. The Cornell SuperOPF is used to illustrate how the operating costs and wholesale prices can be determined for a reliable network (the amount of conventional generating capacity needed to maintain Operating Reliability is determined endogenously). In previous research using the SuperOPF, the analyses have been based on optimizing the dispatch and reserves for typical hours. In contrast, the results in this paper use a typical daily pattern of load and capture the cost of ramping by including additions to the operating costs of the generating units associated with the hour-to-hour changes in their optimal dispatch. The calculations for determining endogenous up and down reserves are included, and the wind generation cost is assumed to be zero. Additionally, the maximum and minimum available capacities for all hours in the day are constrained to the optimal capacities for the hours with the highest and the lowest loads. Different scenarios are evaluated for a given hourly realization of wind speeds using specified amounts of installed wind capacity with and without ramping costs. The analysis also evaluates the effects of eliminating network constraints and the daily variability of the wind resource.