Application of sparse-grid technique to chance constrained optimal power flow

The method of chance constrained optimisation (CCOPT) provides a suitable way to address operations planning of power transmission networks under uncertainty. However, since many uncertain variables as well as many output constraints have to be considered in optimal power flow (OPF), the computational demand to solve the CCOPT problem will be prohibitive. In this study, the authors employ the sparse-grid technique for computing the values and gradients of the objective function and probability constraints, with which the computation efficiency can be significantly enhanced. The authors consider optimal operations planning under uncertain demands at different nodes of networks. Based on the non-linear OPF model, the results of solving the CCOPT problem for the IEEE 57-bus and 118-bus systems demonstrate the efficiency of the proposed approach.