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

Considering Multiple Uncertainties in Stochastic Security-Constrained Unit Commitment Using Point Estimation Method