Multi-Stage Stochastic Programming With Nonanticipativity Constraints for Expansion of Combined Power and Natural Gas Systems

Abstract

A novel multi-stage stochastic programming model is proposed for the expansion coplanning of gas and power networks considering the uncertainties in net load demand. Meanwhile, the nonanticipativity constraints are taken into account to guarantee the decisions should only depend on the information of realized uncertainties up to the present stage. Compared with the traditional two-stage stochastic programming model, the proposed multi-stage stochastic programming model yields sequential investment decisions with the uncertainties revealed gradually over time, such that the investment decisions are capable of keeping future options open and can shift from “never be changed” decisions to a flexible “wait and see” decisions. The test on three systems shows the effectiveness of the proposed multi-stage stochastic programming model.