In this paper, the optimization strategy of reserve capacity and cost sharing mechanism are studied considering the source-load uncertainty. The probability distribution model of wind and PV forecast deviation is improved based on Gauss-Laplace distribution, and an improved Latin hypercube sampling method is proposed based on Box-Muller transformation to promote the efficiency and accuracy. And then a reserve capacity optimization model is constructed to minimize the cost considering the constraints of condition risk. Finally, a reserve cost sharing mechanism is established with the objective of achieving Maxmin fairness in the allocation utility value and the constraint interval of cost allocation as the constraint condition. The IEEE-30 standard test cases show that the improved Latin hypercube sampling method can effectively improve the sampling efficiency and reduce the computation time, and the benefit sharing is more reasonable based on the proposed strategy, which can more effectively motivate the demand side to participate in the standby market.

reserve capacity  /  Box Muller transformation  /  Latin hypercube sampling  /  cost sharing  /  utility resource equivalence