Composite-system generation adequacy planning using stochastic programming with Sample-Average Approximation

This paper proposes a method for generation expansion planning including reliability considerations at the composite-system level. Reliability indices used in this problem are expected load loss in MW and expected cost of load loss in dollars. Using DC load flow model, the problem is formulated as a two-stage recourse model with the objective to minimize expansion cost and expected cost of load loss. The expected load loss is included in the model as a constraint. Random uncertainties in generation, transmission lines, and load are included in the model resulting in a large number of system states. The expected cost of load loss is then approximated using a technique called Sample-Average Approximation (SAA) with Monte Carlo sampling. The method is illustrated on a 24-bus IEEE-RTS. The method can provide an optimal location for new generation resources and this information can be used by entities like ISOs to generate price signals or other incentives for materializing such resources.

Composite-system generation adequacy planning using stochastic programming with Sample-Average Approximation Conference Paper