Z-method for power system resource adequacy applications

Utilities have long struggled with establishing resource planning criteria that ensure adequate resources to meet loads at low cost. Historically, many utilities used planning reserve margin criteria. The onset of deregulation brought about a paradigm shift in which it was expected that markets would provide a more efficient mechanism for maintaining resource sufficiency in the course of system demand growth. Major power shortages in the Midwest and California in the wake of deregulation led to a reexamination by most regions of the need for centralized resource planning and integrated resource plans. Reserve margin techniques continue to be used by many resource planners to ensure resource adequacy. Simulation-based probabilistic assessments can provide a more direct measure of adequacy but are quite intensive computationally and therefore only allow exploring a limited number of scenarios. In this paper, we suggest a simple analytical probabilistic approach to maintaining resource adequacy and calculating peak load carrying capability of incremental generating units. The methodology targets a level of system adequacy, rather than a specified reserve margin, under system expansion. It provides a powerful technique for simply calculating probability-based load carrying capability of resource additions without iteratively running computationally intensive stochastic computer models. The technique also provides a simple but effective method for developing portfolios of resources with comparable contributions to system adequacy. The latter may be employed in capacity expansion algorithms as a simpler, more efficient, and more accurate method of determining least-cost resource additions than targeting planning reserve margins. Applications of these techniques to the IEEE Reliability Test System illustrate the methods and verify the results with a stochastic model.