Long-term reserve requirements planning and decision-making based on a conditional cost/benefit analysis

Reserve requirement evaluation is sensitive to the catastrophic generation deficits and extreme interruption losses, but traditional overall-average-based reliability costs and benefits are flawed to reflect severe and rare damages that decision-makers might particularly concern about. Thus a conditional cost/benefit analysis model was proposed, integrating the concepts of conditional reliability cost and benefit into the optimization of long-term reserve expansion. Recognizing the concerned cost domains of decision-makers by conditional factors, this model can highlight distinctive risk preferences and risk attitudes of decision-makers. We proposed a concept of acceptance margin to verify the final acceptance of the conditional optimal reserve requirements, in terms of conditional total costs. A sequential Mote Carlo simulation based method was used to calculate the costs and benefits, and thus solve the model. An IEEE-RTS79 case study illustrates the necessity of optimizing the reserve conditionally, and shows the significant impacts of personal preferences on reserve requirements. With the concerned cost domains converting into extreme interruption losses from overall-average values, the power system requirement for reserve capacity continuously increases.