Stochastic Pooling Problems in Natural Gas Value Chains

In this thesis, a Benders decomposition algorithm is designed and implemented to solve both deterministic and stochastic pooling problems to global optimality. Convergence of the algorithm to a global optimum is proved and then it is implemented both in GAMS and C++ to get the best performance. A series of example problems are solved, both with the proposed Benders decomposition algorithm and commercially available global optimiza-tion software to determine the validity and the performance of the proposed algorithm. Moreover, a two stage stochastic pooling problem is formulated to model the optimal ca-pacity expansion problem in pooling networks and the proposed algorithm is applied to this problem to obtain global optimum. A number of example stochastic pooling problems are solved, both with the proposed Benders decomposition algorithm and commerciall