Integration of Stochastic Power Generation, Geographical Averaging and Load Response

The stochastic nature of generation from renewable sources can in certain cases increase the costs for dispatchable generation, as well as increase the amount of reserves needed for Operational Reliability. This is likely to happen when conventional generation is used to counteract for unforeseen shortages of renewable generation. The objective of this paper is to analyze how the variability of wind affects optimal dispatches and reserves in a daily optimization cycle. The Cornell SuperOPF1 with several periods optimization is used to illustrate how the system costs can be determined for a reliable network (the amount of conventional generating capacity needed to maintain System Adequacy is determined endogenously). Five cases are studied to illustrate the effects of geographical distribution, ramping costs and load response to customers payment in the wholesale market, and the amount of potential wind generation that is dispatched. 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 proposed regulatory changes for electricity markets are 1) to establish a new market for ramping services, 2) to aggregate the loads of customers on a distribution network so that they can be represented as a single wholesale customer on the bulk-power transmission network and 3) to make use of controllable load to mitigate the variability of wind generation as an alternative to upgrading the capacity of the transmission network. The cost of ramping reduces the amount of potential wind generation that is dispatched because of the inherent variability of wind speeds. The analysis evaluates whether the ability to dispatch some load that is not time-sensitive, such as charging the batteries in electric vehicles over night above the minimum usage requirement, can be an effective way to use more of the potential wind generation. This can help in environments where upgrading the transfer capacity of a transmission network presents political hurdles in the short term. The expectation is that more wind generation can be dispatched at times when load is relatively low and congestion on the network is not a major limitation.