  Security-Constrained Unit Commitment (SCUC) is one of the most significant
problems in secure and optimal operation of modern electricity markets. New
sources of uncertainties such as wind speed volatility and price-sensitive
loads impose additional challenges to this large-scale problem. This paper
proposes a new Stochastic SCUC using point estimation method to model the power
system uncertainties more efficiently. Conventional scenario-based Stochastic
SCUC approaches consider the Mont Carlo method; which presents additional
computational burdens to this large-scale problem. In this paper we use point
estimation instead of scenario generating to detract computational burdens of
the problem. The proposed approach is implemented on a six-bus system and on a
modified IEEE 118-bus system with 94 uncertain variables. The efficacy of
proposed algorithm is confirmed, especially in the last case with notable
reduction in computational burden without considerable loss of precision.
